Template-Type: ReDIF-Article 1.0 Author-Name: P. Glewwe Author-X-Name-First: P. Author-X-Name-Last: Glewwe Title: A test of the normality assumption in ordered probit model Abstract: This paper presents a Lagrange multiplier test of the normality assumption underlying the ordered probit model. The test is presented both for the standard ordered probit model and a version in which censoring is present in the dependent variable. The test is then compared to normality tests proposed here compares favorably to tests based on artificial regression techinques. Journal: Econometric Reviews Pages: 1-19 Issue: 1 Volume: 16 Year: 1997 Keywords: Ordered Probit, Normality, Specification Tests, Lagrange Multiplier Test, Mote Carlo Simulations, X-DOI: 10.1080/07474939708800369 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939708800369 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:16:y:1997:i:1:p:1-19 Template-Type: ReDIF-Article 1.0 Author-Name: H. Peter Boswijk Author-X-Name-First: H. Peter Author-X-Name-Last: Boswijk Author-Name: Jean-Pierre Urbain Author-X-Name-First: Jean-Pierre Author-X-Name-Last: Urbain Title: Lagrance-multiplier tersts for weak exogeneity: a synthesis Abstract: This paper unifies two seemingly separate approaches to test weak exogeneity in dynamic regression models with Lagrange-mulptiplier statistics. The first class of tests focuses on the orthogonality between innovations and conditioning variables, and thus is related to the Durbin-Wu-Hausman specification test. The second approach has been developed more recently in the context of context of cointegration and error correction models, ad concentrates on the question whether the conditioning variables display error correction behaviour. It is shown that the vital difference between the two approaches stems from the choice of the parmeters of interest. A new test is derived, which encompasses both its predecessors. The test is applied to an error correction model of the demand for money in Switzerland. Journal: Econometric Reviews Pages: 21-38 Issue: 1 Volume: 16 Year: 1997 Keywords: error correction models, exogeneity, lagrange-multiplier test, money do-mand, X-DOI: 10.1080/07474939708800370 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939708800370 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:16:y:1997:i:1:p:21-38 Template-Type: ReDIF-Article 1.0 Author-Name: Francisco Cribari-Neto Author-X-Name-First: Francisco Author-X-Name-Last: Cribari-Neto Title: On the corrections to information matrix tests Abstract: This paper addresses the issue of designing finite-sample corrections to information matrix tests. We review a Cornish-Fisher correction that has been propowed elsewhere and propose an alternative, Bartlett-type correction. Simulation results for skewness, excess kurtosis, normality and heteroskedasticity tests are given. Journal: Econometric Reviews Pages: 39-53 Issue: 1 Volume: 16 Year: 1997 Keywords: and Phrases: Bartlett correction: Cornish-Fisher expansion: Edgeworth expansion; heteroskedasticity test; information matrix test; normality test; size-correction, X-DOI: 10.1080/07474939708800371 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939708800371 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:16:y:1997:i:1:p:39-53 Template-Type: ReDIF-Article 1.0 Author-Name: Gloria Gonzalez-Rivera Author-X-Name-First: Gloria Author-X-Name-Last: Gonzalez-Rivera Title: A note on adaptation in garch models Abstract: In the framework of the Engle-type (G)ARCH models, I demonstrate that there is a family of symmetric and asymmetric density functions for which the asymptotic efficiency of the semiparametric estimator is equal to the asymptotic efficiency of the maximum likelihood estimator. This family of densities is bimodal (except for the normal). I also chracterize the solution to the problem of minimizing the mean squared distance between the parametric score and the semiparametric score in order to search for unimodal densities for which the semiparametric estimator is likely to perform well. The LaPlace density function emerges as one of these cases. Journal: Econometric Reviews Pages: 55-68 Issue: 1 Volume: 16 Year: 1997 Keywords: Adaptation, Generalized Autoregressive Conditional Heteroscedasticity (GARCH), maximum likelihood, semiparametric estimator, X-DOI: 10.1080/07474939708800372 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939708800372 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:16:y:1997:i:1:p:55-68 Template-Type: ReDIF-Article 1.0 Author-Name: Christopher Skeels Author-X-Name-First: Christopher Author-X-Name-Last: Skeels Author-Name: Franics Vella Author-X-Name-First: Franics Author-X-Name-Last: Vella Title: Monte carlo evidence on the robustness of conditional moment tests in tobit and probit models Abstract: This paper numerically examines the size robustness of various conditional moment tests in misspecified tobit and probit models. The misspecifications considered include the incorrect exclusion of regressors, ignored heteroskedasticity and false distributional assumptions. An important feature of the experimental design is that it is based on an existing empirical study and is more realistic than many simulation studies. The tests are seen to have mixed performance depending on both the original null hypothesis being tested and type of misspecification encountered. Journal: Econometric Reviews Pages: 69-92 Issue: 1 Volume: 16 Year: 1997 Keywords: and Phrases, probit models, tobit models, conditional moment tests, omitted variables, heteroskedasticity, non-normality, X-DOI: 10.1080/07474939708800373 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939708800373 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:16:y:1997:i:1:p:69-92 Template-Type: ReDIF-Article 1.0 Author-Name: Pene Kalulumia Author-X-Name-First: Pene Author-X-Name-Last: Kalulumia Author-Name: Denis Bolduc Author-X-Name-First: Denis Author-X-Name-Last: Bolduc Title: Generalized mixed estimator for nonlinear models: a maximum likelihood approach Abstract: This paper considers the problem of estimating a nonlinear statistical model subject to stochastic linear constraints among unknown parameters. These constraints represent prior information which originates from a previous estimation of the same model using an alternative database. One feature of this specification allows for the disign matrix of stochastic linear restrictions to be estimated. The mixed regression technique and the maximum likelihood approach are used to derive the estimator for both the model coefficients and the unknown elements of this design matrix. The proposed estimator whose asymptotic properties are studied, contains as a special case the conventional mixed regression estimator based on a fixed design matrix. A new test of compatibility between prior and sample information is also introduced. Thesuggested estimator is tested empirically with both simulated and actual marketing data. Journal: Econometric Reviews Pages: 93-107 Issue: 1 Volume: 16 Year: 1997 Keywords: nonlinear models, mixed regression, maximum likelihood, stochastic linear constraints, X-DOI: 10.1080/07474939708800374 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939708800374 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:16:y:1997:i:1:p:93-107 Template-Type: ReDIF-Article 1.0 Author-Name: Larry Taylor Author-X-Name-First: Larry Author-X-Name-Last: Taylor Title: An R2criterion based on optimal predictors Abstract: The predictor that minimizes mean-squared prediction error is used to derive a goodness-of-fit measure that offers an asymptotically valid model selection criterion for a wide variety of regression models. In particular, a new goodness-of-fit criterion (cr2) is proposed for censored or otherwise limited dependent variables. The new goodness-of-fit measure is then applied to the analysis of duration. Journal: Econometric Reviews Pages: 109-118 Issue: 1 Volume: 16 Year: 1997 Keywords: goodness-of-fit, optimal predictor, nonlinear, multivariate, instrumental variables, deration, JET Classification Numbers: C50, C52, C41, X-DOI: 10.1080/07474939708800375 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939708800375 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:16:y:1997:i:1:p:109-118 Template-Type: ReDIF-Article 1.0 Author-Name: Kazuhiro Ohtani Author-X-Name-First: Kazuhiro Author-X-Name-Last: Ohtani Author-Name: David Giles Author-X-Name-First: David Author-X-Name-Last: Giles Author-Name: Judith Giles Author-X-Name-First: Judith Author-X-Name-Last: Giles Title: The exact risk performance of a pre-test estimator in a heteroskedastic linear regression model under the balanced loss function Abstract: We examine the risk of a pre-test estimator for regression coefficients after a pre-test for homoskedasticity under the Balanced Loss Function (BLF). We show analytically that the two stage Aitken estimator is dominated by the pre-test estimator with the critical value of unity, even if the BLF is used. We also show numerically that both the two stage Aitken estimator and the pre-test estimator can be dominated by the ordinary least squares estimator when “goodness of fit” is regarded as more important than precision of estimation. Journal: Econometric Reviews Pages: 119-130 Issue: 1 Volume: 16 Year: 1997 Keywords: balanced loss, heteroskedasticity, sequential estimator, goodness of fit, X-DOI: 10.1080/07474939708800376 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939708800376 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:16:y:1997:i:1:p:119-130 Template-Type: ReDIF-Article 1.0 Author-Name: Maxwell King Author-X-Name-First: Maxwell Author-X-Name-Last: King Author-Name: Ping Wu Author-X-Name-First: Ping Author-X-Name-Last: Wu Title: Locally optimal one-sided tests for multiparameter hypotheses Abstract: Journal: Econometric Reviews Pages: 131-156 Issue: 2 Volume: 16 Year: 1997 Keywords: autoregressive disturbances, heteroscedasticity, Lagrange multiplier test, linear regression, locally most mean powerful test, variance components, X-DOI: 10.1080/07474939708800379 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939708800379 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:16:y:1997:i:2:p:131-156 Template-Type: ReDIF-Article 1.0 Author-Name: Kosuke Oya Author-X-Name-First: Kosuke Author-X-Name-Last: Oya Author-Name: Kosuke Oya Author-X-Name-First: Kosuke Author-X-Name-Last: Oya Title: Wald,LM and LR test statistics of linear hypothese in a strutural equation model Abstract: For the linear hypothesis in a strucural equation model, the properties of test statistics based on the two stage least squares estimator (2SLSE) have been examined since these test statistics are easily derived in the instrumental variable estimation framework. Savin (1976) has shown that inequalities exist among the test statistics for the linear hypothesis, but it is well known that there is no systematic inequality among these statistics based on 2SLSE for the linear hypothesis in a structural equation model. Morimune and Oya (1994) derived the constrained limited information maximum likelihood estimator (LIMLE) subject to general linear constraints on the coefficients of the structural equation, as well as Wald, LM and Lr Test statistics for the adequacy of the linear constraints. In this paper, we derive the inequalities among these three test statistics based on LIMLE and the local power functions based on Limle and 2SLSE to show that there is no test statistic which is uniformly most powerful, and the LR test statistic based on LIMLE is locally unbised and the other test statistics are not. Monte Carlo simulations are used to examine the actual sizes of these test statistics and some numerical examples of the power differences among these test statistics are given. It is found that the actual sizes of these test statistics are greater than the nominal sizes, the differences between the actual and nominal sizes of Wald test statistics are generally the greatest, those of LM test statistics are the smallest, and the power functions depend on the correlations between the endogenous explanatory variables and the error term of the structural equation, the asymptotic variance of estimator of coefficients of the structural equation and the number of restrictions imposed on the coefficients. Journal: Econometric Reviews Pages: 157-178 Issue: 2 Volume: 16 Year: 1997 X-DOI: 10.1080/07474939708800380 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939708800380 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:16:y:1997:i:2:p:157-178 Template-Type: ReDIF-Article 1.0 Author-Name: Mark Jensen Author-X-Name-First: Mark Author-X-Name-Last: Jensen Title: Revisiting the flexibility and regularity properties of the asymptotically ideal production model Abstract: In this paper we estimate the flexibility properties and regular regions for the first three orders of the seminonparametric Asymptotically Ideal Model (AIM) under four different types of constant returns to scale production technologies. The AIM model's parameters are estimatedfrom a Monte Carlo simulation where the data is generated from a three input, one output, globally regular Constant Differences of Elasticity of Substitution function. The Monte Carlo's input quantity and elasticity of substitution estimates at the unit vector are graphed along with the area of the relative price space where the AIM model is monotonically increasing andquasi-concave. Journal: Econometric Reviews Pages: 179-203 Issue: 2 Volume: 16 Year: 1997 Keywords: flexible functional forms, seminonparametric models, regular regions, X-DOI: 10.1080/07474939708800381 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939708800381 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:16:y:1997:i:2:p:179-203 Template-Type: ReDIF-Article 1.0 Author-Name: Fabio Fornari Author-X-Name-First: Fabio Author-X-Name-Last: Fornari Author-Name: Antonio Mele Author-X-Name-First: Antonio Author-X-Name-Last: Mele Title: Weak convergence and distributional assumptions for a general class of nonliner arch models Abstract: Journal: Econometric Reviews Pages: 205-227 Issue: 2 Volume: 16 Year: 1997 Keywords: non linear ARCH; continuous record asymptotics; stochastic volatility; option pricing theory, X-DOI: 10.1080/07474939708800382 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939708800382 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:16:y:1997:i:2:p:205-227 Template-Type: ReDIF-Article 1.0 Author-Name: Ana Fernandez Author-X-Name-First: Ana Author-X-Name-Last: Fernandez Author-Name: Juan Rodriquez-Poo Author-X-Name-First: Juan Author-X-Name-Last: Rodriquez-Poo Title: Estimation and specification testing in female labor participation models: parametric and semiparametric methods Abstract: Female labor participation models have been usually studied through probit and logit specifications. Little attention has been paid to verify the assumptions that are used in these sort of models, basically distributional assumptions and homoskedasticity. In this paper we apply semiparametirc methods in order to test the previous hypothesis. We also estimate a Spanish female labor participation model using both parametric and semiparametirc approaches. The parametirc model includes fixed and random coefficients probit specification. The estimation procedures are parametric maximum likelihood for both probit and logit models, and semiparametric quasi maximum likelihood following Klein and Spady (1993). The results depend cricially in the assumed model. Journal: Econometric Reviews Pages: 229-247 Issue: 2 Volume: 16 Year: 1997 Keywords: Female labor participation models, Homoskedasticity test, Distributional assumptions, Semiparametirc estimation, X-DOI: 10.1080/07474939708800383 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939708800383 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:16:y:1997:i:2:p:229-247 Template-Type: ReDIF-Article 1.0 Author-Name: James Davidson Author-X-Name-First: James Author-X-Name-Last: Davidson Author-Name: Robert de Jong Author-X-Name-First: Robert Author-X-Name-Last: de Jong Title: Strong laws of large numbers for dependent heterogeneous processes: a synthesis of recent and new results Abstract: This paper surveys recent developments in the strong law of large numbers for dependent heterogeneous processes. We prove a generalised version of a recent strong law for Lz-mixingales, and also a new strong law for Lpmixingales. These results greatly relax the dependence and heterogeneity conditions relative to those currently cited, and introduce explicit trade-offs between dependence and heterogeneity. The results are applied to proving strong laws for near-epoch dependent functions of mixing processes. We contrast several methods for obtaining these results, including mapping directly to the mixingale properties, and applying a truncation argument. Journal: Econometric Reviews Pages: 251-279 Issue: 3 Volume: 16 Year: 1997 Keywords: Strong law of large numbers, mixing, mixingales, near-epoch dependence, JEL Classification: C19, X-DOI: 10.1080/07474939708800387 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939708800387 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:16:y:1997:i:3:p:251-279 Template-Type: ReDIF-Article 1.0 Author-Name: H. Penm Jammie Author-X-Name-First: H. Penm Author-X-Name-Last: Jammie Author-Name: H. W. Penm Jack Author-X-Name-First: H. W. Penm Author-X-Name-Last: Jack Author-Name: R. D. Terrell Author-X-Name-First: R. D. Author-X-Name-Last: Terrell Title: The selection of zero-non-zero patterned cointegrating vectors in error-correction modelling Abstract: An effective and efficient search algorithm has been developed to select from an 1(1) system zero-non-zero patterned cointegrating and loading vectors in a subset VECM, Bq(l)y(t-1) + Bq-1 (L)Ay(t) = ε( t ) , where the long term impact matrix Bq(l) contains zero entries. The algorithm can be applied to higher order integrated systems. The Finnish money-output model presented by Johansen and Juselius (1990) and the United States balanced growth model presented by King, Plosser, Stock and Watson (1991) are used to demonstrate the usefulness of this algorithm in examining the cointegrating relationships in vector time series. Journal: Econometric Reviews Pages: 281-314 Issue: 3 Volume: 16 Year: 1997 Keywords: cointegration, vector error correction modelling, X-DOI: 10.1080/07474939708800388 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939708800388 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:16:y:1997:i:3:p:281-314 Template-Type: ReDIF-Article 1.0 Author-Name: Jose-Mari Sarabia Author-X-Name-First: Jose-Mari Author-X-Name-Last: Sarabia Title: A hierarchy of lorenz curves based on the generalized tukey's lambda distribution Abstract: A hierarchy of Lorenz curves based on the generalized Tukey's Lambda distribution is proposed. Representations of the corresponding distribution and density function are also provided, together with popular inequality measures. Estimation methods are suggested. Finally, a comparison with other parametric families of Lorenz curves is established. Journal: Econometric Reviews Pages: 305-320 Issue: 3 Volume: 16 Year: 1997 Keywords: Generalized Tukey's Lambda distribution, Classical Pareto Lorenz curve, Gini index, Pietra index, X-DOI: 10.1080/07474939708800389 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939708800389 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:16:y:1997:i:3:p:305-320 Template-Type: ReDIF-Article 1.0 Author-Name: Kenneth Stewart Author-X-Name-First: Kenneth Author-X-Name-Last: Stewart Title: Exact testing in multivariate regression Abstract: An F statistic due to Rao (1951,1973) tests uniform mixed linear restrictions in the multivariateregression model. In combination with a generalization of the Bera-Evans-Savin exact functional relationship between the W, LR, and LM statistics, Rao's F serves to unify a number of exact test procedures commonly applied in disparate empirical literatures. Examples in demand analysis and asset pricing are provided. The availability of exact tests of restrictions in certain nonlinear models when the model is linear under the null, originally explored by Milliken-Graybill (1970), is extended to multivariate regression. Generalized RESET, J-, and Hausman-Wu tests are resented. As an extension of Dufour (1989), bounds tests exist for nonlinear and inequality restrictions. Applications include conservative bound tests for symmetry or negativity of the substitution matrix in demand systems. Journal: Econometric Reviews Pages: 321-352 Issue: 3 Volume: 16 Year: 1997 Keywords: exact test, multivariate regression, X-DOI: 10.1080/07474939708800390 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939708800390 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:16:y:1997:i:3:p:321-352 Template-Type: ReDIF-Article 1.0 Author-Name: Chia-Shang James Chu Author-X-Name-First: Chia-Shang James Author-X-Name-Last: Chu Title: Multiple hypothesis test for parameter constancy based on recursive residuals Abstract: This article presents a multiple hypothesis test procedure that combines two well known tests for structural change in the linear regression model, the CUSUM test and the recursive t test. The CUSUM test is run through the sequence of recursive residuals as usual; if the CUSUM plot does not violate the critical lines, one more step is taken to perform the t test for hypothesis of zero mean based on all recursive residuals. The asymptotic size of this multiple hypothesis test is derived; power simulation results suggest that it outperforms the traditional CUSUM test and complements other tests that are currently stressed in econometrics. Journal: Econometric Reviews Pages: 353-360 Issue: 3 Volume: 16 Year: 1997 Keywords: CUSUM test, multiple hypothesis testing, structural change, X-DOI: 10.1080/07474939708800391 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939708800391 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:16:y:1997:i:3:p:353-360 Template-Type: ReDIF-Article 1.0 Author-Name: Andrew Weiss Author-X-Name-First: Andrew Author-X-Name-Last: Weiss Title: Specification tests in ordered logit and probit models Abstract: In this paper, I study the application of various specification tests to ordered logit and probit models with heteroskedastic errors, with the primary focus on the ordered probit model. The tests are Lagrange multiplier tests, information matrix tests, and chi-squared goodness of fit tests. The alternatives are omitted variables in the regression equation, omitted varaibles in the equation describing the heteroskedasticity, and non-logistic/non-normal errors. The alternative error distributions include a generalized logistic distribution in the ordered logit model and the Pearson family in the ordered. Journal: Econometric Reviews Pages: 361-391 Issue: 4 Volume: 16 Year: 1997 Keywords: Lagrange multiplier, Information matrix, Chisquared, X-DOI: 10.1080/07474939708800394 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939708800394 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:16:y:1997:i:4:p:361-391 Template-Type: ReDIF-Article 1.0 Author-Name: Dougas Steigerwald Author-X-Name-First: Dougas Author-X-Name-Last: Steigerwald Title: Uniformly adaptive estimation for models with arma errors Abstract: A semiparametric estimator based on an unknown density isuniformly adaptive if the expected loss of the estimator converges to the asymptotic expected loss of the maximum liklihood estimator based on teh true density (MLE), and if convergence does not depend on either the parameter values or the form of the unknown density. Without uniform adaptivity, the asymptotic expected loss of the MLE need not approximate the expected loss of a semiparametric estimator for any finite sample I show that a two step semiparametric estimator is uniformly adaptive for the parameters of nonlinear regression models with autoregressive moving average errors. Journal: Econometric Reviews Pages: 393-409 Issue: 4 Volume: 16 Year: 1997 Keywords: adaptive, ARMA, semiparametric, uniform convergence, X-DOI: 10.1080/07474939708800395 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939708800395 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:16:y:1997:i:4:p:393-409 Template-Type: ReDIF-Article 1.0 Author-Name: Zhenjuan Liu Author-X-Name-First: Zhenjuan Author-X-Name-Last: Liu Author-Name: Xuewen Lu Author-X-Name-First: Xuewen Author-X-Name-Last: Lu Author-Name: Zhenjuan Liu Author-X-Name-First: Zhenjuan Author-X-Name-Last: Liu Author-Name: Xuewen Lu Author-X-Name-First: Xuewen Author-X-Name-Last: Lu Title: Root-n-consistent semiparametric estimation of partially linear models based on k-nn method Abstract: In the context of the partially linear semiparametric model examined by Robinson (1988), we show that root-n-consisten estimation results established using kernel and series methods can also be obtained by using k-nearest-neighbor (k-nn) method. Journal: Econometric Reviews Pages: 411-420 Issue: 4 Volume: 16 Year: 1997 Keywords: Semiparametric regression, nearest neighbor nonparametric regression, partially linear model, X-DOI: 10.1080/07474939708800396 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939708800396 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:16:y:1997:i:4:p:411-420 Template-Type: ReDIF-Article 1.0 Author-Name: Zacharias Psaradakis Author-X-Name-First: Zacharias Author-X-Name-Last: Psaradakis Title: Testing for unit roots in time series with nearly deterministic seasonal variation Abstract: This paper addresses the problem of testing for the presence of unit autoregressive roots in seasonal time series with negatively correlated moving average components. For such cases, many of the commonly used tests are known to have exact sizes much higher than their nominal significance level. We propose modifications of available test procedures that are based on suitably prewhitened data and feasible generalized least squares estimators. Monte Carlo experiments show that such modifications are successful in reducing size distortions in samples of moderate size. Journal: Econometric Reviews Pages: 421-439 Issue: 4 Volume: 16 Year: 1997 Keywords: and Phrases, Generalized Least Squares, Monte Carlo Experiments, Moving Average, Prewhitening, Seasonality, Unit Roots, X-DOI: 10.1080/07474939708800397 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939708800397 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:16:y:1997:i:4:p:421-439 Template-Type: ReDIF-Article 1.0 Author-Name: Hailong Qian Author-X-Name-First: Hailong Author-X-Name-Last: Qian Author-Name: Peter Schmidt Author-X-Name-First: Peter Author-X-Name-Last: Schmidt Title: The asymptotic equivalence between the iterated improved 2sls estimator and the 3sls estimator Abstract: In this paper we show that the 3SLS estimator of a system of equations is asymptotically equivalent to an iterative 2SLS estimator applied to each equation, augmented with the residuals from the other equations. This result is a natural extension of Telser (1964). Journal: Econometric Reviews Pages: 441-457 Issue: 4 Volume: 16 Year: 1997 Keywords: 2SLS(IV) estimators, Improved 2SLS(IV) estimators, Iterated improved 2SLS(IV) estimators, 3SLS estimators, X-DOI: 10.1080/07474939708800398 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939708800398 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:16:y:1997:i:4:p:441-457 Template-Type: ReDIF-Article 1.0 Author-Name: Lutz Kilian Author-X-Name-First: Lutz Author-X-Name-Last: Kilian Title: Confidence intervals for impulse responses under departures from normality Abstract: Monte Carlo evidence shows that in structural VAR models with fat-tailed or skewed innovations the coverage accuracy of impulse response confidence intervals may deterorate substantially compared to the same model with Gaussian innovations. Empirical evidance suggests that such departures from normality are quite plausible for economic time series. The simulation results suggest that applied researchers are best off using nonparametric bootstrap intervals for impulse responses, regardless of whether or not there is evidence of fat tails or skewness in the error distribution. Allowing for departures from normality is shown to considerably weaken the evidence of the delayed overshooting puzzle in Eichenbaum and Evans (1995). Journal: Econometric Reviews Pages: 1-29 Issue: 1 Volume: 17 Year: 1998 Keywords: structural VAR model, normality assumption, bootstrap, impulse response intervals, delayed overshooting puzzle, X-DOI: 10.1080/07474939808800401 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939808800401 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:17:y:1998:i:1:p:1-29 Template-Type: ReDIF-Article 1.0 Author-Name: Paramsothy Silvapulle Author-X-Name-First: Paramsothy Author-X-Name-Last: Silvapulle Author-Name: Merran Evans Author-X-Name-First: Merran Author-X-Name-Last: Evans Title: Testing for serial correlation in the presence of dynamic heteroscedasticity Abstract: Standard serial correlation tests are derived assuming that the disturbances are homoscedastic, but this study shows that asympotic critical values are not accurate when this assumption is violated. Asymptotic critical values for the ARCH(2)-corrected LM, BP and BL tests are valid only when the underlying ARCH process is strictly stationary, whereas Wooldridge's robust LM test has good properties overall. These tests exhibit similar bahaviour even when the underlying process is GARCH (1,1). When the regressors include lagged dependent variables, the rejection frequencies under both the null and alternative hypotheses depend on the coefficientsof the lagged dependent variables and the other model parameters. They appear to be robust across various disturbance distributions under the null hypothesis. Journal: Econometric Reviews Pages: 31-55 Issue: 1 Volume: 17 Year: 1998 Keywords: serial correlations tests, ARCH-correlated tests, ARMA-ARCH models, X-DOI: 10.1080/07474939808800402 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939808800402 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:17:y:1998:i:1:p:31-55 Template-Type: ReDIF-Article 1.0 Author-Name: Suzanne McCoskey Author-X-Name-First: Suzanne Author-X-Name-Last: McCoskey Author-Name: Chihwa Kao Author-X-Name-First: Chihwa Author-X-Name-Last: Kao Title: A residual-based test of the null of cointegration in panel data Abstract: This paper proposes a residual-based Lagrange Multiplier (LM) test for the null of cointegration in panel data. The test is analogous to the locally best unbiased invariant (LBUI) for a moving average (MA) unit root. The asymptotic distribution of the test is derived under the null. Monte Carlo simulations are performed to study the size and power properties of the proposed test. overall, the empirical sizes of the LM-FM and LM-DOLs are close to the true size even in small samples. The power is quite good for the panels where T ≥ 50, and decent with panels for fewer observation in T. In our fixed sample of N = 50 and T = 50, the presence of a moving average and correlation between the LM-DOLS test seems to be better at correcting these effects, although in some cases the LM-FM test is more powerful. Although much of the non-stationary time series econometrics has been criticized for having more to do with the specific properties of the data set rather than underlying economic models, the recent development of the cointegration literature has allowed for a concrete bridge between economic long run theory and time series methods. Our test now allows for the testing of the null of cointegration in a panel setting and should be of considerable interest to economists in a wide variety of fields. Journal: Econometric Reviews Pages: 57-84 Issue: 1 Volume: 17 Year: 1998 X-DOI: 10.1080/07474939808800403 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939808800403 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:17:y:1998:i:1:p:57-84 Template-Type: ReDIF-Article 1.0 Author-Name: Giorgio Calzolari Author-X-Name-First: Giorgio Author-X-Name-Last: Calzolari Author-Name: Gabriele Fiorentini Author-X-Name-First: Gabriele Author-X-Name-Last: Fiorentini Title: A tobit model with garch errors Abstract: In the context of time series regression, we extend the standard Tobit model to allow for the possibility of conditional heteroskedastic error processes of the GARCH type. We discuss the likelihood function of the Tobit model in the presence of conditionally heteroskedastic errors. Expressing the exact likelihood function turns out to be infeasible, and we propose an approximation by treating the model as being conditionally Gaussian. The performance of the estimator is investigated by means of Monte Carlo simulations. We find that, when the error terms follow a GARCH process, the proposed estimator considerably outperforms the standard Tobit quasi maximum likelihood estimator. The efficiency loss due to the approximation of the likelihood is finally evaluated. Journal: Econometric Reviews Pages: 85-104 Issue: 1 Volume: 17 Year: 1998 Keywords: censored regressions, conditional heteroskedasticity, Monte Carlo simulations, X-DOI: 10.1080/07474939808800404 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939808800404 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:17:y:1998:i:1:p:85-104 Template-Type: ReDIF-Article 1.0 Author-Name: Julia Campos Author-X-Name-First: Julia Author-X-Name-Last: Campos Title: Book review Abstract: Modelling Nonlinear Economic Relationships by Clive W. J. Granger and Timo Teravirta. Pp. x+ 187. Oxford: Oxford University Press, 1993. ($US 21.00 paper) Web Information: www.oup-usa.org/gcdocs/gc-019877320x.h. Journal: Econometric Reviews Pages: 105-108 Issue: 1 Volume: 17 Year: 1998 X-DOI: 10.1080/07474939808800405 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939808800405 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:17:y:1998:i:1:p:105-108 Template-Type: ReDIF-Article 1.0 Author-Name: Mark Steel Author-X-Name-First: Mark Author-X-Name-Last: Steel Title: Bayesian analysis of stochastic volatility models with flexible tails Abstract: An alternative distributional assumption is proposed for the stochastic volatility model. This results in extremely flexible tail behaviour of the sampling distribution for the observables, as well as in the availability of a simple Markov Chain Monte Carlo strategy for posterior analysis. By allowing the tail behaviour to be determined by a separate parameter, we reserve the parameters of the volatility process to dictate the degree of volatility clustering. Treatment of a mean function is formally integrated in the analysis. Some empirical examples on both stock prices and exchange rates clearly indicate the presence of fat tails, in combination with high levels of volatility clustering. In addition, predictive distributions indicate a good fit with these typical financial data sets. Journal: Econometric Reviews Pages: 109-143 Issue: 2 Volume: 17 Year: 1998 Keywords: financial time series, leptokurtic distributions, Markov Chain Monte Carlo, Skewed Exponential Power distribution, X-DOI: 10.1080/07474939808800408 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939808800408 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:17:y:1998:i:2:p:109-143 Template-Type: ReDIF-Article 1.0 Author-Name: Qi Li Author-X-Name-First: Qi Author-X-Name-Last: Li Author-Name: Aman Ullha Author-X-Name-First: Aman Author-X-Name-Last: Ullha Title: Estimating partially linear panel data models with one-way error components Abstract: We consider the problem of estimating a partially linear panel data model whenthe error follows an one-way error components structure. We propose a feasiblesemiparametric generalized least squares (GLS) type estimator for estimating the coefficient of the linear component and show that it is asymptotically more efficient than a semiparametric ordinary least squares (OLS) type estimator. We also discussed the case when the regressor of the parametric component is correlated with the error, and propose an instrumental variable GLS-type semiparametric estimator. Journal: Econometric Reviews Pages: 145-166 Issue: 2 Volume: 17 Year: 1998 Keywords: Partially linear model, individual effects, semiparametric estimation, generalized least squares method, instrumental variable, X-DOI: 10.1080/07474939808800409 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939808800409 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:17:y:1998:i:2:p:145-166 Template-Type: ReDIF-Article 1.0 Author-Name: Kien Tran Author-X-Name-First: Kien Author-X-Name-Last: Tran Title: Estimating mixtures of normal distributions via empirical characteristic function Abstract: This paper uses the empirical characteristic function (ECF) procedure to estimate the parameters of mixtures of normal distributions. Since the characteristic function is uniformly bounded, the procedure gives estimates that are numerically stable. It is shown that, using Monte Carlo simulation, the finite sample properties of th ECF estimator are very good, even in the case where the popular maximum likelihood estimator fails to exist. An empirical application is illustrated using the monthl excess return of the Nyse value-weighted index. Journal: Econometric Reviews Pages: 167-183 Issue: 2 Volume: 17 Year: 1998 Keywords: constrained Maximum-likelihood, empirical characteristic function, grid points, mixtures of normal distribution, moment generating function, Monte Carlo simulation, X-DOI: 10.1080/07474939808800410 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939808800410 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:17:y:1998:i:2:p:167-183 Template-Type: ReDIF-Article 1.0 Author-Name: Andre Lucas Author-X-Name-First: Andre Author-X-Name-Last: Lucas Title: Inference on cointegrating ranks using lr and lm tests based on pseudo-likelihoods Abstract: This paper considers Lagrange Multiplier (LM) and Likelihood Ratio (LR) tests for determining the cointegrating rank of a vector autoregressive system. n order to deal with outliers and possible fat-tailedness of the error process, non-Gaussian likelihoods are used to carry out the estimation. The limiting distributions of the tests based on these non-Gaussian pseudo-)likelihoods are derived. These distributions depend on nuisance parameters. An operational procedure is proposed to perform inference. It appears that the tests based on non-Gaussian pseudo-likelihoods are much more powerful than their Gaussian counterparts if the errors are fat-tailed. Moreover, the operational LM-type test has a better overall performance than the LR-type test. Copyright O 1998 by Marcel Dekker, Inc. Journal: Econometric Reviews Pages: 185-214 Issue: 2 Volume: 17 Year: 1998 Keywords: cointegration, Lagrange multiplier test, likelihood, ratio test, outlier robustness, fat tails, GARCH, pseudo-likelihood, X-DOI: 10.1080/07474939808800411 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939808800411 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:17:y:1998:i:2:p:185-214 Template-Type: ReDIF-Article 1.0 Author-Name: Charles Nelson Author-X-Name-First: Charles Author-X-Name-Last: Nelson Title: Book reviews Abstract: Dynamic Econometrics by David F. Hendry. Pp. xxxiv+869. Oxford: Oxford University Press, 1995. ($US 85.00 cloth, $US 45.00 paper) WEB INFORMATION: www.oup-usa.org/gcdocs/gc_O198283172.ht. Journal: Econometric Reviews Pages: 215-220 Issue: 2 Volume: 17 Year: 1998 X-DOI: 10.1080/07474939808800412 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939808800412 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:17:y:1998:i:2:p:215-220 Template-Type: ReDIF-Article 1.0 Author-Name: Norman Swanson Author-X-Name-First: Norman Author-X-Name-Last: Swanson Title: Book reviews Abstract: Statistical Foundations for Econometric Techniques by Asad Zaman. Pp. xxviS570. London: Academic Press, 1996. ($US 44.95 paper) Web Information: www.apnet.com/textbook/sbe/new9596/zaman.htm. Journal: Econometric Reviews Pages: 221-225 Issue: 2 Volume: 17 Year: 1998 X-DOI: 10.1080/07474939808800413 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939808800413 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:17:y:1998:i:2:p:221-225 Template-Type: ReDIF-Article 1.0 Author-Name: Pascal Lavergne Author-X-Name-First: Pascal Author-X-Name-Last: Lavergne Title: Selection of regressors in econometrics: parametric and nonparametric methods selection of regressors in econometrics Abstract: The present paper addresses the selection-of-regressors issue into a general discrimination framework. We show how this framework is useful in unifying various procedures for selecting regressors and helpful in understanding the different strategies underlying these procedures. We review selection of regressors in linear, nonlinear and nonparametric regression models. In each case we successively consider model selection criteria and hypothesis testing procedures. Journal: Econometric Reviews Pages: 227-273 Issue: 3 Volume: 17 Year: 1998 Keywords: Selection of regressors, Discrimination, JEL Classification: Primary C52: Secondary C20, X-DOI: 10.1080/07474939808800415 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939808800415 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:17:y:1998:i:3:p:227-273 Template-Type: ReDIF-Article 1.0 Author-Name: Zacharias Psaradakis Author-X-Name-First: Zacharias Author-X-Name-Last: Psaradakis Title: Bootstrap-based evaluation of markov-switching time series models Abstract: This paper explores the possibility of evaluating the adequacy of Markov-switching time series models by comparing selected functionals (such as the spectral density function and moving empirical moments) obtained from the data with those of the fitted model using a bootstrap algorithm. The proposed model checking procedure is easy to implement and flexible enough to be adapted to a wide variety of models with parameters subject to Markov regime-switching. Examples with real and artificial data illustrate the potential of the methodology. Journal: Econometric Reviews Pages: 275-288 Issue: 3 Volume: 17 Year: 1998 Keywords: Markov Chain, Moving Estimates, Parametric Bootstrap, Regime Switching, Spectral Density Function, JEL Classification: C15: C22: C52, X-DOI: 10.1080/07474939808800416 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939808800416 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:17:y:1998:i:3:p:275-288 Template-Type: ReDIF-Article 1.0 Author-Name: David Crawford Author-X-Name-First: David Author-X-Name-Last: Crawford Author-Name: Robert Pollak Author-X-Name-First: Robert Author-X-Name-Last: Pollak Author-Name: Francis Vella Author-X-Name-First: Francis Author-X-Name-Last: Vella Title: Simple inference in multinomial and ordered logit Abstract: This paper provides some simple methods of interpreting the coefficients in multinomial logit and ordered logit models. These methods are summarized in Propositions concerning the magnitudes, signs, and patterns of partial derivatives of the outcome probabilities with respect to the exogenousvariables. The paper also provides an empirical example illustrating the use of these Propositions. Journal: Econometric Reviews Pages: 289-299 Issue: 3 Volume: 17 Year: 1998 Keywords: Inference, Mult inomial Logit, Ordered Logit, JEL Classification: C12, X-DOI: 10.1080/07474939808800417 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939808800417 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:17:y:1998:i:3:p:289-299 Template-Type: ReDIF-Article 1.0 Author-Name: Yoon-Jae Whang Author-X-Name-First: Yoon-Jae Author-X-Name-Last: Whang Title: A test of normality using nonparametrlic residuals Abstract: In this paper, we develop a test of the normality assumption of the errors using the residuals from a nonparametric kernel regression. Contrary to the existing tests based on the residuals from a parametric regression, our test is thus robust to misspecification of the regression function. The test statistic proposed here is a Bera-Jarque type test of skewness and kurtosis. We show that the test statistic has the usual x2(2) limit distribution under the null hypothesis. In contrast to the results of Rilstone (1992), we provide a set of primitive assumptions that allow weakly dependent observations and data dependent bandwidth parameters. We also establish consistency property of the test. Monte Carlo experiments show that our test has reasonably good size and power performance in small samples and perfornu better than some of the alternative tests in various situations. Journal: Econometric Reviews Pages: 301-327 Issue: 3 Volume: 17 Year: 1998 Keywords: Nonparametric kernel estimator, Normality test, Skewness, Ihrtosis, Empirical process, X-DOI: 10.1080/07474939808800418 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939808800418 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:17:y:1998:i:3:p:301-327 Template-Type: ReDIF-Article 1.0 Author-Name: H.Peter Boswijk Author-X-Name-First: H.Peter Author-X-Name-Last: Boswijk Title: Book reviews Abstract: Elements of Modern Asymptotic Theo y with Statistical Applications by Brendan McCabe and Andrew ~kemayne. Pp. xi+264. Manchester: Manchester University Press, 1993. (£50 cloth, £17.99 paper) WEB INFORMATION: www.man.ac.uk/mup/ Journal: Econometric Reviews Pages: 329-334 Issue: 3 Volume: 17 Year: 1998 X-DOI: 10.1080/07474939808800419 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939808800419 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:17:y:1998:i:3:p:329-334 Template-Type: ReDIF-Article 1.0 Author-Name: Jon Faust Author-X-Name-First: Jon Author-X-Name-Last: Faust Title: Book reviews Abstract: Periodicity and Stochastic Dends in Economic Time Series by Philip Hans Franses. Pp. xii+230. Oxford: Oxford University Press, 1996. ($US 65.00 cloth, $US 32.50 paper) WEB INFORMATION: www.oupusa.org/docs/0198774540.h. Journal: Econometric Reviews Pages: 335-338 Issue: 3 Volume: 17 Year: 1998 X-DOI: 10.1080/07474939808800420 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939808800420 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:17:y:1998:i:3:p:335-338 Template-Type: ReDIF-Article 1.0 Author-Name: R. Winkelmann Author-X-Name-First: R. Author-X-Name-Last: Winkelmann Title: Count data models with selectivity Abstract: This paper shows how truncated, censored, hurdle, zero inflated and underreported count models can be interpreted as models with selectivity. Until recently, users of such count data models have commonly imposed independence brtween the count generating mechanism and the selection mechanism. Such an assumption is unrealistic in most applications, and various models with endogenous selectivity (correlation between the count and the selection equations) are presented. The methods are illustrated in an application to labor mobility where the dependent variable is the number of individual job changes during a ten year period. Journal: Econometric Reviews Pages: 339-359 Issue: 4 Volume: 17 Year: 1998 Keywords: Poisson distribution, sample selection, underreporting, labor mobility, JEL Classification:C25,C42, X-DOI: 10.1080/07474939808800422 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939808800422 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:17:y:1998:i:4:p:339-359 Template-Type: ReDIF-Article 1.0 Author-Name: W. Tsay Author-X-Name-First: W. Author-X-Name-Last: Tsay Title: On the power of durbin-watson statistic against fractionally integrated processes Abstract: This paper provides the theoretical explanation and Monte Carlo experiments of using a modified version of Durbin-Watson ( D W ) statistic to test an 1 ( 1 ) process against I ( d ) alternatives, that is, integrated process of order d, where d is a fractional number. We provide the exact order of magnitude of the modified D W test when the data generating process is an I ( d ) process with d E (0. 1.5). Moreover, the consistency of the modified DW statistic as a unit root test against I ( d ) alternatives with d E ( 0 , l ) U ( 1 , 1.5) is proved in this paper. In addition to the theoretical analysis, Monte Carlo experiments show that the performance of the modified D W statistic reveals that it can be used as a unit root test against I ( d ) alternatives. Journal: Econometric Reviews Pages: 361-386 Issue: 4 Volume: 17 Year: 1998 Keywords: Durbin-Watson statistic, unit root, fractional Brownian motion, JEL classification:C22, X-DOI: 10.1080/07474939808800423 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939808800423 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:17:y:1998:i:4:p:361-386 Template-Type: ReDIF-Article 1.0 Author-Name: K. Maekawa Author-X-Name-First: K. Author-X-Name-Last: Maekawa Author-Name: J. L. Knight Author-X-Name-First: J. L. Author-X-Name-Last: Knight Author-Name: H. Hisamatsu Author-X-Name-First: H. Author-X-Name-Last: Hisamatsu Title: Finite sample comparisons of the distributions of the ols and gls estimators in regression with an integrated regsorad correlated errors Abstract: We compare the finite sample distributional properties of the OLS and GT,S mtinialors 11 a rcgrassior wilh arl inl,cgrd,ctl rcgrtssor ant1 corrctifical errors of the form of AR(1) and MA(1) processes. The approach is one of first deriving the joint characteristic function of the quadratic forms in the clefiriit,on of t,hc est,irrial,ors and then rurrierically inverting these 1.0 find the distributions. When the characteristic functions are intractable, Monte Carlo integration is employed. We find substantial differences in the finite jarriplc ditributiorls of OLS ant1 C:LS dthough lsynlptotically thee distributions are equivalent. Journal: Econometric Reviews Pages: 387-413 Issue: 4 Volume: 17 Year: 1998 X-DOI: 10.1080/07474939808800424 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939808800424 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:17:y:1998:i:4:p:387-413 Template-Type: ReDIF-Article 1.0 Author-Name: Kuan Xu Author-X-Name-First: Kuan Author-X-Name-Last: Xu Author-Name: L. Osberg Author-X-Name-First: L. Author-X-Name-Last: Osberg Title: A distribution-free test for deprivation dominance Abstract: The Raw1sian perspective on social policy pays particular attentionto the least advantaged members of society, but how should "the least advantaged" be identified? The concept of deprivation dominance operationalizes in part the Rawlsian evaluation of the welfare of the least advantaged members of society, but a statistical procedure for testing deprivation dominance is needed. In this paper, we construct a new distribution-free test for deprivation dominance and apply i t to Canadian income survey data Journal: Econometric Reviews Pages: 415-429 Issue: 4 Volume: 17 Year: 1998 Keywords: deprivation profile, deprivation dominance, poverty, welfare, asymptotic distribution, statistical test, JEL Classification:C12,I32, X-DOI: 10.1080/07474939808800425 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939808800425 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:17:y:1998:i:4:p:415-429 Template-Type: ReDIF-Article 1.0 Author-Name: Ragnar Nymoen Author-X-Name-First: Ragnar Author-X-Name-Last: Nymoen Title: Book reviews Abstract: Journal: Econometric Reviews Pages: 431-442 Issue: 4 Volume: 17 Year: 1998 X-DOI: 10.1080/07474939808800426 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939808800426 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:17:y:1998:i:4:p:431-442 Template-Type: ReDIF-Article 1.0 Author-Name: John Geweke Author-X-Name-First: John Author-X-Name-Last: Geweke Title: Using simulation methods for bayesian econometric models: inference, development,and communication Abstract: This paper surveys the fundamental principles of subjective Bayesian inference in econometrics and the implementation of those principles using posterior simulation methods. The emphasis is on the combination of models and the development of predictive distributions. Moving beyond conditioning on a fixed number of completely specified models, the paper introduces subjective Bayesian tools for formal comparison of these models with as yet incompletely specified models. The paper then shows how posterior simulators can facilitate communication between investigators (for example, econometricians) on the one hand and remote clients (for example, decision makers) on the other, enabling clients to vary the prior distributions and functions of interest employed by investigators. A theme of the paper is the practicality of subjective Bayesian methods. To this end, the paper describes publicly available software for Bayesian inference, model development, and communication and provides illustrations using two simple econometric models. Journal: Econometric Reviews Pages: 1-73 Issue: 1 Volume: 18 Year: 1999 X-DOI: 10.1080/07474939908800428 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939908800428 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:18:y:1999:i:1:p:1-73 Template-Type: ReDIF-Article 1.0 Author-Name: W. E. Griffiths Author-X-Name-First: W. E. Author-X-Name-Last: Griffiths Title: Estimating consumer surplus comments on "using simulation methods for bayesian econometric models: inference development and communication" Abstract: Journal: Econometric Reviews Pages: 75-87 Issue: 1 Volume: 18 Year: 1999 X-DOI: 10.1080/07474939908800429 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939908800429 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:18:y:1999:i:1:p:75-87 Template-Type: ReDIF-Article 1.0 Author-Name: C. Fernandez Author-X-Name-First: C. Author-X-Name-Last: Fernandez Author-Name: M. F. J. Steel Author-X-Name-First: M. F. J. Author-X-Name-Last: Steel Title: Some comments on model development and posterior existence Abstract: We wish to congratulate John Geweke on producing such an interesting and complete paper. We are delighted to see that serious attempts to make Bayesian methods more generally understood and available are being undertaken. In addition, a number of quite challenging issues is addressed here. Whereas we agree with most of what is stated in the paper, it is our (perceived) duty to single out those things that we feel are more contentious. However, we hope that this can lead to a stimulating discussion of general interest and hopefully to our better understanding of these issues. Journal: Econometric Reviews Pages: 89-96 Issue: 1 Volume: 18 Year: 1999 X-DOI: 10.1080/07474939908800430 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939908800430 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:18:y:1999:i:1:p:89-96 Template-Type: ReDIF-Article 1.0 Author-Name: G. Koop Author-X-Name-First: G. Author-X-Name-Last: Koop Author-Name: D. J. Poirier Author-X-Name-First: D. J. Author-X-Name-Last: Poirier Title: Incomplete models and reweighting Abstract: Journal: Econometric Reviews Pages: 97-104 Issue: 1 Volume: 18 Year: 1999 X-DOI: 10.1080/07474939908800431 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939908800431 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:18:y:1999:i:1:p:97-104 Template-Type: ReDIF-Article 1.0 Author-Name: H. K. Van Dijk Author-X-Name-First: H. K. Author-X-Name-Last: Van Dijk Title: Some remarks on the simulation revolution in bayesian econometric inference Abstract: Journal: Econometric Reviews Pages: 105-112 Issue: 1 Volume: 18 Year: 1999 X-DOI: 10.1080/07474939908800432 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939908800432 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:18:y:1999:i:1:p:105-112 Template-Type: ReDIF-Article 1.0 Author-Name: G. M. Martin Author-X-Name-First: G. M. Author-X-Name-Last: Martin Author-Name: C. S. Forbes Author-X-Name-First: C. S. Author-X-Name-Last: Forbes Title: Using simulation methods for bayesian econometric models: inference, development and communication: some comments Abstract: Journal: Econometric Reviews Pages: 113-118 Issue: 1 Volume: 18 Year: 1999 X-DOI: 10.1080/07474939908800433 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939908800433 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:18:y:1999:i:1:p:113-118 Template-Type: ReDIF-Article 1.0 Author-Name: J. Geweke Author-X-Name-First: J. Author-X-Name-Last: Geweke Title: Reply Abstract: Thanks and congratulations to all of the discussants for covering a wide array of important topics. Since space does not permit attention to all of the points that have been raise, this reply will concentrate on trying to dispell confusion on important matters that might remain. Journal: Econometric Reviews Pages: 119-126 Issue: 1 Volume: 18 Year: 1999 X-DOI: 10.1080/07474939908800434 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939908800434 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:18:y:1999:i:1:p:119-126 Template-Type: ReDIF-Article 1.0 Author-Name: D. Ormoneit Author-X-Name-First: D. Author-X-Name-Last: Ormoneit Author-Name: H. White Author-X-Name-First: H. Author-X-Name-Last: White Title: An efficient algorithm to compute maximum entropy densities Abstract: We describe an algorithm to efficiently compute maximum entropy densities, i.e. densities maximizing the Shannon entropy - [image omitted]  under a set of constraints [image omitted] . Our method is based on an algorithm by Zellner and Highfield, which has been found not to converge under a variety of circumstances. To demonstrate that our method overcomes these difficulties, we conduct numerous experiments for the special case gi(x) = xi, n = 4. An extensive table of results for this case and computer code are available on the World Wide Web Journal: Econometric Reviews Pages: 127-140 Issue: 2 Volume: 18 Year: 1999 Keywords: Density Estimation, Maximum Entropy Principle, Shannon Entropy, JEL Classification:C61,C63,C87, X-DOI: 10.1080/07474939908800436 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939908800436 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:18:y:1999:i:2:p:127-140 Template-Type: ReDIF-Article 1.0 Author-Name: R. F. Phillips Author-X-Name-First: R. F. Author-X-Name-Last: Phillips Title: Partially adaptive estimation of nonlinear models via a normal mixture Abstract: This paper extends the partially adaptive method Phillips (1994) provided for linear models to nonlinear models. Asymptotic results are established under conditions general enough they cover both cross-sectional and time series applications. The sampling efficiency of the new estimator is illustrated in a small Monte Carlo study in which the parameters of an autoregressive moving average are estimated. The study indicates that, for non-normal distributions, the new estimator improves on the nonlinear least squares estimator in terms of efficiency. Journal: Econometric Reviews Pages: 141-167 Issue: 2 Volume: 18 Year: 1999 Keywords: ARMA process, nonlinear regression model, quasi maximum likelihood, JEL Classifications:C13,C20, X-DOI: 10.1080/07474939908800437 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939908800437 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:18:y:1999:i:2:p:141-167 Template-Type: ReDIF-Article 1.0 Author-Name: L. G. Godfrey Author-X-Name-First: L. G. Author-X-Name-Last: Godfrey Author-Name: C. D. Orme Author-X-Name-First: C. D. Author-X-Name-Last: Orme Title: The robustness, reliabiligy and power of heteroskedasticity tests Abstract: Several tests for heteroskedasticity in linear regression models are examined. Asymptoticrobustness to heterokurticity, nonnormality and skewness is discussed. The finite sample eliability of asymptotically valid tests is investigated using Monte Carlo experiments. It is found that asymptotic critical values cannot, in general. be relied upon to give good agreement between nominal and actual finite sample significance levels. The use of the bootstrap overcomes this problem for general approaches that lead to asymptotically pivotal test statistics. Power comparisons are made for bootstrap tests and modified Glejser and Koenker tests are recommended. Journal: Econometric Reviews Pages: 169-194 Issue: 2 Volume: 18 Year: 1999 Keywords: heteroskedasticity, robustness, nonnormality, bootstrap, JEL Classification:C12,C52, X-DOI: 10.1080/07474939908800438 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939908800438 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:18:y:1999:i:2:p:169-194 Template-Type: ReDIF-Article 1.0 Author-Name: N. Coulibaly Author-X-Name-First: N. Author-X-Name-Last: Coulibaly Author-Name: B. Wade Brorsen Author-X-Name-First: B. Wade Author-X-Name-Last: Brorsen Title: Monte carlo sampling approach to testing nonnested hypothesis: monte carlo results Abstract: Alternative ways of using Monte Carlo methods to implement a Cox-type test for separate families of hypotheses are considered. Monte Carlo experiments are designed to compare the finite sample performances of Pesaran and Pesaran's test, a RESET test, and two Monte Carlo hypothesis test procedures. One of the Monte Carlo tests is based on the distribution of the log-likelihood ratio and the other is based on an asymptotically pivotal statistic. The Monte Carlo results provide strong evidence that the size of the Pesaran and Pesaran test is generally incorrect, except for very large sample sizes. The RESET test has lower power than the other tests. The two Monte Carlo tests perform equally well for all sample sizes and are both clearly preferred to the Pesaran and Pesaran test, even in large samples. Since the Monte Carlo test based on the log-likelihood ratio is the simplest to calculate, we recommend using it. Journal: Econometric Reviews Pages: 195-209 Issue: 2 Volume: 18 Year: 1999 Keywords: Cox test, Monte Carlo test, Nonnested hypotheses, JEL Classification:C12,C15, X-DOI: 10.1080/07474939908800439 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939908800439 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:18:y:1999:i:2:p:195-209 Template-Type: ReDIF-Article 1.0 Author-Name: F. Cribari-Neto Author-X-Name-First: F. Author-X-Name-Last: Cribari-Neto Author-Name: S. G. Zarkos Author-X-Name-First: S. G. Author-X-Name-Last: Zarkos Title: Bootstrap methods for heteroskedastic regression models: evidence on estimation and testing Abstract: This paper uses Monte Carlo simulation analysis to study the finite-sample behavior of bootstrap estimators and tests in the linear heteroskedastic model. We consider four different bootstrapping schemes, three of them specifically tailored to handle heteroskedasticity. Our results show that weighted bootstrap methods can be successfully used to estimate the variances of the least squares estimators of the linear parameters both under normality and under nonnormality. Simulation results are also given comparing the size and power of the bootstrapped Breusch-Pagan test with that of the original test and of Bartlett and Edgeworth-corrected tests. The bootstrap test was found to be robust against unfavorable regression designs. Journal: Econometric Reviews Pages: 211-228 Issue: 2 Volume: 18 Year: 1999 Keywords: Bartlett-type correction, bootstrap, Edgeworth expansion, heteroskedasticity, Lagrange multiplier test, score test, weighted bootstrap, JEL CLASSIFICATION:C12,C13,C15, X-DOI: 10.1080/07474939908800440 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939908800440 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:18:y:1999:i:2:p:211-228 Template-Type: ReDIF-Article 1.0 Author-Name: Charles Goodhart Author-X-Name-First: Charles Author-X-Name-Last: Goodhart Title: Book reviews Abstract: The Economics of Seasonal Cycles by Jeffrey A. Miron. Pp. xviii+225. Cambridge, Massachusetts: MIT Press, 1996. ($US30.00 cloth) WEB INFORMATION: http://mitpress.mit.edu/book-home.tcl?isbn=O262133237. Journal: Econometric Reviews Pages: 229-230 Issue: 2 Volume: 18 Year: 1999 X-DOI: 10.1080/07474939908800441 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939908800441 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:18:y:1999:i:2:p:229-230 Template-Type: ReDIF-Article 1.0 Author-Name: Pentti Saikkonen Author-X-Name-First: Pentti Author-X-Name-Last: Saikkonen Title: Testing normalization and overidentification of cointegrating vectors in vector autoregressive processes Abstract: This paper develops test procedures for testing the validity of general linear identifying restrictions imposed on cointegrating vectors in the context of a vector autoregressive model. In addition to overidentifying restrictions the considered restrictions may also involve normalizing restrictions. Tests for both types of restrictions are developed and their asymptotic properties are obtained. Under the null hypothesis tests for normalizing restrictions have an asymptotic "multivariate unit root distribution", similar to that obtained for the likelihood ratio test for cointegration, while tests for overidentifying restrictions have a standard chi-square limiting distribution. Since these two types of tests are asymptotically independent they are easy to cotnbine to an overall test for the spccifed identifying restrictions. An overall test of this kind can consistently reveal the failure of the identifying restrictions in a wider class of cases than previous tests which only test for overidentifying restrictions. Journal: Econometric Reviews Pages: 235-257 Issue: 3 Volume: 18 Year: 1999 Keywords: and phrases, cointegration, normalizing restrictions, overidentifying restrictions, vector autoregressive process, X-DOI: 10.1080/07474939908800444 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939908800444 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:18:y:1999:i:3:p:235-257 Template-Type: ReDIF-Article 1.0 Author-Name: Clive Granger Author-X-Name-First: Clive Author-X-Name-Last: Granger Author-Name: Tae-Hwy Lee Author-X-Name-First: Tae-Hwy Author-X-Name-Last: Lee Title: The effect of aggregation on nonlinearity Abstract: This paper investigates the interaction between aggregation and nonlinearity through a monte carlo study. Various tests for neglected nonlinearity are used to compare the power of the tests for different nonlinear models to different levels of aggregation. Three types of aggregation, namely, cross-sectional aggregation, temporal aggregation and systematic sampling are considered. Aggregation is inclined to simplify nonlinearity. The degree to which nonlinearity is reduced depends on the importance of common factor and extent of the aggregation. The effect is larger when the size of common factor is smaller and when the extent of the aggregation is larger. Journal: Econometric Reviews Pages: 259-269 Issue: 3 Volume: 18 Year: 1999 X-DOI: 10.1080/07474939908800445 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939908800445 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:18:y:1999:i:3:p:259-269 Template-Type: ReDIF-Article 1.0 Author-Name: Richard Paap Author-X-Name-First: Richard Author-X-Name-Last: Paap Author-Name: Philip Hans Franses Author-X-Name-First: Philip Hans Author-X-Name-Last: Franses Title: On trends and constants in periodic autoregressions Abstract: Periodic autoregressions are characterised by autoregressive structures that vary with the season. If a time series is periodically integrated, one needs a seasonally varying differencing filter to remove the stochastic trend. When the periodic regression model contains constants and trends with unrestricted parameters, the data can show diverging seasonal deterministic trends. In this paper we derive explicit expressions for parameter restrictions that result in common deterministic trends under periodic trend stationarity and periodic integration. Journal: Econometric Reviews Pages: 271-286 Issue: 3 Volume: 18 Year: 1999 X-DOI: 10.1080/07474939908800446 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939908800446 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:18:y:1999:i:3:p:271-286 Template-Type: ReDIF-Article 1.0 Author-Name: Karim Abadir Author-X-Name-First: Karim Author-X-Name-Last: Abadir Title: An introduction to hypergeometric functions for economists Abstract: Hypergeometric functions are a generalization of exponential functions. They are explicit, computable functions that can also be manipulated analytically. The functions and series we use in quantitative economics are all special cases of them. In this paper, a unified approach to hypergeometric functions is given. As a result, some potentially useful general applications emerge in a number of areas such as in econometrics and economic theory. The greatest benefit from using these functions stems from the fact that they provide parsimonious explicit (and interpretable) solutions to a wide range of general problems. Journal: Econometric Reviews Pages: 287-330 Issue: 3 Volume: 18 Year: 1999 Keywords: and phrases, Hypergeometric functions, distribution theory, non-linear models and discontinues, differential equations; economic theory, utility, production and cost functions, X-DOI: 10.1080/07474939908800447 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939908800447 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:18:y:1999:i:3:p:287-330 Template-Type: ReDIF-Article 1.0 Author-Name: Zacharias Psarasakis Author-X-Name-First: Zacharias Author-X-Name-Last: Psarasakis Title: A note on super exogeneity in linear regression models Abstract: This note considers how hypotheses of invariance and super exogeneity may be formulated and tested in elliptical linear regression models. It is demonstrated that for jointly elliptical random variables super exogeneity will only hold under normality. Journal: Econometric Reviews Pages: 331-336 Issue: 3 Volume: 18 Year: 1999 Keywords: Elliptically contoured distribution, Invariance, Normality, Regression model, Super exogeneity, X-DOI: 10.1080/07474939908800448 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939908800448 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:18:y:1999:i:3:p:331-336 Template-Type: ReDIF-Article 1.0 Author-Name: Kevin Hoover Author-X-Name-First: Kevin Author-X-Name-Last: Hoover Title: Book review Abstract: The Foundations of Econometric Analysis, edited by David F. Hendry and Mary S. Morgan. Pp. xvi+558. Cambridge: Cambridge University Press, 1995. (£19.95 paper, £45.00 cloth). Journal: Econometric Reviews Pages: 337-342 Issue: 3 Volume: 18 Year: 1999 X-DOI: 10.1080/07474939908800449 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939908800449 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:18:y:1999:i:3:p:337-342 Template-Type: ReDIF-Article 1.0 Author-Name: David Edgerton Author-X-Name-First: David Author-X-Name-Last: Edgerton Author-Name: Ghazi Shukur Author-X-Name-First: Ghazi Author-X-Name-Last: Shukur Title: Testing autocorrelation in a system perspective testing autocorrelation Abstract: The Breusch-Godfrey test for autocorrelated errors is generalised to cover systems of equations, and the properties of 18 versions of the test are studied using Monte Carlo methods. We show that only one group of tests regularly has actual size close to the nominal size; namely the likelihood ratio tests of the auxiliary regression system that are corrected in some manner for degrees-of-freedom. The Rao Ftest exhibits the best performance, whilst the commonly used TR2 test behaves badly even in single equations. However, the size and power properties of all tests deteriorate sharply as the number of equations increases, the system becomes more dynamic, the exogenous variables become more autocorrelated and the sample size decreases. This performance has, in general, an unknown degree since the interaction amongst these factors does not permit a predictive summary, as might be hoped for by response surface-type approaches. Journal: Econometric Reviews Pages: 343-386 Issue: 4 Volume: 18 Year: 1999 X-DOI: 10.1080/07474939908800351 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939908800351 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:18:y:1999:i:4:p:343-386 Template-Type: ReDIF-Article 1.0 Author-Name: Myoung-jae Lee Author-X-Name-First: Myoung-jae Author-X-Name-Last: Lee Title: Probability inequalities in multivariate distributions Abstract: For a bivariate binary response model y, = 1 (xj βj+j > 0), j=1,2, we propose to estimate nonpararnetrically the quadrant correlation E{sgn(u1) *sgn(u2)} between the two error terms ul and u2 without specifjing the error term distribution. The quadrant correlation accounts for the relationship between yl and y2 that is not explained by xl and x2, and can be used in testing for the specification of endogenous dummy variable models. The quadrant correlation is further generalized into orthant dependence allowing unknown regression functions, unknown error term distribution and arbitrary forms of heteroskedasticity. A simulation study is provided, followed by a brief application to a real data set. Journal: Econometric Reviews Pages: 387-415 Issue: 4 Volume: 18 Year: 1999 Keywords: binary response, endogenous dummy varible, quadrant correlation, orthant dependence, X-DOI: 10.1080/07474939908800352 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939908800352 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:18:y:1999:i:4:p:387-415 Template-Type: ReDIF-Article 1.0 Author-Name: Steven Wei Author-X-Name-First: Steven Author-X-Name-Last: Wei Title: A bayesian approach to dynamic tobit models Abstract: This paper develops a posterior simulation method for a dynamic Tobit model. The major obstacle rooted in such a problem lies in high dimensional integrals, induced by dependence among censored observations, in the likelihood function. The primary contribution of this study is to develop a practical and efficient sampling scheme for the conditional posterior distributions of the censored (i.e., unobserved) data, so that the Gibbs sampler with the data augmentation algorithm is successfully applied. The substantial differences between this approach and some existing methods are highlighted. The proposed simulation method is investigated by means of a Monte Carlo study and applied to a regression model of Japanese exports of passenger cars to the U.S. subject to a non-tariff trade barrier. Journal: Econometric Reviews Pages: 417-439 Issue: 4 Volume: 18 Year: 1999 Keywords: Bayesian inference, Dynamic Tobit model, The Gibbs sampler with the data augmentation, Monte Carlo simulation, truncated normal distribution, X-DOI: 10.1080/07474939908800353 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939908800353 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:18:y:1999:i:4:p:417-439 Template-Type: ReDIF-Article 1.0 Author-Name: Zacharias Psaradakis Author-X-Name-First: Zacharias Author-X-Name-Last: Psaradakis Author-Name: Elias Tzavalis Author-X-Name-First: Elias Author-X-Name-Last: Tzavalis Title: On regression-based tests for persistence in logarithmic volatility models Abstract: Building on the work of Pantula (1986), this paper discusses how the hypothesis of conditional variance nonstationarity in the logarithmic family of generalized autoregressive conditional heteroskedasticity (GARCH) and stochastic volatility processes may be tested using regression-based tests. The latter are easy to implement, have well-defined large-sample distributions, and are less sensitive to structural changes than tests based on the quasimaximum likelihood estimator. Journal: Econometric Reviews Pages: 441-448 Issue: 4 Volume: 18 Year: 1999 Keywords: conditional heteroskedasticity, nonlinear Garch, persistence, stochastic volatility, regime changes, unit root, X-DOI: 10.1080/07474939908800354 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939908800354 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:18:y:1999:i:4:p:441-448 Template-Type: ReDIF-Article 1.0 Author-Name: Pietro Balestra Author-X-Name-First: Pietro Author-X-Name-Last: Balestra Author-Name: Jaya Krishnakumar Author-X-Name-First: Jaya Author-X-Name-Last: Krishnakumar Title: Announcement and call for papers for the ninth international conference on panel data Abstract: Journal: Econometric Reviews Pages: 449-450 Issue: 4 Volume: 18 Year: 1999 X-DOI: 10.1080/07474939908800355 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474939908800355 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:18:y:1999:i:4:p:449-450 Template-Type: ReDIF-Article 1.0 Author-Name: Jeremy Berkowitz Author-X-Name-First: Jeremy Author-X-Name-Last: Berkowitz Author-Name: Lutz Kilian Author-X-Name-First: Lutz Author-X-Name-Last: Kilian Title: Recent developments in bootstrapping time series Abstract: Journal: Econometric Reviews Pages: 1-48 Issue: 1 Volume: 19 Year: 2000 Keywords: Bootstrap, ARLIA, Frequency Domain, Blocks, X-DOI: 10.1080/07474930008800457 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930008800457 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:19:y:2000:i:1:p:1-48 Template-Type: ReDIF-Article 1.0 Author-Name: Russell Davidson Author-X-Name-First: Russell Author-X-Name-Last: Davidson Author-Name: James MacKinnon Author-X-Name-First: James Author-X-Name-Last: MacKinnon Title: Bootstrap tests: how many bootstraps? Abstract: In practice, bootstrap tests must use a finite number of bootstrap samples. This means that the outcome of the test will depend on the sequence of random numbers used to generate the bootstrap samples, and it necessarily results in some loss of power. We examine the extent of this power loss and propose a simple pretest procedure for choosing the number of bootstrap samples so as to minimize experimental randomness. Simulation experiments suggest that this procedure will work very well in practice. Journal: Econometric Reviews Pages: 55-68 Issue: 1 Volume: 19 Year: 2000 Keywords: bootstrap test, test power, pretest, X-DOI: 10.1080/07474930008800459 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930008800459 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:19:y:2000:i:1:p:55-68 Template-Type: ReDIF-Article 1.0 Author-Name: Alexander Benkwitz Author-X-Name-First: Alexander Author-X-Name-Last: Benkwitz Author-Name: Michael Neumann Author-X-Name-First: Michael Author-X-Name-Last: Neumann Author-Name: Helmut Lutekpohl Author-X-Name-First: Helmut Author-X-Name-Last: Lutekpohl Title: Problems related to confidence intervals for impulse responses of autoregressive processes Abstract: Confidence intervals for impulse responses computed from autoregressive processes are considered. A detailed analysis of the methods in current use shows that they are not very reliable in some cases. In particular, there are theoretical reasons for them to have actual coverage probabilities which deviate considerably from the nominal level in some situations of practical importance. For a simple case alternative bootstrap methods are proposed which provide correct results asymptotically. Journal: Econometric Reviews Pages: 69-103 Issue: 1 Volume: 19 Year: 2000 Keywords: impulse response, bootstrap, autoregressive process, asymptotic inference, nonparametric inference, X-DOI: 10.1080/07474930008800460 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930008800460 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:19:y:2000:i:1:p:69-103 Template-Type: ReDIF-Article 1.0 Author-Name: Denzil Fiebig Author-X-Name-First: Denzil Author-X-Name-Last: Fiebig Author-Name: Jae Kim Author-X-Name-First: Jae Author-X-Name-Last: Kim Title: Estimation and inference in sur models when the number of equations is large Abstract: There is a tendency for the true variability of feasible GLS estimators to be understated by asymptotic standard errors. For estimation of SUR models, this tendency becomes more severe in large equation systems when estimation of the error covariance matrix, C, becomes problematic. We explore a number of potential solutions involving the use of improved estimators for the disturbance covariance matrix and bootstrapping. In particular, Ullah and Racine (1992) have recently introduced a new class of estimators for SUR models that use nonparametric kernel density estimation techniques. The proposed estimators have the same structure as the feasible GLS estimator of Zellner (1962) differing only in the choice of estimator for C. Ullah and Racine (1992) prove that their nonparametric density estimator of C can be expressed as Zellner's original estimator plus a positive definite matrix that depends on the smoothing parameter chosen for the density estimation. It is this structure of the estimator that most interests us as it has the potential to be especially useful in large equation systems. Atkinson and Wilson (1992) investigated the bias in the conventional and bootstrap estimators of coefficient standard errors in SUR models. They demonstrated that under certain conditions the former were superior, but they caution that neither estimator uniformly dominated and hence bootstrapping provides little improvement in the estimation of standard errors for the regression coefficients. Rilstone and Veal1 (1996) argue that an important qualification needs to be made to this somewhat negative conclusion. They demonstrated that bootstrapping can result in improvements in inferences if the procedures are applied to the t-ratios rather than to the standard errors. These issues are explored for the case of large equation systems and when bootstrapping is combined with improved covariance estimation. Journal: Econometric Reviews Pages: 105-130 Issue: 1 Volume: 19 Year: 2000 Keywords: seemingly unrelated regression models, improved covariance estimation, bootstrapping, large equation systems, X-DOI: 10.1080/07474930008800461 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930008800461 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:19:y:2000:i:1:p:105-130 Template-Type: ReDIF-Article 1.0 Author-Name: Jorgen Grofi Author-X-Name-First: Jorgen Author-X-Name-Last: Grofi Author-Name: Simo Puntanen Author-X-Name-First: Simo Author-X-Name-Last: Puntanen Title: Remark on pseudo-generalized least squares Abstract: We briefly discuss the so called pseudo-GLS estimator in a standard linear regression model with nonsperical disturbances, and conclude that the potentiality for applications is higher than originally assumed by Fiebig Bartels and Kramer (1996). Journal: Econometric Reviews Pages: 139-144 Issue: 1 Volume: 19 Year: 2000 Keywords: C13, C20, X-DOI: 10.1080/07474930008800462 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930008800462 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:19:y:2000:i:1:p:139-144 Template-Type: ReDIF-Article 1.0 Author-Name: James Hamilton Author-X-Name-First: James Author-X-Name-Last: Hamilton Title: Book review Abstract: State-Space Models with Regime Switching by Chang-Jin Kim and Charles R. Nelson. Pp. 250. Cambridge, Massachnsetts: MIT Press, 1999. ($40.00 cloth) WEB INFOR~UATION: http://mitpress.mit.edu/book-home.tcl?isbn=0262l123. Journal: Econometric Reviews Pages: 135-137 Issue: 1 Volume: 19 Year: 2000 X-DOI: 10.1080/07474930008800463 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930008800463 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:19:y:2000:i:1:p:135-137 Template-Type: ReDIF-Article 1.0 Author-Name: Oliver Linton Author-X-Name-First: Oliver Author-X-Name-Last: Linton Author-Name: Douglas Steigerwald Author-X-Name-First: Douglas Author-X-Name-Last: Steigerwald Title: Adaptive testing in arch models Abstract: Specification tests for conditional heteroskedasticity that are derived under the assumption that the density of the innovation is Gaussian may not be powerful in light of the recent empirical results that the density is not Gaussian. We obtain specification tests for conditional heteroskedasticity under the assumption that the innovation density is a member of a general family of densities. Our test statistics maximize asymptotic local power and weighted average power criteria for the general family of densities. We establish both first-order and second-order theory for our procedures. Simulations indicate that asymptotic power gains are achievable in finite samples. Journal: Econometric Reviews Pages: 145-174 Issue: 2 Volume: 19 Year: 2000 Keywords: adaptive testing, ARCH, conditional heteroskedasticity;, semiparametric, X-DOI: 10.1080/07474930008800466 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930008800466 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:19:y:2000:i:2:p:145-174 Template-Type: ReDIF-Article 1.0 Author-Name: Douglas Hodgson Author-X-Name-First: Douglas Author-X-Name-Last: Hodgson Title: Unconditional pseudo-maximum likelihood and adaptive estimation in the presence of conditional heterogeneity of unknown form Abstract: We consider parametric non-linear regression models with additive innovations which are serially uncorrelated but not necessarily independent, and consider the consequences of maximum likelihood and related one-step iterative estimation when the innovations are treated as being iid from their unconditional density. We find that the estimators' asymptotic covariance matrices will generally differ from those that would obtain if the errors actually were iid, except for the special case of strictly exogenous regressors. One important application of these results is to analysis of the properties of adaptive estimators, which employ nonparametric kernel estimates of the unconditional density of the disturbances in the construction of one-step iterative estimators. In the presence of strictly exogenous regressors, adaptive estimators are found to be asymptotically equivalent to the one-step iterative estimators that use the correct unconditional density. We illustrate our results through a brief Monte Carlo study. Journal: Econometric Reviews Pages: 175-206 Issue: 2 Volume: 19 Year: 2000 X-DOI: 10.1080/07474930008800467 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930008800467 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:19:y:2000:i:2:p:175-206 Template-Type: ReDIF-Article 1.0 Author-Name: Eiji Kurozumi Author-X-Name-First: Eiji Author-X-Name-Last: Kurozumi Author-Name: Taku Yamamoto Author-X-Name-First: Taku Author-X-Name-Last: Yamamoto Title: Modified lag augmented vector autoregressions Abstract: This paper proposes an inference procedure for a possibly integrated vector autoregression (VAR) model. We modify the lag augmented VAR (LA-VAR) estimator to exclude the quasiasymptotic bias, which is associated with the term Op(T-1), using the jackknife method. The new estimator has an asymptotic normal distribution and then the Wald statistic to test for the parameter restrictions has an asymptotic chi-square distribut,ion. We investigate the finite sample properties of this approach by comparing with the LA-VAR approach. We find t,hat our modified LA-VAR (MLA-VAR) approach excels the LA-VAR approach in view of an accuracy of the empirical size and the robustness to the tnisspecification of the lag length. The MLA-VAR approach may be used when the researchers place importance on an accuracy of the size, and also be used to complement other testing procedures that may suffer from serious size distortion. Journal: Econometric Reviews Pages: 207-231 Issue: 2 Volume: 19 Year: 2000 Keywords: Vector autoregressions, Integration, Cointegration, Bias correction, Hypothesis testing, X-DOI: 10.1080/07474930008800468 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930008800468 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:19:y:2000:i:2:p:207-231 Template-Type: ReDIF-Article 1.0 Author-Name: Kenneth Stewart Author-X-Name-First: Kenneth Author-X-Name-Last: Stewart Author-Name: Kenneth Stewart Author-X-Name-First: Kenneth Author-X-Name-Last: Stewart Title: GNR, MGR, and exact misspeclfication testing Abstract: The Gauss-Newton regression (GNR) is widely used to compute Lagrange multiplier statistics. A regression described by Milliken and Graybill yields an exact F test in a certain class of nonlinear models which are linear under the null. This paper shows that the Milliken-Graybill regression is a GNR. Hence one interpretation of Milliken-Graybill is that they identified a class of nonlinear models for which the GNR yields an exact test. Journal: Econometric Reviews Pages: 233-240 Issue: 2 Volume: 19 Year: 2000 X-DOI: 10.1080/07474930008800469 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930008800469 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:19:y:2000:i:2:p:233-240 Template-Type: ReDIF-Article 1.0 Author-Name: L. G. Godfrey Author-X-Name-First: L. G. Author-X-Name-Last: Godfrey Author-Name: M. R. Veal Author-X-Name-First: M. R. Author-X-Name-Last: Veal Title: Alternative approaches to testing by variable addition Abstract: Journal: Econometric Reviews Pages: 241-261 Issue: 2 Volume: 19 Year: 2000 Keywords: specification errors, model specification, variable addition tests, bootstrap critical values, X-DOI: 10.1080/07474930008800470 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930008800470 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:19:y:2000:i:2:p:241-261 Template-Type: ReDIF-Article 1.0 Author-Name: Esfandiar Maasoumi Author-X-Name-First: Esfandiar Author-X-Name-Last: Maasoumi Author-Name: Almas Heshmati Author-X-Name-First: Almas Author-X-Name-Last: Heshmati Title: Introduction Abstract: Journal: Econometric Reviews Pages: 5-5 Issue: 3 Volume: 19 Year: 2000 X-DOI: 10.1080/07474930008800472 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930008800472 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:19:y:2000:i:3:p:5-5 Template-Type: ReDIF-Article 1.0 Author-Name: Peter Phillips Author-X-Name-First: Peter Author-X-Name-Last: Phillips Author-Name: Hyungsik Moon Author-X-Name-First: Hyungsik Author-X-Name-Last: Moon Title: Nonstationary panel data analysis: an overview of some recent developments Abstract: This paper overviews some recent developments in panel data asymptotics, concentrating on the nonstationary panel case and gives a new result for models with individual effects. Underlying recent theory are asymptotics for multi-indexed processes in which both indexes may pass to infinity. We review some of the new limit theory that has been developed, show how it can be applied and give a new interpretation of individual effects in nonstationary panel data. Fundamental to the interpretation of much of the asymptotics is the concept of a panel regression coefficient which measures the long run average relation across a section of the panel. This concept is analogous to the statistical interpretation of the coefficient in a classical regression relation. A variety of nonstationary panel data models are discussed and the paper reviews the asymptotic properties of estimators in these various models. Some recent developments in panel unit root tests and stationary dynamic panel regression models are also reviewed. Journal: Econometric Reviews Pages: 263-286 Issue: 3 Volume: 19 Year: 2000 X-DOI: 10.1080/07474930008800473 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930008800473 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:19:y:2000:i:3:p:263-286 Template-Type: ReDIF-Article 1.0 Author-Name: Esfandiar Maasoumi Author-X-Name-First: Esfandiar Author-X-Name-Last: Maasoumi Author-Name: Almas Heshmati Author-X-Name-First: Almas Author-X-Name-Last: Heshmati Title: Stochastic dominance amongst swedish income distributions Abstract: :Sweden's income distribution for the whole population and for subgroups, including its immigants, has been extensively studied. The interest in this area has grown with increasing availability of data, including panels. The previous studies are based on indices of inequality or mobility. While indices are useful for complete ordering and have an air of "decisiveness" about them, they lack universal acceptance of the value judgements inherent to the welfare functions that underlay any index. In contrast, uniformpartial order relations are studied in this paper which rank welfare situations over very wide classes of welfare functions. We conduct bootstrap tests for the existence of first and second order stochastic dominance amongst Sweden's income distributions over time and for several subgroups of immigrants. Analysis of immigrant's income is motivated by the fact that the development of income for immigrants has been different and strongly affected by their length of residence and countries of origin. We consider several non-consecutive waves of a panel of incomes in Sweden. Two income definitions are developed. One is pre-transfers and taxes, gross income, the other is a post-transfers and taxes, disposable income. The comparison of the distribution of these two variables affords a partial view of Sweden's welfare system. We have focused on the incomes of Swede's and immigrant groups of single individuals identified by country of origin, length of residence, age, education, gender, marital status and other relevant characteristics. We find that first order dominance is rare, but second order relations hold in several cases, especially amongst disposable income distributions. Sweden's incomes and welfare policies favor the elderly, females, larger families, and longer periods of residency. We find, in general, the higher the educational credentials, the higher is the burden of this equalization policy. Journal: Econometric Reviews Pages: 287-320 Issue: 3 Volume: 19 Year: 2000 X-DOI: 10.1080/07474930008800474 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930008800474 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:19:y:2000:i:3:p:287-320 Template-Type: ReDIF-Article 1.0 Author-Name: Richard Blundell Author-X-Name-First: Richard Author-X-Name-Last: Blundell Author-Name: Stephen Bond Author-X-Name-First: Stephen Author-X-Name-Last: Bond Title: GMM Estimation with persistent panel data: an application to production functions Abstract: This paper considers the estimation of Cobb-Douglas production functions using panel data covering a large sample of companies observed for a small number of time periods. GMM estimatorshave been found to produce large finite-sample biases when using the standard first-differenced estimator. These biases can be dramatically reduced by exploiting reasonable stationarity restrictions on the initial conditions process. Using data for a panel of R&Dperforming US manufacturing companies we find that the additional instruments used in our extended GMM estimator yield much more reasonable parameter estimates. Journal: Econometric Reviews Pages: 321-340 Issue: 3 Volume: 19 Year: 2000 Keywords: panel data, GMM, production functions, X-DOI: 10.1080/07474930008800475 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930008800475 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:19:y:2000:i:3:p:321-340 Template-Type: ReDIF-Article 1.0 Author-Name: Bo Honore Author-X-Name-First: Bo Author-X-Name-Last: Honore Author-Name: Ekaterini Kyriazidou Author-X-Name-First: Ekaterini Author-X-Name-Last: Kyriazidou Author-Name: J. L. Powell Author-X-Name-First: J. L. Author-X-Name-Last: Powell Title: Estimation of tobit-type models with individual specific effects Abstract: The aim of this paper is two-fold. First, we review recent estimators for censored regression and sample selection panel data models with unobservable individual specific effects, and show how the idea behind these estimators can be used to construct estimators for a variety of other Tobit-type models. The estimators presented in this paper are semiparametric, in the sense that they do not require the parametrization of the distribution of the unobservables. The second aim of the paper is to introduce a new class of estimators for the censored regression model. The advantage of the new estimators is that they can be applied under a stationarity assumption on the transitory error terms, which is weaker than the exchangeability assumption that is usually made in this literature. A similar generalization does not seem feasible for the estimators of the other models that are considered. Journal: Econometric Reviews Pages: 341-366 Issue: 3 Volume: 19 Year: 2000 X-DOI: 10.1080/07474930008800476 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930008800476 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:19:y:2000:i:3:p:341-366 Template-Type: ReDIF-Article 1.0 Author-Name: Ragner Tveterås Author-X-Name-First: Ragner Author-X-Name-Last: Tveterås Author-Name: G. H. Wan Author-X-Name-First: G. H. Author-X-Name-Last: Wan Title: Flexible panel data models for risky production technologies with an application to salmon aquaculture Abstract: Primal panel data models of production risk are estimated, using more flexible specifications than has previously been the practice. Production risk has important implications for the analysis of technology adoption and technical efficiency, since risk averse producers will take into account both the mean and variance of output when ranking alternative technologies. Hence, one should estimate technical change separately for the deterministic part and the risk part of thetechnology. Journal: Econometric Reviews Pages: 367-389 Issue: 3 Volume: 19 Year: 2000 Keywords: production risk, technical change, stochastic dominance, salmon aquaculture, X-DOI: 10.1080/07474930008800477 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930008800477 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:19:y:2000:i:3:p:367-389 Template-Type: ReDIF-Article 1.0 Author-Name: Esfandiar Maasoumi Author-X-Name-First: Esfandiar Author-X-Name-Last: Maasoumi Author-Name: Almas Heshmati Author-X-Name-First: Almas Author-X-Name-Last: Heshmati Title: Introduction Abstract: Journal: Econometric Reviews Pages: 5-5 Issue: 4 Volume: 19 Year: 2000 X-DOI: 10.1080/07474930008800479 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930008800479 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:19:y:2000:i:4:p:5-5 Template-Type: ReDIF-Article 1.0 Author-Name: Erik Biørn Author-X-Name-First: Erik Author-X-Name-Last: Biørn Title: Panel Data With Measurement Errors: Instrumental Variables And Gmm Procedures Combining Levels And Differences Abstract: Journal: Econometric Reviews Pages: 391-424 Issue: 4 Volume: 19 Year: 2000 Keywords: Panel Data, Errors-in-Variables, Repeated Measurement, Moment Conditions, GMM Estimation, Returns to scale, X-DOI: 10.1080/07474930008800480 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930008800480 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:19:y:2000:i:4:p:391-424 Template-Type: ReDIF-Article 1.0 Author-Name: Subal Kumbhakar Author-X-Name-First: Subal Author-X-Name-Last: Kumbhakar Author-Name: M. Denny Author-X-Name-First: M. Author-X-Name-Last: Denny Author-Name: M. Fuss Author-X-Name-First: M. Author-X-Name-Last: Fuss Title: Estimation and decomposition of productivity change when production is not efficient: a paneldata approach Abstract: This paper addresses estimation and decomposition of productivity change, which is mostly identified as technical change under constant (unitary) returns to scale (CRS). If the CRS assumption is not made, productivity change is decomposed into technical change and scale effects.Furthermore, if inefficiency exists, it also contributes to productivity change. Here we decompose productivity change into efficiency change, technical change, and scale effects. Three alternative approaches using parametric production, cost, and profit functions, which differ in terms of behavioral assumptions on the producers and data requirements, are considered. Journal: Econometric Reviews Pages: 312-320 Issue: 4 Volume: 19 Year: 2000 Keywords: total factor productivity, technical change, returns to scale, scale effects, technical inefficiency, allocative inefficiency, production function, cost function, profit function, X-DOI: 10.1080/07474930008800481 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930008800481 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:19:y:2000:i:4:p:312-320 Template-Type: ReDIF-Article 1.0 Author-Name: Seung Ahn Author-X-Name-First: Seung Author-X-Name-Last: Ahn Author-Name: Robin Sickles Author-X-Name-First: Robin Author-X-Name-Last: Sickles Title: Estimation of long-run inefficiency levels: a dynamic frontier approach Abstract: Cornwell, Schmidt, and Sickles (1990) and Kumbhakar (1990), among others, developed stochasticfrontier production models which allow firm specific inefficiency levels to change over time. These studies assumed arbitrary restrictions on the short-run dynamics of efficiency levels which have little theoretical justification. Further, the models are inappropriate for estimation of long-run efficiencies. We consider estimation of an alternative frontier model in which firmspecific technical inefficiency levels are autoregressive. This model is particularly useful to examine a potential dynamic link between technical innovations and production inefficiency levels. We apply our methodology to a panel of US airlines. Journal: Econometric Reviews Pages: 461-492 Issue: 4 Volume: 19 Year: 2000 Keywords: panel data, long-run inefficiency, frontier production function, generalized method of moments, X-DOI: 10.1080/07474930008800482 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930008800482 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:19:y:2000:i:4:p:461-492 Template-Type: ReDIF-Article 1.0 Author-Name: Subal Kumbhakar Author-X-Name-First: Subal Author-X-Name-Last: Kumbhakar Author-Name: Shinichiro Nakamura Author-X-Name-First: Shinichiro Author-X-Name-Last: Nakamura Author-Name: Almas Heshmati Author-X-Name-First: Almas Author-X-Name-Last: Heshmati Title: Estimation of firm-specific technological bias, technical change and total factor productivity growth: a dual approach Abstract: This paper deals with modeling firm-specific technical change (TC), and technological biases (inputs and scale) in estimating total factor productivity (TFP) growth. Several dual parametric econometric models are used for this purpose. We examine robustness of TFP growth and TC among competing models. These models include the traditional time trend (TT) model and the general index (GI) model. The TT and the GI models are generalized to accommodate firm-specific TC and technological bias (in inputs and output). Both nested and non-nested tests are used to select the appropriate models. Firm-level panel data from the Japanese chemical industry during 1968- 1987 is used as an application. Journal: Econometric Reviews Pages: 162-173 Issue: 4 Volume: 19 Year: 2000 Keywords: returns to scale, time trend, general index, cost function, X-DOI: 10.1080/07474930008800483 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930008800483 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:19:y:2000:i:4:p:162-173 Template-Type: ReDIF-Article 1.0 Author-Name: Gordon Anderson Author-X-Name-First: Gordon Author-X-Name-Last: Anderson Title: THE POWER AND SIZE OF NONPARAMETRIC TESTS FOR COMMON DISTRIBUTIONAL CHARACTERISTICS Abstract: This paper considers the power and size properties of some well known nonparametric linear rank tests for location and scale as well as the Kolmogorov-Smirnov omnibus test and proposed alternatives to it. Independence between some classes of linear rank tests is established facilitating their joint application. Monte Carlo study confirms the asymptotic power properties of the linear rank tests but raises concerns about their application in more general and practically relevant circumstances. It also indicates that the new omnibus tests constitute viable alternatives with superior properties to the Kolmogorov-Smirnov test in certain circumstances. Journal: Econometric Reviews Pages: 1-30 Issue: 1 Volume: 20 Year: 2001 Keywords: Two sample linear rank tests, Omnibus tests, JEL Classification: C12, C14, X-DOI: 10.1081/ETC-100104077 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-100104077 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:20:y:2001:i:1:p:1-30 Template-Type: ReDIF-Article 1.0 Author-Name: Badi Baltagi Author-X-Name-First: Badi Author-X-Name-Last: Baltagi Author-Name: Dong Li Author-X-Name-First: Dong Author-X-Name-Last: Li Title: DOUBLE LENGTH ARTIFICIAL REGRESSIONS FOR TESTING SPATIAL DEPENDENCE Abstract: This paper derives two simple artificial Double Length Regressions (DLR) to test for spatial dependence. The first DLR tests for spatial lag dependence while the second DLR tests for spatial error dependence. Both artificial regressions utilize only least squares residuals of the restricted model and are therefore easy to compute. These tests are illustrated using two simple examples. In addition, Monte Carlo experiments are performed to study the small sample performance of these tests. As expected, these DLR tests have similar performance to their corresponding LM counterparts. Journal: Econometric Reviews Pages: 31-40 Issue: 1 Volume: 20 Year: 2001 Keywords: Double length regressions, Spatial dependence, Lagrange multiplier, JEL Classification: C12, C21, R15, X-DOI: 10.1081/ETC-100104078 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-100104078 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:20:y:2001:i:1:p:31-40 Template-Type: ReDIF-Article 1.0 Author-Name: Thanasis Stengos Author-X-Name-First: Thanasis Author-X-Name-Last: Stengos Author-Name: Yiguo Sun Author-X-Name-First: Yiguo Author-X-Name-Last: Sun Title: A CONSISTENT MODEL SPECIFICATION TEST FOR A REGRESSION FUNCTION BASED ON NONPARAMETRIC WAVELET ESTIMATION Abstract: In this paper we present a consistent specification test of a parametric regression function against a general nonparametric alternative. The proposed test is based on wavelet estimation and it is shown to have similar rates of convergence to the more commonly used kernel based tests. Monte Carlo simulations show that this test statistic has adequate size and high power and that it compares favorably with its kernel based counterparts in small samples. Journal: Econometric Reviews Pages: 41-60 Issue: 1 Volume: 20 Year: 2001 Keywords: Wavelets, Consistent specification test, Nonparametric regression, JEL Classification: C12, C14, C52, X-DOI: 10.1081/ETC-100104079 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-100104079 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:20:y:2001:i:1:p:41-60 Template-Type: ReDIF-Article 1.0 Author-Name: Nunzio Cappuccio Author-X-Name-First: Nunzio Author-X-Name-Last: Cappuccio Author-Name: Diego Lubian Author-X-Name-First: Diego Author-X-Name-Last: Lubian Title: ESTIMATION AND INFERENCE ON LONG-RUN EQUILIBRIA: A SIMULATION STUDY Abstract: In this paper we study the finite sample properties of some asymptotically equivalent estimators of cointegrating relationships and related test statistics: the Fully Modified Least Squares estimator proposed by Phillips and Hansen (1990), the Dynamic OLS estimator of Saikkonen (1991) and Stock and Watson (1993), the maximum likelihood estimator (reduced rank regression estimator) of Johansen (1988). On the basis of previous Monte Carlo results on this topic, the main objective of our simulation experiments is to study the sensitivity of the finite sample distribution of estimators and test statistics to three features of the DGP of the observable variables, namely, the degree of serial correlation of the cointegrating relationship, the condition of weak exogeneity and the signal-to-noise ratio. To this end, we consider 100 different DGPs and four increasing sample sizes. Besides the usual descriptive statistics, further information about the empirical distributions of interest by means of graphical and statistical methods are provided. In particular, we study size distortion of test statistics using P-value discrepancy plots and estimate the maximal moment exponent of the empirical distribution of estimators. Journal: Econometric Reviews Pages: 61-84 Issue: 1 Volume: 20 Year: 2001 Keywords: Cointegration, Monte Carlo experiment, Recursive variance, P-value discrepancy plots, Maximal moment exponent, JEL Classification: C13, C15, X-DOI: 10.1081/ETC-100104080 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-100104080 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:20:y:2001:i:1:p:61-84 Template-Type: ReDIF-Article 1.0 Author-Name: Paramsothy Silvapulle Author-X-Name-First: Paramsothy Author-X-Name-Last: Silvapulle Title: A SCORE TEST FOR SEASONAL FRACTIONAL INTEGRATION AND COINTEGRATION Abstract: This paper develops a time domain score statistic for testing fractional integration at zero and seasonal frequencies in quarterly time series models. Further, it introduces the notion of fractional cointegration at different frequencies between two seasonally integrated, I(1) series. In testing problems involving seasonal fractional cointegration, it is argued that the alternative hypothesis is one-sided for which the usual score test may not be appropriate. Therefore, based on ideas in Silvapulle and Silvapulle (1995), a one-sided score statistic is constructed. A simulation study finds that the score statistic generally has desirable size and power properties in moderately sized samples. The score test is applied to the quarterly Australian consumption function. The income and consumption series are found to be I(1) at zero and seasonal frequencies and these two series are not cointegrated at any frequency. Journal: Econometric Reviews Pages: 85-104 Issue: 1 Volume: 20 Year: 2001 Keywords: Seasonal fractional roots, Long-memory, Fractional cointegration, One-sided alternatives, JEL Classification: C12, C22 and C32, X-DOI: 10.1081/ETC-100104081 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-100104081 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:20:y:2001:i:1:p:85-104 Template-Type: ReDIF-Article 1.0 Author-Name: Kazumitsu Nawata Author-X-Name-First: Kazumitsu Author-X-Name-Last: Nawata Author-Name: Michael McAleer Author-X-Name-First: Michael Author-X-Name-Last: McAleer Title: SIZE CHARACTERISTICS OF TESTS FOR SAMPLE SELECTION BIAS: A MONTE CARLO COMPARISON AND EMPIRICAL EXAMPLE Abstract: The t-test of an individual coefficient is used widely in models of qualitative choice. However, it is well known that the t-test can yield misleading results when the sample size is small. This paper provides some experimental evidence on the finite sample properties of the t-test in models with sample selection biases, through a comparison of the t-test with the likelihood ratio and Lagrange multiplier tests, which are asymptotically equivalent to the squared t-test. The finite sample problems with the t-test are shown to be alarming, and much more serious than in models such as binary choice models. An empirical example is also presented to highlight the differences in the calculated test statistics. Journal: Econometric Reviews Pages: 105-112 Issue: 1 Volume: 20 Year: 2001 Keywords: Sample selection bias, t-test, Wald test, JEL Classification: C12, C24, X-DOI: 10.1081/ETC-100104082 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-100104082 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:20:y:2001:i:1:p:105-112 Template-Type: ReDIF-Article 1.0 Author-Name: Chunrong Ai Author-X-Name-First: Chunrong Author-X-Name-Last: Ai Title: A MODIFIED AVERAGE DERIVATIVES ESTIMATOR Abstract: We extend the average derivatives estimator to the case of functionally dependent regressors. We show that the proposed estimator is consistent and has a limiting normal distribution. A consistent covariance matrix estimator for the proposed estimator is provided. Journal: Econometric Reviews Pages: 113-131 Issue: 1 Volume: 20 Year: 2001 Keywords: Nonparametric estimation, Functional dependency, Average derivatives estimator, JEL Classification: C2, C4, X-DOI: 10.1081/ETC-100104083 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-100104083 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:20:y:2001:i:1:p:113-131 Template-Type: ReDIF-Article 1.0 Author-Name: J. Denis Sargan Author-X-Name-First: J. Denis Author-X-Name-Last: Sargan Title: MODEL BUILDING AND DATA MINING Abstract: This paper defines the phenomenon of data mining in econometrics and discusses various outcomes of and solutions to data mining. Both classical and Bayesian approaches are considered, each with notable advantages and disadvantages, and with the choice of loss function affecting critical values. Illustrative examples include variable addition and exclusion in a standard linear regression model, the choice of lag structure in a dynamic single equation, and specification in a simultaneous equations model. Journal: Econometric Reviews Pages: 159-170 Issue: 2 Volume: 20 Year: 2001 Keywords: Bayes, Loss function, Pre-test estimation, Specification searches, Stein-James estimator, JEL Classification: C44, C51, X-DOI: 10.1081/ETC-100103820 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-100103820 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:20:y:2001:i:2:p:159-170 Template-Type: ReDIF-Article 1.0 Author-Name: J. Denis Sargan Author-X-Name-First: J. Denis Author-X-Name-Last: Sargan Title: THE CHOICE BETWEEN SETS OF REGRESSORS Abstract: This paper examines the choice of critical values for testing both non-sequential and nested sequential sets of constraints in the standard linear regression model. Modest increases in (e.g.) t-ratio critical values relative to their one-off values are often sufficient to maintain proper size. A Bayesian decision-theoretic approach, highlighted by the Schwarz (1978) criterion, provides a framework for deriving consistency and asymptotic local power properties of both forms of testing (data mining) algorithms. Journal: Econometric Reviews Pages: 171-186 Issue: 2 Volume: 20 Year: 2001 Keywords: Bayes, Bonferroni, Critical values, Data mining, Multiple testing, Scheffe, Schwarz criterion, Specification searches, JEL Classifixcation: C44, C51, X-DOI: 10.1081/ETC-100103821 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-100103821 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:20:y:2001:i:2:p:171-186 Template-Type: ReDIF-Article 1.0 Author-Name: Akira Tokihisa Author-X-Name-First: Akira Author-X-Name-Last: Tokihisa Author-Name: Shigeyuki Hamori Author-X-Name-First: Shigeyuki Author-X-Name-Last: Hamori Title: SEASONAL INTEGRATION FOR DAILY DATA Abstract: This paper has two purposes: it introduces the econometric methods used to analyze time series data with general frequency and presents a framework for analyzing economic variables that are measured daily; this special case is then applied to the trading volume of stock markets. Journal: Econometric Reviews Pages: 187-200 Issue: 2 Volume: 20 Year: 2001 Keywords: Seasonal unit roots, Asymptotic distribution, Stock markets, JEL Classifcation Number: C12, C15, and C22, X-DOI: 10.1081/ETC-100103822 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-100103822 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:20:y:2001:i:2:p:187-200 Template-Type: ReDIF-Article 1.0 Author-Name: Gianluca Cubadda Author-X-Name-First: Gianluca Author-X-Name-Last: Cubadda Title: COMMON FEATURES IN TIME SERIES WITH BOTH DETERMINISTIC AND STOCHASTIC SEASONALITY Abstract: This paper extends the notions of common cycles and common seasonal features to time series having deterministic and stochastic seasonality at different frequencies. The conditions under which quarterly time series with these characteristics have common features are investigated, various representations are presented and statistical inference is discussed. Finally, the analysis is applied to study comovements between different components of consumption and income using UK data. Journal: Econometric Reviews Pages: 201-216 Issue: 2 Volume: 20 Year: 2001 Keywords: Common features, Seasonality, Codependence, JEL Classification: C32, C52, X-DOI: 10.1081/ETC-100103823 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-100103823 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:20:y:2001:i:2:p:201-216 Template-Type: ReDIF-Article 1.0 Author-Name: Gael Martin Author-X-Name-First: Gael Author-X-Name-Last: Martin Title: BAYESIAN ANALYSIS OF A FRACTIONAL COINTEGRATION MODEL Abstract: The concept of fractional cointegration, whereby deviations from an equilibrium relationship follow a fractionally integrated process, has attracted some attention of late. The extended concept allows cointegration to be associated with mean reversion in the error, rather than requiring the more stringent condition of stationarity. This paper presents a Bayesian method for conducting inference about fractional cointegration. The method is based on an approximation of the exact likelihood, with a Jeffreys prior being used to offset identification problems. Numerical results are produced via a combination of Markov chain Monte Carlo algorithms. The procedure is applied to several purchasing power parity relations, with substantial evidence found in favor of parity reversion. Journal: Econometric Reviews Pages: 217-234 Issue: 2 Volume: 20 Year: 2001 Keywords: Fractional cointegration, Bayesian inference, Jeffreys prior, Markov chain Monte Carlo, JEL Classification: C11; C32, X-DOI: 10.1081/ETC-100103824 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-100103824 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:20:y:2001:i:2:p:217-234 Template-Type: ReDIF-Article 1.0 Author-Name: Mahmoud El-Gamal Author-X-Name-First: Mahmoud Author-X-Name-Last: El-Gamal Title: A BAYESIAN INTERPRETATION OF MULTIPLE POINT ESTIMATES Abstract: Consider a large number of econometric investigations using different estimation techniques and/or different subsets of all available data to estimate a fixed set of parameters. The resulting empirical distribution of point estimates can be shown - under suitable conditions - to coincide with a Bayesian posterior measure on the parameter space induced by a minimum information procedure. This Bayesian interpretation makes it easier to combine the results of various empirical exercises for statistical decision making. The collection of estimators may be generated by one investigator to ensure the satisfaction of our conditions, or they may be collected from published works, where behavioral assumptions need to be made regarding the dependence structure of econometric studies. Journal: Econometric Reviews Pages: 235-245 Issue: 2 Volume: 20 Year: 2001 Keywords: Bayesian statistics and econometrics, Decision theory, Literature surveys, Meta-analysis, Markov random fields, Gibbs random fields, Point estimation, JEL Classification: C11, C13, C42, C44, and C51, X-DOI: 10.1081/ETC-100103825 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-100103825 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:20:y:2001:i:2:p:235-245 Template-Type: ReDIF-Article 1.0 Author-Name: Kirstin Hubrich Author-X-Name-First: Kirstin Author-X-Name-Last: Hubrich Author-Name: Helmut Lutkepohl Author-X-Name-First: Helmut Author-X-Name-Last: Lutkepohl Author-Name: Pentti Saikkonen Author-X-Name-First: Pentti Author-X-Name-Last: Saikkonen Title: A REVIEW OF SYSTEMS COINTEGRATION TESTS Abstract: The literature on systems cointegration tests is reviewed and the various sets of assumptions for the asymptotic validity of the tests are compared within a general unifying framework. The comparison includes likelihood ratio tests, Lagrange multiplier and Wald type tests, lag augmentation tests, tests based on canonical correlations, the Stock-Watson tests and Bierens' nonparametric tests. Asymptotic results regarding the power of these tests and previous small sample simulation studies are discussed. Further issues and proposals in the context of systems cointegration tests are also considered briefly. New simulations are presented to compare the tests under uniform conditions. Special emphasis is given to the sensitivity of the test performance with respect to the trending properties of the DGP. Journal: Econometric Reviews Pages: 247-318 Issue: 3 Volume: 20 Year: 2001 Keywords: Systems cointegration tests, LR tests, Nonparametric tests, Asymptotic power, Small sample simulations, X-DOI: 10.1081/ETC-100104936 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-100104936 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:20:y:2001:i:3:p:247-318 Template-Type: ReDIF-Article 1.0 Author-Name: Shigeru Iwata Author-X-Name-First: Shigeru Author-X-Name-Last: Iwata Title: RECENTERED AND RESCALED INSTRUMENTAL VARIABLE ESTIMATION OF TOBIT AND PROBIT MODELS WITH ERRORS IN VARIABLES Abstract: Since Durbin (1954) and Sargan (1958), instrumental variable (IV) method has long been one of the most popular procedures among economists and other social scientists to handle linear models with errors-in-variables. A direct application of this method to nonlinear errors-in-variables models, however, fails to yield consistent estimators. This article restricts attention to Tobit and Probit models and shows that simple recentering and rescaling of the observed dependent variable may restore consistency of the standard IV estimator if the true dependent variable and the IV's are jointly normally distributed. Although the required condition seems rarely to be satisfied by real data, our Monte Carlo experiment suggests that the proposed estimator may be quite robust to the possible deviation from normality. Journal: Econometric Reviews Pages: 319-335 Issue: 3 Volume: 20 Year: 2001 Keywords: Instrumental variables, GMM estimator, Nonlinear errors in variables, Elliptically symmetric distribution, X-DOI: 10.1081/ETC-100104937 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-100104937 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:20:y:2001:i:3:p:319-335 Template-Type: ReDIF-Article 1.0 Author-Name: Evzen Kocenda Author-X-Name-First: Evzen Author-X-Name-Last: Kocenda Title: AN ALTERNATIVE TO THE BDS TEST: INTEGRATION ACROSS THE CORRELATION INTEGRAL Abstract: This paper extends and generalizes the BDS test presented by Brock, Dechert, Scheinkman, and LeBaron (1996). In doing so it aims to remove the limitation of having to arbitrarily select a proximity parameter by integrating across the correlation integral. The Monte Carlo simulation is used to tabulate critical values of the alternative statistic. Previously published empirical studies are replicated as well as power tests executed in order to evaluate the relative performance of the suggested alternative to the BDS test. The results are favorable for the suggested alternative. Journal: Econometric Reviews Pages: 337-351 Issue: 3 Volume: 20 Year: 2001 Keywords: Chaos, Nonlinear dynamics, Correlation integral, Monte Carlo, Exchange rates, X-DOI: 10.1081/ETC-100104938 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-100104938 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:20:y:2001:i:3:p:337-351 Template-Type: ReDIF-Article 1.0 Author-Name: Robert Breunig Author-X-Name-First: Robert Author-X-Name-Last: Breunig Title: DENSITY ESTIMATION FOR CLUSTERED DATA Abstract: The commonly used survey technique of clustering introduces dependence into sample data. Such data is frequently used in economic analysis, though the dependence induced by the sample structure of the data is often ignored. In this paper, the effect of clustering on the non-parametric, kernel estimate of the density, f(x), is examined. The window width commonly used for density estimation for the case of i.i.d. data is shown to no longer be optimal. A new optimal bandwidth using a higher-order kernel is proposed and is shown to give a smaller integrated mean squared error than two window widths which are widely used for the case of i.i.d. data. Several illustrations from simulation are provided. Journal: Econometric Reviews Pages: 353-367 Issue: 3 Volume: 20 Year: 2001 Keywords: Bandwidth choice, Cluster sampling, Dependent data, Kernel density estimation, X-DOI: 10.1081/ETC-100104939 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-100104939 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:20:y:2001:i:3:p:353-367 Template-Type: ReDIF-Article 1.0 Author-Name: Offer Lieberman Author-X-Name-First: Offer Author-X-Name-Last: Lieberman Title: THE EXACT BIAS OF THE LOG-PERIODOGRAM REGRESSION ESTIMATOR Abstract: The paper makes two contributions. First, we provide a formula for the exact distribution of the periodogram evaluated at any arbitrary frequency, when the sample is taken from any zero-mean stationary Gaussian process. The inadequacy of the asymptotic distribution is demonstrated through an example in which the observations are generated by a fractional Gaussian noise process. The results are then applied in deriving the exact bias of the log-periodogram regression estimator (Geweke and Porter-Hudak (1983), Robinson (1995)). The formula is computable. Practical bounds on this bias are developed and their arithmetic mean is shown to be accurate and useful. Journal: Econometric Reviews Pages: 369-383 Issue: 3 Volume: 20 Year: 2001 Keywords: ARFIMA, Chi-square distribution, Log-periodogram regression, X-DOI: 10.1081/ETC-100104940 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-100104940 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:20:y:2001:i:3:p:369-383 Template-Type: ReDIF-Article 1.0 Author-Name: Christian Gourieroux Author-X-Name-First: Christian Author-X-Name-Last: Gourieroux Author-Name: Joann Jasiak Author-X-Name-First: Joann Author-X-Name-Last: Jasiak Title: DYNAMIC FACTOR MODELS Abstract: This paper introduces nonlinear dynamic factor models for various applications related to risk analysis. Traditional factor models represent the dynamics of processes driven by movements of latent variables, called the factors. Our approach extends this setup by introducing factors defined as random dynamic parameters and stochastic autocorrelated simulators. This class of factor models can represent processes with time varying conditional mean, variance, skewness and excess kurtosis. Applications discussed in the paper include dynamic risk analysis, such as risk in price variations (models with stochastic mean and volatility), extreme risks (models with stochastic tails), risk on asset liquidity (stochastic volatility duration models), and moral hazard in insurance analysis. We propose estimation procedures for models with the marginal density of the series and factor dynamics parameterized by distinct subsets of parameters. Such a partitioning of the parameter vector found in many applications allows to simplify considerably statistical inference. We develop a two- stage Maximum Likelihood method, called the Finite Memory Maximum Likelihood, which is easy to implement in the presence of multiple factors. We also discuss simulation based estimation, testing, prediction and filtering. Journal: Econometric Reviews Pages: 385-424 Issue: 4 Volume: 20 Year: 2001 Keywords: Nonlinear dynamics, Factor models, Stochastic volatility, Moral hazard, Stable distributions, JEL Number: C22, C32, G10, G12, X-DOI: 10.1081/ETC-100106997 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-100106997 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:20:y:2001:i:4:p:385-424 Template-Type: ReDIF-Article 1.0 Author-Name: Kurt Brannas Author-X-Name-First: Kurt Author-X-Name-Last: Brannas Author-Name: Jorgen Hellstrom Author-X-Name-First: Jorgen Author-X-Name-Last: Hellstrom Title: GENERALIZED INTEGER-VALUED AUTOREGRESSION Abstract: The integer-valued AR1 model is generalized to encompass some of the more likely features of economic time series of count data. The generalizations come at the price of loosing exact distributional properties. For most specifications the first and second order both conditional and unconditional moments can be obtained. Hence estimation, testing and forecasting are feasible and can be based on least squares or GMM techniques. An illustration based on the number of plants within an industrial sector is considered. Journal: Econometric Reviews Pages: 425-443 Issue: 4 Volume: 20 Year: 2001 Keywords: Characterization, Dependence, Time series model, Estimation, Forecasting, Entry and exit, JEL Classification: C12, C13, C22, C25, C51, X-DOI: 10.1081/ETC-100106998 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-100106998 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:20:y:2001:i:4:p:425-443 Template-Type: ReDIF-Article 1.0 Author-Name: Badi Baltagi Author-X-Name-First: Badi Author-X-Name-Last: Baltagi Author-Name: Qi Li Author-X-Name-First: Qi Author-X-Name-Last: Li Title: ESTIMATION OF ECONOMETRIC MODELS WITH NONPARAMETRICALLY SPECIFIED RISK TERMS Abstract: This paper studies the asymptotic properties of the semiparametric estimator considered by Pagan and Ullah (1988) and Pagan and Hong (1991) for models with risk terms. We show that when the risk term is nonparametrically specified, the estimator with generated regressors suggested by Pagan and Ullah (1988) and Pagan and Hong (1991) is [image omitted]-consistent and has an asymptotic normal distribution. The result is then applied to analyzing risk premium for the U.S. dollar against the British pound, the French franc and the Japanese yen exchange markets for monthly data covering the period 1976:1 to 1992:8. Journal: Econometric Reviews Pages: 445-460 Issue: 4 Volume: 20 Year: 2001 Keywords: Risk premium, Exchange market, Semiparametric estimation, √n-consistency, Asymptotic normality, JEL Classification: C14; C12, X-DOI: 10.1081/ETC-100106999 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-100106999 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:20:y:2001:i:4:p:445-460 Template-Type: ReDIF-Article 1.0 Author-Name: Sung Ahn Author-X-Name-First: Sung Author-X-Name-Last: Ahn Author-Name: Stergios Fotopoulos Author-X-Name-First: Stergios Author-X-Name-Last: Fotopoulos Author-Name: Lijian He Author-X-Name-First: Lijian Author-X-Name-Last: He Title: UNIT ROOT TESTS WITH INFINITE VARIANCE ERRORS Abstract: This paper considers the asymptotic properties of some unit root test statistics with the errors belonging to the domain of attraction of a symmetric α-stable law with 0 < α < 2. The results obtained can be viewed as a parallel extension of the asymptotic results for the finite-variance case. The test statistics considered are the Dickey-Fuller, the Lagrange multiplier, the Durbin-Watson and Phillips-type modified. Their asymptotic distributions are expressed as functionals of a standard symmetric α-stable Levy motion. Percentiles of these test statistics are obtained by computer simulation. Asymptotic distributions of sample moments that are part of the test statistics are found to have explicit densities. A small Monte Carlo simulation study is performed to assess small-sample performance of these test statistics for heavy-tailed errors. Journal: Econometric Reviews Pages: 461-483 Issue: 4 Volume: 20 Year: 2001 Keywords: Stable distributions, Invariance principles, Partial sum processes, X-DOI: 10.1081/ETC-100107000 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-100107000 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:20:y:2001:i:4:p:461-483 Template-Type: ReDIF-Article 1.0 Author-Name: David Mandy Author-X-Name-First: David Author-X-Name-Last: Mandy Author-Name: Carlos Martins-Filho Author-X-Name-First: Carlos Author-X-Name-Last: Martins-Filho Title: OPTIMAL IV ESTIMATION OF SYSTEMS WITH STOCHASTIC REGRESSORS AND VAR DISTURBANCES WITH APPLICATIONS TO DYNAMIC SYSTEMS Abstract: This paper considers the general problem of Feasible Generalized Least Squares Instrumental Variables (FGLS IV) estimation using optimal instruments. First we summarize the sufficient conditions for the FGLS IV estimator to be asymptotically equivalent to an optimal GLS IV estimator. Then we specialize to stationary dynamic systems with stationary VAR errors, and use the sufficient conditions to derive new moment conditions for these models. These moment conditions produce useful IVs from the lagged endogenous variables, despite the correlation between errors and endogenous variables. This use of the information contained in the lagged endogenous variables expands the class of IV estimators under consideration and thereby potentially improves both asymptotic and small-sample efficiency of the optimal IV estimator in the class. Some Monte Carlo experiments compare the new methods with those of Hatanaka (1976). For the DGP used in the Monte Carlo experiments, asymptotic efficiency is strictly improved by the new IVs, and experimental small-sample efficiency is improved as well. Journal: Econometric Reviews Pages: 485-505 Issue: 4 Volume: 20 Year: 2001 Keywords: Dynamic models, IV estimation, VAR errors, JEL Classification: C30, X-DOI: 10.1081/ETC-100107001 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-100107001 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:20:y:2001:i:4:p:485-505 Template-Type: ReDIF-Article 1.0 Author-Name: Dick van Dijk Author-X-Name-First: Dick Author-X-Name-Last: van Dijk Author-Name: Timo Terasvirta Author-X-Name-First: Timo Author-X-Name-Last: Terasvirta Author-Name: Philip Hans Franses Author-X-Name-First: Philip Hans Author-X-Name-Last: Franses Title: SMOOTH TRANSITION AUTOREGRESSIVE MODELS — A SURVEY OF RECENT DEVELOPMENTS Abstract: This paper surveys recent developments related to the smooth transition autoregressive (STAR) time series model and several of its variants. We put emphasis on new methods for testing for STAR nonlinearity, model evaluation, and forecasting. Several useful extensions of the basic STAR model, which concern multiple regimes, time-varying non-linear properties, and models for vector time series, are also reviewed. Journal: Econometric Reviews Pages: 1-47 Issue: 1 Volume: 21 Year: 2002 Keywords: Regime-switching models, Time series model specification, Model evaluation, Forecasting, Impulse response analysis, JEL Classification: C22, C52, E24, X-DOI: 10.1081/ETC-120008723 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-120008723 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:21:y:2002:i:1:p:1-47 Template-Type: ReDIF-Article 1.0 Author-Name: M. Hashem Pesaran Author-X-Name-First: M. Hashem Author-X-Name-Last: Pesaran Author-Name: Yongcheol Shin Author-X-Name-First: Yongcheol Author-X-Name-Last: Shin Title: LONG-RUN STRUCTURAL MODELLING Abstract: The paper develops a general framework for identification, estimation, and hypothesis testing in cointegrated systems when the cointegrating coefficients are subject to (possibly) non-linear and cross-equation restrictions, obtained from economic theory or other relevant a priori information. It provides a proof of the consistency of the quasi maximum likelihood estimators (QMLE), establishes the relative rates of convergence of the QMLE of the short-run and the long-run parameters, and derives their asymptotic distributions; thus generalizing the results already available in the literature for the linear case. The paper also develops tests of the over-identifying (possibly) non-linear restrictions on the cointegrating vectors. The estimation and hypothesis testing procedures are applied to an Almost Ideal Demand System estimated on U.K. quarterly observations. Unlike many other studies of consumer demand this application does not treat relative prices and real per capita expenditures as exogenously given. Journal: Econometric Reviews Pages: 49-87 Issue: 1 Volume: 21 Year: 2002 Keywords: Cointegration, Identification, QMLE, Consistency, Asymptotic distribution, testing non-linear restrictions, Almost Ideal Demand Systems, JEL Classifications: C1, C3, D1, E1, X-DOI: 10.1081/ETC-120008724 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-120008724 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:21:y:2002:i:1:p:49-87 Template-Type: ReDIF-Article 1.0 Author-Name: Mukhtar Ali Author-X-Name-First: Mukhtar Author-X-Name-Last: Ali Title: DISTRIBUTION OF THE LEAST SQUARES ESTIMATOR IN A FIRST-ORDER AUTOREGRESSIVE MODEL Abstract: This paper investigates the finite sample distribution of the least squares estimator of the autoregressive parameter in a first-order autoregressive model. A uniform asymptotic expansion for the distribution applicable to both stationary and nonstationary cases is obtained. Accuracy of the approximation to the distribution by a first few terms of this expansion is then investigated. It is found that the leading term of this expansion approximates well the distribution. The approximation is, in almost all cases, accurate to the second decimal place throughout the distribution. In the literature, there exist a number of approximations to this distribution which are specifically designed to apply in some special cases of this model. The present approximation compares favorably with those approximations and in fact, its accuracy is, with almost no exception, as good as or better than these other approximations. Convenience of numerical computations seems also to favor the present approximations over the others. An application of the finding is illustrated with examples. Journal: Econometric Reviews Pages: 89-119 Issue: 1 Volume: 21 Year: 2002 Keywords: Unit root, Saddlepoint approximation, Asymptotic expansion, JEL Classification: C13, C22, X-DOI: 10.1081/ETC-120008725 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-120008725 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:21:y:2002:i:1:p:89-119 Template-Type: ReDIF-Article 1.0 Author-Name: Kazuhiro Ohtani Author-X-Name-First: Kazuhiro Author-X-Name-Last: Ohtani Author-Name: Alan Wan Author-X-Name-First: Alan Author-X-Name-Last: Wan Title: ON THE USE OF THE STEIN VARIANCE ESTIMATOR IN THE DOUBLE k-CLASS ESTIMATOR IN REGRESSION Abstract: This paper investigates the predictive mean squared error performance of a modified double k-class estimator by incorporating the Stein variance estimator. Recent studies show that the performance of the Stein rule estimator can be improved by using the Stein variance estimator. However, as we demonstrate below, this conclusion does not hold in general for all members of the double k-class estimators. On the other hand, an estimator is found to have smaller predictive mean squared error than the Stein variance-Stein rule estimator, over quite large parts of the parameter space. Journal: Econometric Reviews Pages: 121-134 Issue: 1 Volume: 21 Year: 2002 Keywords: Ad-hoc, Double k-class, Predictive mean squared error, Pre-test, Stein rule, JEL Classification: primary C13; secondary C20, X-DOI: 10.1081/ETC-120008726 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-120008726 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:21:y:2002:i:1:p:121-134 Template-Type: ReDIF-Article 1.0 Author-Name: Gerd Ronning Author-X-Name-First: Gerd Author-X-Name-Last: Ronning Title: ESTIMATION OF DISCRETE CHOICE MODELS WITH MINIMAL VARIATION OF ALTERNATIVE-SPECIFIC VARIABLES Abstract: The paper states conditions for minimal variation within the explanatory variables such that the maximum likelihood estimate of the coefficient vector in the discrete choice logit model is unique. Special emphasis is given to the case that (almost) all individuals observe the same set of alternative-specific explanatory variables. The aspect of 'experimental design' in discrete choice models is discussed. Journal: Econometric Reviews Pages: 135-146 Issue: 1 Volume: 21 Year: 2002 Keywords: Experimental design, Maximum likelihood, Multinomial logit, JEL Classification: C13, C25, X-DOI: 10.1081/ETC-120008727 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-120008727 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:21:y:2002:i:1:p:135-146 Template-Type: ReDIF-Article 1.0 Author-Name: Zeng-Hua Lu Author-X-Name-First: Zeng-Hua Author-X-Name-Last: Lu Author-Name: Maxwell King Author-X-Name-First: Maxwell Author-X-Name-Last: King Title: IMPROVING THE NUMERICAL TECHNIQUE FOR COMPUTING THE ACCUMULATED DISTRIBUTION OF A QUADRATIC FORM IN NORMAL VARIABLES Abstract: This paper is concerned with the technique of numerically evaluating the cumulative distribution function of a quadratic form in normal variables. The efficiency of two new truncation bounds and all existing truncation bounds are investigated. We also find that the suggestion in the literature for further splitting truncation errors might reduce computational efficiency, and the optimum splitting rate could be different in different situations. A practical solution is provided. The paper also discusses a modified secant algorithm for finding the critical value of the distribution at any given significance level. Journal: Econometric Reviews Pages: 149-165 Issue: 2 Volume: 21 Year: 2002 Keywords: Quadratic form in normal variables, Numerical inversion of characteristic function, Truncation error, Newton', s method, Secant method, JEL Classification, C19, C63, X-DOI: 10.1081/ETC-120014346 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-120014346 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:21:y:2002:i:2:p:149-165 Template-Type: ReDIF-Article 1.0 Author-Name: Badi Baltagi Author-X-Name-First: Badi Author-X-Name-Last: Baltagi Author-Name: Seuck Heun Song Author-X-Name-First: Seuck Heun Author-X-Name-Last: Song Author-Name: Byoung Cheol Jung Author-X-Name-First: Byoung Cheol Author-X-Name-Last: Jung Title: SIMPLE LM TESTS FOR THE UNBALANCED NESTED ERROR COMPONENT REGRESSION MODEL Abstract: This paper derives several Lagrange Multiplier tests for the unbalanced nested error component model. Economic data with a natural nested grouping include firms grouped by industry; or students grouped by schools. The LM tests derived include the joint test for both effects as well as the test for one effect conditional on the presence of the other. The paper also derives the standardized versions of these tests, their asymptotic locally mean most powerful version as well as their robust to local misspecification version. Monte Carlo experiments are conducted to study the performance of these LM tests. Journal: Econometric Reviews Pages: 167-187 Issue: 2 Volume: 21 Year: 2002 Keywords: Panel data, Nested error component, Unbalanced data, LM tests, X-DOI: 10.1081/ETC-120014347 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-120014347 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:21:y:2002:i:2:p:167-187 Template-Type: ReDIF-Article 1.0 Author-Name: Nilanjana Roy Author-X-Name-First: Nilanjana Author-X-Name-Last: Roy Title: IS ADAPTIVE ESTIMATION USEFUL FOR PANEL MODELS WITH HETEROSKEDASTICITY IN THE INDIVIDUAL SPECIFIC ERROR COMPONENT? SOME MONTE CARLO EVIDENCE Abstract: This paper first derives an adaptive estimator when heteroskedasticity is present in the individual specific error in an error component model and then compares the finite sample performance of the proposed estimator with various other estimators. While the Monte Carlo results show that the proposed estimator performs adequately in terms of relative efficiency, its performance on the basis of empirical size is quite similar to the other estimators considered. Journal: Econometric Reviews Pages: 189-203 Issue: 2 Volume: 21 Year: 2002 Keywords: Heteroskedasticity, Kernel estimation, Error component model, JEL Classification, C14, C23, X-DOI: 10.1081/ETC-120014348 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-120014348 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:21:y:2002:i:2:p:189-203 Template-Type: ReDIF-Article 1.0 Author-Name: John Galbraith Author-X-Name-First: John Author-X-Name-Last: Galbraith Author-Name: Aman Ullah Author-X-Name-First: Aman Author-X-Name-Last: Ullah Author-Name: Victoria Zinde-Walsh Author-X-Name-First: Victoria Author-X-Name-Last: Zinde-Walsh Title: ESTIMATION OF THE VECTOR MOVING AVERAGE MODEL BY VECTOR AUTOREGRESSION Abstract: We examine a simple estimator for the multivariate moving average model based on vector autoregressive approximation. In finite samples the estimator has a bias which is low where roots of the characteristic equation are well away from the unit circle, and more substantial where one or more roots have modulus near unity. We show that the representation estimated by this multivariate technique is consistent and asymptotically invertible. This estimator has significant computational advantages over Maximum Likelihood, and more importantly may be more robust than ML to mis-specification of the vector moving average model. The estimation method is applied to a VMA model of wholesale and retail inventories, using Canadian data on inventory investment, and allows us to examine the propagation of shocks between the two classes of inventory. Journal: Econometric Reviews Pages: 205-219 Issue: 2 Volume: 21 Year: 2002 Keywords: Vector autoregression, Vector moving average, JEL Classification:, C12, C22, X-DOI: 10.1081/ETC-120014349 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-120014349 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:21:y:2002:i:2:p:205-219 Template-Type: ReDIF-Article 1.0 Author-Name: Denise Osborn Author-X-Name-First: Denise Author-X-Name-Last: Osborn Author-Name: Paulo Rodrigues Author-X-Name-First: Paulo Author-X-Name-Last: Rodrigues Title: ASYMPTOTIC DISTRIBUTIONS OF SEASONAL UNIT ROOT TESTS: A UNIFYING APPROACH Abstract: This paper adopts a unified approach to the derivation of the asymptotic distributions of various seasonal unit root tests. The procedures considered are those of Dickey et al. [DHF], Kunst, Hylleberg et al. [HEGY], Osborn et al. [OCSB], Ghysels et al. [GHL] and Franses. This unified approach shows that the asymptotic distributions of all these test statistics are functions of the same vector of Brownian motions. The Kunst test and the overall HEGY F-test are, indeed, equivalent both asymptotically and in finite samples, while the Franses and GHL tests are shown to have equivalent parameterizations. The OCSB and DHF test regressions are viewed as restricted forms of the Kunst-HEGY regressions, and these restrictions may have non-trivial asymptotic implications. Journal: Econometric Reviews Pages: 221-241 Issue: 2 Volume: 21 Year: 2002 Keywords: Seasonal unit roots, Asymptotic distributions, Unit root tests, Brownian motions, JEL Classification, C12, C22, X-DOI: 10.1081/ETC-120014350 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-120014350 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:21:y:2002:i:2:p:221-241 Template-Type: ReDIF-Article 1.0 Author-Name: Eiji Kurozumi Author-X-Name-First: Eiji Author-X-Name-Last: Kurozumi Title: TESTING FOR PERIODIC STATIONARITY Abstract: This paper proposes a test for the null hypothesis of periodic stationarity against the alternative hypothesis of periodic integration. We derive the limiting distribution of the test statistic and its characteristic function, which are the same as those of the test developed in Kwiatkowski, Phillips, Schmidt and Shin.[15] We find that some parameters, which we must assume under the alternative, have an important effect on the limiting power, so we should choose such parameters carefully. A Monte Carlo simulation reveals that the test has reasonable power but may be affected by the lag truncation parameter that is used for the correction of nuisance parameters. Journal: Econometric Reviews Pages: 243-270 Issue: 2 Volume: 21 Year: 2002 Keywords: Periodic stationarity, Periodic integration, Hypothesis testing, JEL Classification, C22, C32, X-DOI: 10.1081/ETC-120014351 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-120014351 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:21:y:2002:i:2:p:243-270 Template-Type: ReDIF-Article 1.0 Author-Name: Alain Hecq Author-X-Name-First: Alain Author-X-Name-Last: Hecq Author-Name: Franz Palm Author-X-Name-First: Franz Author-X-Name-Last: Palm Author-Name: Jean-Pierre Urbain Author-X-Name-First: Jean-Pierre Author-X-Name-Last: Urbain Title: SEPARATION, WEAK EXOGENEITY, AND P-T DECOMPOSITION IN COINTEGRATED VAR SYSTEMS WITH COMMON FEATURES Abstract: The aim of this paper is to study the concept of separability in multiple nonstationary time series displaying both common stochastic trends and common stochastic cycles. When modeling the dynamics of multiple time series for a panel of several entities such as countries, sectors, firms, imposing some form of separability and commonalities is often required to restrict the dimension of the parameter space. For this purpose we introduce the concept of common feature separation and investigate the relationships between separation in cointegration and separation in serial correlation common features. Loosely speaking we investigate whether a set of time series can be partitioned into subsets such that there are serial correlation common features within the sub-groups only. The paper investigates three issues. First, it provides conditions for separating joint cointegrating vectors into marginal cointegrating vectors as well as separating joint short-term dynamics into marginal short-term dynamics. Second, conditions for making permanent-transitory decompositions based on marginal systems are given. Third, issues of weak exogeneity are considered. Likelihood ratio type tests for the different hypotheses under study are proposed. An empirical analysis of the link between economic fluctuations in the United States and Canada shows the practical relevance of the approach proposed in this paper. Journal: Econometric Reviews Pages: 273-307 Issue: 3 Volume: 21 Year: 2002 Keywords: Separation, Cointegration, Common features, Weak exogeneity, P-T Decomposition, Consumption function, X-DOI: 10.1081/ETC-120015785 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-120015785 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:21:y:2002:i:3:p:273-307 Template-Type: ReDIF-Article 1.0 Author-Name: Jinyong Hahn Author-X-Name-First: Jinyong Author-X-Name-Last: Hahn Author-Name: Atsushi Inoue Author-X-Name-First: Atsushi Author-X-Name-Last: Inoue Title: A MONTE CARLO COMPARISON OF VARIOUS ASYMPTOTIC APPROXIMATIONS TO THE DISTRIBUTION OF INSTRUMENTAL VARIABLES ESTIMATORS Abstract: We examine empirical relevance of three alternative asymptotic approximations to the distribution of instrumental variables estimators by Monte Carlo experiments. We find that conventional asymptotics provides a reasonable approximation to the actual distribution of instrumental variables estimators when the sample size is reasonably large. For most sample sizes, we find Bekker[11] asymptotics provides reasonably good approximation even when the first stage R2 is very small. We conclude that reporting Bekker[11] confidence interval would suffice for most microeconometric (cross-sectional) applications, and the comparative advantage of Staiger and Stock[5] asymptotic approximation is in applications with sample sizes typical in macroeconometric (time series) applications. Journal: Econometric Reviews Pages: 309-336 Issue: 3 Volume: 21 Year: 2002 Keywords: Many instruments, Weak instruments, JEL Classification: C31, X-DOI: 10.1081/ETC-120015786 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-120015786 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:21:y:2002:i:3:p:309-336 Template-Type: ReDIF-Article 1.0 Author-Name: Yanqin Fan Author-X-Name-First: Yanqin Author-X-Name-Last: Fan Author-Name: Qi Li Author-X-Name-First: Qi Author-X-Name-Last: Li Title: A CONSISTENT MODEL SPECIFICATION TEST BASED ON THE KERNEL SUM OF SQUARES OF RESIDUALS Abstract: This paper constructs a consistent model specification test based on the difference between the nonparametric kernel sum of squares of residuals and the sum of squares of residuals from a parametric null model. We establish the asymptotic normality of the proposed test statistic under the null hypothesis of correct parametric specification and show that the wild bootstrap method can be used to approximate the null distribution of the test statistic. Results from a small simulation study are reported to examine the finite sample performance of the proposed tests. Journal: Econometric Reviews Pages: 337-352 Issue: 3 Volume: 21 Year: 2002 Keywords: Consistent test, Kernel method, Sum of squares of residuals, Asymptotic normality, Wild bootstrap, Simulation, JEL Classification Number: C12, C14, X-DOI: 10.1081/ETC-120015787 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-120015787 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:21:y:2002:i:3:p:337-352 Template-Type: ReDIF-Article 1.0 Author-Name: Serena Ng Author-X-Name-First: Serena Author-X-Name-Last: Ng Author-Name: Timothy Vogelsang Author-X-Name-First: Timothy Author-X-Name-Last: Vogelsang Title: ANALYSIS OF VECTOR AUTOREGRESSIONS IN THE PRESENCE OF SHIFTS IN MEAN Abstract: This paper considers the implications of mean shifts in a multivariate setting. It is shown that under the additive outlier type mean shift specification, the intercept in each equation of the vector autoregression (VAR) will be subject to multiple shifts when the break dates of the mean shifts to the univariate series do not coincide. Conversely, under the innovative outlier type mean shift specification, both the univariate and the multivariate time series are subject to multiple shifts when mean shifts to the innovation processes occur at different dates. We consider two procedures, the first removes the shifts series by series before forming the VAR, and the second removes intercept shifts in the VAR directly. The pros and cons of both methods are discussed. Journal: Econometric Reviews Pages: 353-381 Issue: 3 Volume: 21 Year: 2002 Keywords: Trend break, Structural change, Causality tests, Forecasting, X-DOI: 10.1081/ETC-120015788 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-120015788 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:21:y:2002:i:3:p:353-381 Template-Type: ReDIF-Article 1.0 Author-Name: Jason Abrevaya Author-X-Name-First: Jason Author-X-Name-Last: Abrevaya Title: COMPUTING MARGINAL EFFECTS IN THE BOX-COX MODEL Abstract: This paper considers computation of fitted values and marginal effects in the Box-Cox regression model. Two methods, 1 the “smearing” technique suggested by Duan (see Ref. [10]) and 2 direct numerical integration, are examined and compared with the “naive” method often used in econometrics. Journal: Econometric Reviews Pages: 383-393 Issue: 3 Volume: 21 Year: 2002 Keywords: Marginal effects, Box-Cox model, JEL Classification: C13, C21, X-DOI: 10.1081/ETC-120015789 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-120015789 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:21:y:2002:i:3:p:383-393 Template-Type: ReDIF-Article 1.0 Author-Name: Jonathan Wright Author-X-Name-First: Jonathan Author-X-Name-Last: Wright Title: LOG-PERIODOGRAM ESTIMATION OF LONG MEMORY VOLATILITY DEPENDENCIES WITH CONDITIONALLY HEAVY TAILED RETURNS Abstract: Many recent papers have used semiparametric methods, especially the log-periodogram regression, to detect and estimate long memory in the volatility of asset returns. In these papers, the volatility is proxied by measures such as squared, log-squared, and absolute returns. While the evidence for the existence of long memory is strong using any of these measures, the actual long memory parameter estimates can be sensitive to which measure is used. In Monte-Carlo simulations, I find that if the data is conditionally leptokurtic, the log-periodogram regression estimator using squared returns has a large downward bias, which is avoided by using other volatility measures. In United States stock return data, I find that squared returns give much lower estimates of the long memory parameter than the alternative volatility measures, which is consistent with the simulation results. I conclude that researchers should avoid using the squared returns in the semiparametric estimation of long memory volatility dependencies. Journal: Econometric Reviews Pages: 397-417 Issue: 4 Volume: 21 Year: 2002 Keywords: Semiparametric methods, Fractional integration, Stochastic volatility, Stock returns, Heavy tails, JEL Classification: C22, G10, X-DOI: 10.1081/ETC-120015382 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-120015382 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:21:y:2002:i:4:p:397-417 Template-Type: ReDIF-Article 1.0 Author-Name: Ionel Birgean Author-X-Name-First: Ionel Author-X-Name-Last: Birgean Author-Name: Lutz Kilian Author-X-Name-First: Lutz Author-X-Name-Last: Kilian Title: DATA-DRIVEN NONPARAMETRIC SPECTRAL DENSITY ESTIMATORS FOR ECONOMIC TIME SERIES: A MONTE CARLO STUDY Abstract: Spectral analysis at frequencies other than zero plays an increasingly important role in econometrics. A number of alternative automated data-driven procedures for nonparametric spectral density estimation have been suggested in the literature, but little is known about their finite-sample accuracy. We compare five such procedures in terms of their mean-squared percentage error across frequencies. Our data generating processes (DGP) include autoregressive-moving average (ARMA) models, fractionally integrated ARMA models and nonparametric models based on 16 commonly used macroeconomic time series. We find that for both quarterly and monthly data the autoregressive sieve estimator is the most reliable method overall. Journal: Econometric Reviews Pages: 449-476 Issue: 4 Volume: 21 Year: 2002 Keywords: Business cycle measurement, Model identification, Periodogram smoothing, Autocovariance smoothing, Autoregressive sieve, Bandwidth selection, X-DOI: 10.1081/ETC-120015386 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-120015386 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:21:y:2002:i:4:p:449-476 Template-Type: ReDIF-Article 1.0 Author-Name: Edoardo Otranto Author-X-Name-First: Edoardo Author-X-Name-Last: Otranto Author-Name: Giampiero Gallo Author-X-Name-First: Giampiero Author-X-Name-Last: Gallo Title: A NONPARAMETRIC BAYESIAN APPROACH TO DETECT THE NUMBER OF REGIMES IN MARKOV SWITCHING MODELS Abstract: Journal: Econometric Reviews Pages: 477-496 Issue: 4 Volume: 21 Year: 2002 Keywords: Markov switching models, Nuisance parameters, Specification testing, Exchange rate determination, JEL Classification: C2, C5, F3, X-DOI: 10.1081/ETC-120015387 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-120015387 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:21:y:2002:i:4:p:477-496 Template-Type: ReDIF-Article 1.0 Author-Name: Russell Davidson Author-X-Name-First: Russell Author-X-Name-Last: Davidson Author-Name: James MacKinnon Author-X-Name-First: James Author-X-Name-Last: MacKinnon Title: FAST DOUBLE BOOTSTRAP TESTS OF NONNESTED LINEAR REGRESSION MODELS Abstract: It has been shown in previous work that bootstrapping the J test for nonnested linear regression models dramatically improves its finite-sample performance. We provide evidence that a more sophisticated bootstrap procedure, which we call the fast double bootstrap, produces a very substantial further improvement in cases where the ordinary bootstrap does not work as well as it might. This FDB procedure is only about twice as expensive as the usual single bootstrap. Journal: Econometric Reviews Pages: 419-429 Issue: 4 Volume: 21 Year: 2002 Keywords: Nonnested test, Bootstrap test, Jtest, JEL Classification:C12, C15, C20, X-DOI: 10.1081/ETC-120015384 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-120015384 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:21:y:2002:i:4:p:419-429 Template-Type: ReDIF-Article 1.0 Author-Name: Yoosoon Chang Author-X-Name-First: Yoosoon Author-X-Name-Last: Chang Author-Name: Joon Park Author-X-Name-First: Joon Author-X-Name-Last: Park Title: ON THE ASYMPTOTICS OF ADF TESTS FOR UNIT ROOTS Abstract: In this paper, we derive the asymptotic distributions of Augmented-Dickey-Fuller (ADF) tests under very mild conditions. The tests were originally proposed and investigated by Said and Dickey (1984) for testing unit roots in finite-order ARMA models with i.i.d. innovations, and are based on a finite AR process of order increasing with the sample size. Our conditions are significantly weaker than theirs. In particular, we allow for general linear processes with martingale difference innovations, possibly having conditional heteroskedasticities. The linear processes driven by ARCH type innovations are thus permitted. The range for the permissible increasing rates for the AR approximation order is also much wider. For the usual t-type test, we only require that it increase at order o(n1/2) while they assume that it is of order o(nκ) for some κ satisfying 0 < κ ≤ 1/3. Journal: Econometric Reviews Pages: 431-447 Issue: 4 Volume: 21 Year: 2002 Keywords: ADF tests, Unit roots, Asymptotics, Linear process, Autoregressive approximation, X-DOI: 10.1081/ETC-120015385 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-120015385 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:21:y:2002:i:4:p:431-447 Template-Type: ReDIF-Article 1.0 Author-Name: Fran�ois Laisney Author-X-Name-First: Fran�ois Author-X-Name-Last: Laisney Author-Name: Michael Lechner Author-X-Name-First: Michael Author-X-Name-Last: Lechner Title: Almost Consistent Estimation of Panel Probit Models with "Small" Fixed Effects Abstract: We propose four different GMM estimators that allow almost consistent estimation of the structural parameters of panel probit models with fixed effects for the case of small Tand large N. The moments used are derived for each period from a first order approximation of the mean of the dependent variable conditional on explanatory variables and on the fixed effect. The estimators differ w.r.t. the choice of instruments and whether they use trimming to reduce the bias or not. In a Monte Carlo study, we compare these estimators with pooled probit and conditional logit estimators for different data generating processes. The results show that the proposed estimators outperform these competitors in several situations. Journal: Econometric Reviews Pages: 1-28 Issue: 1 Volume: 22 Year: 2003 Month: 2 X-DOI: 10.1081/ETC-120017972 File-URL: http://hdl.handle.net/10.1081/ETC-120017972 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:22:y:2003:i:1:p:1-28 Template-Type: ReDIF-Article 1.0 Author-Name: Maurice J. G. Bun Author-X-Name-First: Maurice J. G. Author-X-Name-Last: Bun Title: Bias Correction in the Dynamic Panel Data Model with a Nonscalar Disturbance Covariance Matrix Abstract: Approximation formulae are developed for the bias of ordinary and generalized Least Squares Dummy Variable (LSDV) estimators in dynamic panel data models. Results from Kiviet [Kiviet, J. F. (1995), on bias, inconsistency, and efficiency of various estimators in dynamic panel data models, J. Econometrics68:53-78; Kiviet, J. F. (1999), Expectations of expansions for estimators in a dynamic panel data model: some results for weakly exogenous regressors, In: Hsiao, C., Lahiri, K., Lee, L-F., Pesaran, M. H., eds., Analysis of Panels and Limited Dependent Variables, Cambridge: Cambridge University Press, pp. 199-225] are extended to higher-order dynamic panel data models with general covariance structure. The focus is on estimation of both short- and long-run coefficients. The results show that proper modelling of the disturbance covariance structure is indispensable. The bias approximations are used to construct bias corrected estimators which are then applied to quarterly data from 14 European Union countries. Money demand functions for M1, M2 and M3 are estimated for the EU area as a whole for the period 1991: I-1995: IV. Significant spillovers between countries are found reflecting the dependence of domestic money demand on foreign developments. The empirical results show that in general plausible long-run effects are obtained by the bias corrected estimators. Moreover, finite sample bias, although of moderate magnitude, is present underlining the importance of more refined estimation techniques. Also the efficiency gains by exploiting the heteroscedasticity and cross-correlation patterns between countries are sometimes considerable. Journal: Econometric Reviews Pages: 29-58 Issue: 1 Volume: 22 Year: 2003 Month: 2 X-DOI: 10.1081/ETC-120017973 File-URL: http://hdl.handle.net/10.1081/ETC-120017973 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:22:y:2003:i:1:p:29-58 Template-Type: ReDIF-Article 1.0 Author-Name: Melvyn Weeks Author-X-Name-First: Melvyn Author-X-Name-Last: Weeks Author-Name: James Yudong Yao Author-X-Name-First: James Author-X-Name-Last: Yudong Yao Title: Provincial Conditional Income Convergence in China, 1953-1997: A Panel Data Approach Abstract: This paper examines the tendency towards income convergence among China's main provinces during the two periods: the pre-reform period 1953-1977 and the reform period 1978-1997 using the framework of the Solow growth model. The panel data method accounts for not only province-specific initial technology level but also the heterogeneity of the technological progress rate between the fast-growing coastal and interior provinces. Estimation problems of weak instruments and endogeneity are addressed by the use of a system generalized method of moments (GMM) estimator. The main empirical finding is that there is a system-wide income divergence during the reform period because the coastal provinces do not share a common technology progress rate with the interior provinces. Journal: Econometric Reviews Pages: 59-77 Issue: 1 Volume: 22 Year: 2003 Month: 2 X-DOI: 10.1081/ETC-120017974 File-URL: http://hdl.handle.net/10.1081/ETC-120017974 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:22:y:2003:i:1:p:59-77 Template-Type: ReDIF-Article 1.0 Author-Name: Rafik Baccouche Author-X-Name-First: Rafik Author-X-Name-Last: Baccouche Author-Name: Mokhtar Kouki Author-X-Name-First: Mokhtar Author-X-Name-Last: Kouki Title: Stochastic Production Frontier and Technical Inefficiency: A Sensitivity Analysis Abstract: The present paper focuses attention on the sensitivity of technical inefficiency to most commonly used one-sided distributions of the inefficiency error term, namely the truncated normal, the half-normal, and the exponential distributions. A generalized version of the half-normal, which does not embody the zero-mean restriction, is also explored. For each distribution, the likelihood function and the counterpart of the estimator of technical efficiency are explicitly stated (Jondrow, J., Lovell, C. A. K., Materov, I. S., Schmidt, P. ([1982]), On estimation of technical inefficiency in the stochastic frontier production function model, J. Econometrics19:233-238). Based on our panel data set, related to Tunisian manufacturing firms over the period 1983-1993, formal tests lead to a strong rejection of the zero-mean restriction embodied in the half normal distribution. Our main conclusion is that the degree of measured inefficiency is very sensitive to the postulated assumptions about the distribution of the one-sided error term. The estimated inefficiency indices are, however, unaffected by the choice of the functional form for the production function. Journal: Econometric Reviews Pages: 79-91 Issue: 1 Volume: 22 Year: 2003 Month: 2 X-DOI: 10.1081/ETC-120017975 File-URL: http://hdl.handle.net/10.1081/ETC-120017975 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:22:y:2003:i:1:p:79-91 Template-Type: ReDIF-Article 1.0 Author-Name: Rim Ben Ayed-Mouelhi Author-X-Name-First: Rim Ben Author-X-Name-Last: Ayed-Mouelhi Author-Name: Mohamed Goa�ed Author-X-Name-First: Mohamed Author-X-Name-Last: Goa�ed Title: Efficiency Measure from Dynamic Stochastic Production Frontier: Application to Tunisian Textile, Clothing, and Leather Industries Abstract: This paper adresses the measurement of technical efficiency of textile, clothing, and leather (TCL) industries in Tunisia through a panel data estimation of a dynamic translog production frontier. It provides a perspective on productivity and efficiency that should be instructive to a developing economy which will face substantial competitive pressure along the gradual economic liberalisation process. The importance of TCL industries in Tunisian manufacturing sector is a reason for obtaining more knowledge of productivity and efficiency for this key industry. Dynamic is introduced to reflect the production consequences of the adjustment costs, which are associated with changes in factor inputs. Estimation of a dynamic error components model is considered using the system generalized method of moments (GMM) estimator suggested by Arellano and Bover (1995), Another look at the instrumental-variable estimation of error-components models, J. Econometrics68:29-51) and Blundell and Bond (Blundell, R., Bond, S. (1998a), Initial conditions and moment restrictions in dynamic panel data models. J. Econometrics87:115-143; Blundell, R., Bond, S. (1998b), GMM estimation with persistent panel data: an application to production functions, Paper presented at the Eighth International Conference on Panel Data, Goteborg University). Our study evaluates the sensitivity of the results, particularly of the efficiency measures, to different specifications. Firm-specific time-invariant technical efficiency is obtained using the Schmidt and Sickles (Schmidt, P., Sickles, R. C. (1984). Production frontiers and panel data. J. Bus. Econ. Stat.2:367-374) approach after estimating the dynamic frontier. We stress the importance of allowing for lags in adjustment of output to inputs and of controlling for time-invariant variables when estimating firm-specific efficiency. The results suggest that the system GMM estimation of the dynamic specification produces the most accurate parameter estimates and technical efficiency measure. Mean efficiency scores is of 68%. Policy implications of the results are outlined. Journal: Econometric Reviews Pages: 93-111 Issue: 1 Volume: 22 Year: 2003 Month: 2 X-DOI: 10.1081/ETC-120017976 File-URL: http://hdl.handle.net/10.1081/ETC-120017976 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:22:y:2003:i:1:p:93-111 Template-Type: ReDIF-Article 1.0 Author-Name: Cheng Hsiao Author-X-Name-First: Cheng Author-X-Name-Last: Hsiao Title: In Memoriam: G. S. Maddala Journal: Econometric Reviews Pages: vii-ix Issue: 1 Volume: 22 Year: 2003 Month: 2 X-DOI: 10.1081/ETC-120017977 File-URL: http://hdl.handle.net/10.1081/ETC-120017977 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:22:y:2003:i:1:p:vii-ix Template-Type: ReDIF-Article 1.0 Author-Name: Jacques Mairesse Author-X-Name-First: Jacques Author-X-Name-Last: Mairesse Title: In Memoriam: Zvi Griliches Journal: Econometric Reviews Pages: xi-xv Issue: 1 Volume: 22 Year: 2003 Month: 2 X-DOI: 10.1081/ETC-120017978 File-URL: http://hdl.handle.net/10.1081/ETC-120017978 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:22:y:2003:i:1:p:xi-xv Template-Type: ReDIF-Article 1.0 Author-Name: Brian Boyer Author-X-Name-First: Brian Author-X-Name-Last: Boyer Author-Name: James McDonald Author-X-Name-First: James Author-X-Name-Last: McDonald Author-Name: Whitney Newey Author-X-Name-First: Whitney Author-X-Name-Last: Newey Title: A Comparison of Partially Adaptive and Reweighted Least Squares Estimation Abstract: The small sample performance of least median of squares, reweighted least squares, least squares, least absolute deviations, and three partially adaptive estimators are compared using Monte Carlo simulations. Two data problems are addressed in the paper: (1) data generated from non-normal error distributions and (2) contaminated data. Breakdown plots are used to investigate the sensitivity of partially adaptive estimators to data contamination relative to RLS. One partially adaptive estimator performs especially well when the errors are skewed, while another partially adaptive estimator and RLS perform particularly well when the errors are extremely leptokur-totic. In comparison with RLS, partially adaptive estimators are only moderately effective in resisting data contamination; however, they outperform least squares and least absolute deviation estimators. Journal: Econometric Reviews Pages: 115-134 Issue: 2 Volume: 22 Year: 2003 Keywords: Least median of squares, Reweighted least squares, Partially adaptive estimation, X-DOI: 10.1081/ETC-120020459 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-120020459 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:22:y:2003:i:2:p:115-134 Template-Type: ReDIF-Article 1.0 Author-Name: William Barnett Author-X-Name-First: William Author-X-Name-Last: Barnett Author-Name: Meenakshi Pasupathy Author-X-Name-First: Meenakshi Author-X-Name-Last: Pasupathy Title: Regularity of the Generalized Quadratic Production Model: A Counterexample Abstract: Recently there has been a growing tendency to impose curvature, but not monotonicity, on specifications of technology. But regularity requires satisfaction of both curvature and monotonicity conditions. Without both satisfied, the second order conditions for optimizing behavior fail and duality theory fails. When neither curvature nor monotonicity are imposed, estimated flexible specifications of technology are much more likely to violate curvature than monotonicity. Hence it has been argued that there is no need to impose or check for monotonicity, when curvature has been imposed globally. But imposition of curvature may induce violations of monotonicity that otherwise would not have occurred. We explore the regularity properties of our earlier results with a multiproduct financial technology specified to be generalized quadratic. In our earlier work, we used the usual approach and accepted the usual view. We now find that imposition of curvature globally and monotonicity locally does not assure monotonicity within the region of the data. Our purpose is to alert researchers to the kinds of problems that we encountered and which we believe are largely being overlooked in the production modelling literature, as we had been overlooking them. Journal: Econometric Reviews Pages: 135-154 Issue: 2 Volume: 22 Year: 2003 Keywords: Technology, Regularity, Curvature, Production, Flexibility, X-DOI: 10.1081/ETC-120020460 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-120020460 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:22:y:2003:i:2:p:135-154 Template-Type: ReDIF-Article 1.0 Author-Name: Esfandiar Maasoumi Author-X-Name-First: Esfandiar Author-X-Name-Last: Maasoumi Author-Name: Daniel Slottje Author-X-Name-First: Daniel Author-X-Name-Last: Slottje Title: Dynamics of Market Power and Concentration Profiles Abstract: This paper examines some of the economic and econometric issues that arise in attempting to measure the degree of concentration in an industry and its dynamic evolution. A general axiomatic basis is developed. We offer new measures of concentration over aggregated periods of time and provide a sound statistical basis for inferences. Concentration is one aspect of the problem of measuring “market power” within an industry. Modern economic analysis of antitrust issues does not focus only on the level of concentration, but still must examine the issue carefully. We contrast concentration at a point in time with a dynamic profile of change in the distribution of shares in a given market. Our methods are demonstrated with an application to the US steel industry. Journal: Econometric Reviews Pages: 155-177 Issue: 2 Volume: 22 Year: 2003 Keywords: Market power, Concentration, Mobility, Statistical inference, US Steel industry, Industrial concentration, Antitrust, Steel, Tests, Dynamic profiles, X-DOI: 10.1081/ETC-120020461 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-120020461 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:22:y:2003:i:2:p:155-177 Template-Type: ReDIF-Article 1.0 Author-Name: Shiqing Ling Author-X-Name-First: Shiqing Author-X-Name-Last: Ling Author-Name: W. K. Li Author-X-Name-First: W. K. Author-X-Name-Last: Li Author-Name: Michael McAleer Author-X-Name-First: Michael Author-X-Name-Last: McAleer Title: Estimation and Testing for Unit Root Processes with GARCH (1, 1) Errors: Theory and Monte Carlo Evidence Abstract: Least squares (LS) and maximum likelihood (ML) estimation are considered for unit root processes with GARCH (1, 1) errors. The asymptotic distributions of LS and ML estimators are derived under the condition α + β < 1. The former has the usual unit root distribution and the latter is a functional of a bivariate Brownian motion, as in Ling and Li [Ling, S., Li, W. K. (1998). Limiting distributions of maximum likelihood estimators for unstable autoregressive moving-average time series with GARCH errors. Ann. Statist.26:84-125]. Several unit root tests based on LS estimators, ML estimators, and mixing LS and ML estimators, are constructed. Simulation results show that tests based on mixing LS and ML estimators perform better than Dickey-Fuller tests which are based on LS estimators, and that tests based on the ML estimators perform better than the mixed estimators. Journal: Econometric Reviews Pages: 179-202 Issue: 2 Volume: 22 Year: 2003 Keywords: Asymptotic distribution, Brownian motion, GARCH model, Least squares estimator, Maximum likelihood estimator, Unit root, X-DOI: 10.1081/ETC-120020462 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-120020462 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:22:y:2003:i:2:p:179-202 Template-Type: ReDIF-Article 1.0 Author-Name: Arnold Zellner Author-X-Name-First: Arnold Author-X-Name-Last: Zellner Title: Some Recent Developments in Econometric Inference Abstract: Recent results in information theory, see Soofi (1996; 2001) for a review, include derivations of optimal information processing rules, including Bayes' theorem, for learning from data based on minimizing a criterion functional, namely output information minus input information as shown in Zellner (1988; 1991; 1997; 2002). Herein, solution post data densities for parameters are obtained and studied for cases in which the input information is that in (1) a likelihood function and a prior density; (2) only a likelihood function; and (3) neither a prior nor a likelihood function but only input information in the form of post data moments of parameters, as in the Bayesian method of moments approach. Then it is shown how optimal output densities can be employed to obtain predictive densities and optimal, finite sample structural coefficient estimates using three alternative loss functions. Such optimal estimates are compared with usual estimates, e.g., maximum likelihood, two-stage least squares, ordinary least squares, etc. Some Monte Carlo experimental results in the literature are discussed and implications for the future are provided. Journal: Econometric Reviews Pages: 203-215 Issue: 2 Volume: 22 Year: 2003 Keywords: Econometric inference, Bayes' theorem, Information theory, Learning, Optimal estimation, X-DOI: 10.1081/ETC-120020463 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-120020463 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:22:y:2003:i:2:p:203-215 Template-Type: ReDIF-Article 1.0 Author-Name: Elena Andreou Author-X-Name-First: Elena Author-X-Name-Last: Andreou Author-Name: Aris Spanos Author-X-Name-First: Aris Author-X-Name-Last: Spanos Title: Statistical Adequacy and the Testing of Trend Versus Difference Stationarity Abstract: The debate on whether macroeconomic series are trend or difference stationary, initiated by Nelson and Plosser [Nelson, C. R.; Plosser, C. I. (1982). Trends and random walks in macroeconomic time series: some evidence and implications. Journal of Monetary Economics10:139-162] remains unresolved. The main objective of the paper is to contribute toward a resolution of this issue by bringing into the discussion the problem of statistical adequacy. The paper revisits the empirical results of Nelson and Plosser [Nelson, C. R.; Plosser, C. I. (1982). Trends and random walks in macroeconomic time series: some evidence and implications. Journal of Monetary Economics10:139-162] and Perron [Perron, P. (1989). The great crash, the oil price shock, and the unit root hypothesis. Econometrica57:1361-1401] and shows that several of their estimated models are misspecified. Respecification with a view to ensuring statistical adequacy gives rise to heteroskedastic AR(k) models for some of the price series. Based on estimated models which are statistically adequate, the main conclusion of the paper is that the majority of the data series are trend stationary. Journal: Econometric Reviews Pages: 217-237 Issue: 3 Volume: 22 Year: 2003 Month: 1 X-DOI: 10.1081/ETC-120023897 File-URL: http://hdl.handle.net/10.1081/ETC-120023897 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:22:y:2003:i:3:p:217-237 Template-Type: ReDIF-Article 1.0 Author-Name: Pierre Perron Author-X-Name-First: Pierre Author-X-Name-Last: Perron Title: Comment on "Statistical Adequacy and the Testing of Trend Versus Difference Stationarity" by Andreou and Spanos (Number 1) Journal: Econometric Reviews Pages: 239-245 Issue: 3 Volume: 22 Year: 2003 Month: 1 X-DOI: 10.1081/ETC-120023900 File-URL: http://hdl.handle.net/10.1081/ETC-120023900 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:22:y:2003:i:3:p:239-245 Template-Type: ReDIF-Article 1.0 Author-Name: Robin L. Lumsdaine Author-X-Name-First: Robin L. Author-X-Name-Last: Lumsdaine Title: Comment on "Statistical Adequacy and the Testing of Trend Versus Difference Stationarity" by Andreou and Spanos (Number 2)-super-# Abstract: <fn id="FN0001"> -super-#The opinions expressed are the author's and do not represent those of Deutsche Bank or its affiliates. </fn> Journal: Econometric Reviews Pages: 247-252 Issue: 3 Volume: 22 Year: 2003 Month: 1 X-DOI: 10.1081/ETC-120023903 File-URL: http://hdl.handle.net/10.1081/ETC-120023903 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:22:y:2003:i:3:p:247-252 Template-Type: ReDIF-Article 1.0 Author-Name: Ragnar Nymoen Author-X-Name-First: Ragnar Author-X-Name-Last: Nymoen Title: Comment on "Statistical Adequacy and the Testing of Trend Versus Difference Stationarity" by Andreou and Spanos (Number 3) Journal: Econometric Reviews Pages: 253-260 Issue: 3 Volume: 22 Year: 2003 Month: 1 X-DOI: 10.1081/ETC-120023906 File-URL: http://hdl.handle.net/10.1081/ETC-120023906 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:22:y:2003:i:3:p:253-260 Template-Type: ReDIF-Article 1.0 Author-Name: Maozu Lu Author-X-Name-First: Maozu Author-X-Name-Last: Lu Author-Name: Jan M. Podivinsky Author-X-Name-First: Jan M. Author-X-Name-Last: Podivinsky Title: The Robustness of Trend Stationarity: An Illustration with the Extended Nelson-Plosser Dataset Abstract: We re-evaluate Andreu and Spanos's findings in favour of trend stationarity by considering the extended Nelson-Plosser data set. This expanded (to 1988) data set includes a period of rather different behaviour compared with the original Nelson-Plosser data used by Andreou and Spanos. We find that Andreou and Spanos's models (with only minor adjustments) exhibit remarable stability over this extended period, and indicate that their conclusions are more robust than they have shown. Journal: Econometric Reviews Pages: 261-267 Issue: 3 Volume: 22 Year: 2003 Month: 1 X-DOI: 10.1081/ETC-120024075 File-URL: http://hdl.handle.net/10.1081/ETC-120024075 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:22:y:2003:i:3:p:261-267 Template-Type: ReDIF-Article 1.0 Author-Name: Alastair R. Hall Author-X-Name-First: Alastair R. Author-X-Name-Last: Hall Author-Name: Fernanda P. M. Peixe Author-X-Name-First: Fernanda P. M. Author-X-Name-Last: Peixe Title: A Consistent Method for the Selection of Relevant Instruments Abstract: In many applications, a researcher must select an instrument vector from a candidate set of instruments. If the ultimate objective is to perform inference about the unknown parameters using conventional asymptotic theory, then we argue that it is desirable for the chosen instrument vector to satisfy four conditions which we refer to as orthogonality, identification, efficiency, and non-redundancy. It is impossible to verify a priori which elements of the candidate set satisfy these conditions; this can only be done using the data. However, once the data are used in this fashion it is important that the selection process does not contaminate the limiting distribution of the parameter estimator. We refer to this requirement as the inference condition. In a recent paper, Andrews [[Andrews, D. W. K. (1999)]. Consistent moment selection procedures for generalized method of moments estimation. <italic>Econometrica</italic>67:543-564] has proposed a method of moment selection based on an information criterion involving the overidentifying restrictions test. This method can be shown to select an instrument vector which satisfies the orthogonality condition with probability one in the limit. In this paper, we consider the problem of instrument selection based on a combination of the efficiency and non-redundancy conditions which we refer to as the relevance condition. It is shown that, within a particular class of models, certain canonical correlations form the natural metric for relevancy, and this leads us to propose a canonical correlations information criterion (CCIC) for instrument selection. We establish conditions under which our method satisfies the inference condition. We also consider the properties of an instrument selection method based on the sequential application of [Andrews, D. W. K. (1999)]. Consistent moment selection procedures for generalized method of moments estimation. <italic>Econometrica</italic>67:543-564 method and CCIC. Journal: Econometric Reviews Pages: 269-287 Issue: 3 Volume: 22 Year: 2003 Month: 1 X-DOI: 10.1081/ETC-120024752 File-URL: http://hdl.handle.net/10.1081/ETC-120024752 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:22:y:2003:i:3:p:269-287 Template-Type: ReDIF-Article 1.0 Author-Name: Rodolfo Cermeño Author-X-Name-First: Rodolfo Author-X-Name-Last: Cermeño Author-Name: G. S. Maddala Author-X-Name-First: G. S. Author-X-Name-Last: Maddala Author-Name: Michael A. Trueblood Author-X-Name-First: Michael A. Author-X-Name-Last: Trueblood Title: Modeling Technology as a Dynamic Error Components Process: The Case of the Inter-country Agricultural Production Function† Abstract: In this paper, we propose a dynamic error-components model to represent the unobserved level of technology. This specification implies a well-defined common factor dynamic model for per capita output that can be tested explicitly. The model is applied to data on aggregates of agricultural inputs and outputs for groups of countries from the OECD, Africa (AF), Latin America (LA) as well as centrally planned countries, over a period of 31 years. We find that the proposed model fits the data better than alternative static specifications and satisfies the implied common factor restrictions in two of the samples. The results suggest that although technological change seems to have been a faster process for less developed countries relative to the OECD countries, it has not been fast enough to reduce appreciably the enormous differences in average technological levels that still persist between them.<fn id="FN0001"> -super-†Dedicated to the memory of G. S. Maddala. </fn> Journal: Econometric Reviews Pages: 289-306 Issue: 3 Volume: 22 Year: 2003 Month: 1 X-DOI: 10.1081/ETC-120024753 File-URL: http://hdl.handle.net/10.1081/ETC-120024753 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:22:y:2003:i:3:p:289-306 Template-Type: ReDIF-Article 1.0 Author-Name: Lung-fei Lee Author-X-Name-First: Lung-fei Author-X-Name-Last: Lee Title: Best Spatial Two-Stage Least Squares Estimators for a Spatial Autoregressive Model with Autoregressive Disturbances Abstract: Estimation of a cross-sectional spatial model containing both a spatial lag of the dependent variable and spatially autoregressive disturbances are considered. [Kelejian and Prucha (1998)]described a generalized two-stage least squares procedure for estimating such a spatial model. Their estimator is, however, not asymptotically optimal. We propose best spatial 2SLS estimators that are asymptotically optimal instrumental variable (IV) estimators. An associated goodness-of-fit (or over identification) test is available. We suggest computationally simple and tractable numerical procedures for constructing the optimal instruments. Journal: Econometric Reviews Pages: 307-335 Issue: 4 Volume: 22 Year: 2003 Keywords: Spatial autoregressive model, Two-stage least squares, Asymptotic efficiency, Best two-stage least squares, Cholesky decomposition, Contracting mapping, X-DOI: 10.1081/ETC-120025891 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-120025891 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:22:y:2003:i:4:p:307-335 Template-Type: ReDIF-Article 1.0 Author-Name: Jorge Belaire-Franch Author-X-Name-First: Jorge Author-X-Name-Last: Belaire-Franch Title: A Note on Resampling the Integration Across the Correlation Integral with Alternative Ranges Abstract: This paper reconsiders the nonlinearity test proposed by Koc-super-˘enda (Koc-super-˘enda, E. (2001). An alternative to the BDS test: integration across the correlation integral. Econometric Reviews20:337-351). When the analyzed series is non-Gaussian, the empirical rejection rates can be much larger than the nominal size. In this context, the necessity of tabulating the empirical distribution of the statistic each time the test is computed is stressed. To that end, simple random permutation works reasonably well. This paper also shows, through Monte Carlo experiments, that Koc-super-˘enda's test can be more powerful than the Brock et al. (Brock, W., Dechert, D., Scheickman, J., LeBaron, B. (1996). A test for independence based on the correlation dimension. Econometric Reviews15:197-235) procedure. However, more than one range of values for the proximity parameter should be used. Finally, empirical evidence on exchange rates is reassessed. Journal: Econometric Reviews Pages: 337-349 Issue: 4 Volume: 22 Year: 2003 Keywords: Chaos, Nonlinear dynamics, Koc-super-˘enda's test, Random permutation, Exchange rates, X-DOI: 10.1081/ETC-120025892 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-120025892 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:22:y:2003:i:4:p:337-349 Template-Type: ReDIF-Article 1.0 Author-Name: Manuel Dominguez Author-X-Name-First: Manuel Author-X-Name-Last: Dominguez Author-Name: Ignacio Lobato Author-X-Name-First: Ignacio Author-X-Name-Last: Lobato Title: Testing the Martingale Difference Hypothesis Abstract: In this paper we consider testing that an economic time series follows a martingale difference process. The martingale difference hypothesis has typically been tested using information contained in the second moments of a process, that is, using test statistics based on the sample autocovariances or periodograms. Tests based on these statistics are inconsistent since they cannot detect nonlinear alternatives. In this paper we consider tests that detect linear and nonlinear alternatives. Given that the asymptotic distributions of the considered tests statistics depend on the data generating process, we propose to implement the tests using a modified wild bootstrap procedure. The paper theoretically justifies the proposed tests and examines their finite sample behavior by means of Monte Carlo experiments. Journal: Econometric Reviews Pages: 351-377 Issue: 4 Volume: 22 Year: 2003 Keywords: Nonlinear dependence, Nonparametric, Correlation, Bootstrap, X-DOI: 10.1081/ETC-120025895 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-120025895 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:22:y:2003:i:4:p:351-377 Template-Type: ReDIF-Article 1.0 Author-Name: Alain Guay Author-X-Name-First: Alain Author-X-Name-Last: Guay Title: Optimal Predictive Tests Abstract: This paper develops optimal tests based on sequential predictive moment conditions. We show that an appropriate weighting version of the predictive test achieves the same power as optimal structural change tests proposed by Sowell (1996a) Optimal tests for parameter instability in the generalized method of moments framework. Econometrica64:1085-1107 and (1996b) Tests for Violations of MOMENT conditions. Manuscript.Graduate School of Industrial Administration, Carnegie Mellon University. Consequently, we can apply directly Sowell's results. Optimal predictive tests for parameter instability and overidentifying restriction stability are proposed. The finite sample properties of LM, Wald, LR-type and predictive tests for parameter instability are studied via a simulation study. Journal: Econometric Reviews Pages: 379-410 Issue: 4 Volume: 22 Year: 2003 Keywords: Predictive test, Optimal test, Moment conditions, X-DOI: 10.1081/ETC-120025896 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-120025896 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:22:y:2003:i:4:p:379-410 Template-Type: ReDIF-Article 1.0 Author-Name: Vasco Gabriel Author-X-Name-First: Vasco Author-X-Name-Last: Gabriel Title: Tests for the Null Hypothesis of Cointegration: A Monte Carlo Comparison Abstract: The aim of this paper is to compare the relative performance of several tests for the null hypothesis of cointegration, in terms of size and power in finite samples. This is carried out using Monte Carlo simulations for a range of plausible data-generating processes. We also analyze the impact on size and power of choosing different procedures to estimate the long run variance of the errors. We found that the parametrically adjusted test of McCabe et al. (1997) is the most well-balanced test, displaying good power and relatively few size distortions. Journal: Econometric Reviews Pages: 411-435 Issue: 4 Volume: 22 Year: 2003 Keywords: Cointegration, Tests, Monte Carlo, X-DOI: 10.1081/ETC-120025897 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-120025897 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:22:y:2003:i:4:p:411-435 Template-Type: ReDIF-Article 1.0 Author-Name: Bent Nielsen Author-X-Name-First: Bent Author-X-Name-Last: Nielsen Title: On the Distribution of Likelihood Ratio Test Statistics for Cointegration Rank Abstract: This paper analyses the likelihood ratio test for the hypothesis of reduced cointegration rank in a Gaussian vector autoregressive model. The usual asymptotic distribution typically gives rather large size distortions. This is explained by the fact that the asymptotic distribution of the likelihood ratio test statistic varies across the parameter space. A much improved distribution approximation can be obtained using local asymptotic theory. The idea is discussed for some low dimensional examples. Journal: Econometric Reviews Pages: 1-23 Issue: 1 Volume: 23 Year: 2004 Keywords: Bartlett corrections, Cointegration, Finite sample results, Lack of similarity, Local asymptotics, X-DOI: 10.1081/ETC-120028834 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-120028834 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:23:y:2004:i:1:p:1-23 Template-Type: ReDIF-Article 1.0 Author-Name: Guglielmo Maria Caporale Author-X-Name-First: Guglielmo Maria Author-X-Name-Last: Caporale Author-Name: Nikitas Pittis Author-X-Name-First: Nikitas Author-X-Name-Last: Pittis Title: Estimator Choice and Fisher's Paradox: A Monte Carlo Study Abstract: This paper argues that Fisher's paradox can be explained away in terms of estimator choice. We analyse by means of Monte Carlo experiments the small sample properties of a large set of estimators (including virtually all available single-equation estimators), and compute the critical values based on the empirical distributions of the t-statistics, for a variety of Data Generation Processes (DGPs), allowing for structural breaks, ARCH effects etc. We show that precisely the estimators most commonly used in the literature, namely OLS, Dynamic OLS (DOLS) and non-prewhitened FMLS, have the worst performance in small samples, and produce rejections of the Fisher hypothesis. If one employs the estimators with the most desirable properties (i.e., the smallest downward bias and the minimum shift in the distribution of the associated t-statistics), or if one uses the empirical critical values, the evidence based on US data is strongly supportive of the Fisher relation, consistently with many theoretical models. Journal: Econometric Reviews Pages: 25-52 Issue: 1 Volume: 23 Year: 2004 Keywords: Fisher's paradox, Cointegration, Single-equation estimators, Monte Carlo analysis, X-DOI: 10.1081/ETC-120028835 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-120028835 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:23:y:2004:i:1:p:25-52 Template-Type: ReDIF-Article 1.0 Author-Name: Dimitris Politis Author-X-Name-First: Dimitris Author-X-Name-Last: Politis Author-Name: Halbert White Author-X-Name-First: Halbert Author-X-Name-Last: White Title: Automatic Block-Length Selection for the Dependent Bootstrap Abstract: We review the different block bootstrap methods for time series, and present them in a unified framework. We then revisit a recent result of Lahiri [Lahiri, S. N. (1999b). Theoretical comparisons of block bootstrap methods, Ann. Statist. 27:386-404] comparing the different methods and give a corrected bound on their asymptotic relative efficiency; we also introduce a new notion of finite-sample “attainable” relative efficiency. Finally, based on the notion of spectral estimation via the flat-top lag-windows of Politis and Romano [Politis, D. N., Romano, J. P. (1995). Bias-corrected nonparametric spectral estimation. J. Time Series Anal. 16:67-103], we propose practically useful estimators of the optimal block size for the aforementioned block bootstrap methods. Our estimators are characterized by the fastest possible rate of convergence which is adaptive on the strength of the correlation of the time series as measured by the correlogram. Journal: Econometric Reviews Pages: 53-70 Issue: 1 Volume: 23 Year: 2004 Keywords: Bandwidth choice, Block bootstrap, Resampling, Subsampling, Time series, Variance estimation, X-DOI: 10.1081/ETC-120028836 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-120028836 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:23:y:2004:i:1:p:53-70 Template-Type: ReDIF-Article 1.0 Author-Name: Amos Golan Author-X-Name-First: Amos Author-X-Name-Last: Golan Author-Name: Enrico Moretti Author-X-Name-First: Enrico Author-X-Name-Last: Moretti Author-Name: Jeffrey M.Perloff Author-X-Name-First: Jeffrey Author-X-Name-Last: M.Perloff Title: A Small-Sample Estimator for the Sample-Selection Model Abstract: A semiparametric estimator for evaluating the parameters of data generated under a sample selection process is developed. This estimator is based on the generalized maximum entropy estimator and performs well for small and ill-posed samples. Theoretical and sampling comparisons with parametric and semiparametric estimators are given. This method and standard ones are applied to three small-sample empirical applications of the wage-participation model for female teenage heads of households, immigrants, and Native Americans. Journal: Econometric Reviews Pages: 71-91 Issue: 1 Volume: 23 Year: 2004 Keywords: Maximum entropy, Sample selection, Monte Carlo experiments, X-DOI: 10.1081/ETC-120028837 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-120028837 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:23:y:2004:i:1:p:71-91 Template-Type: ReDIF-Article 1.0 Author-Name: Jun Yu Author-X-Name-First: Jun Author-X-Name-Last: Yu Title: Empirical Characteristic Function Estimation and Its Applications Abstract: This paper reviews the method of model-fitting via the empirical characteristic function. The advantage of using this procedure is that one can avoid difficulties inherent in calculating or maximizing the likelihood function. Thus it is a desirable estimation method when the maximum likelihood approach encounters difficulties but the characteristic function has a tractable expression. The basic idea of the empirical characteristic function method is to match the characteristic function derived from the model and the empirical characteristic function obtained from data. Ideas are illustrated by using the methodology to estimate a diffusion model that includes a self-exciting jump component. A Monte Carlo study shows that the finite sample performance of the proposed procedure offers an improvement over a GMM procedure. An application using over 72 years of DJIA daily returns reveals evidence of jump clustering. Journal: Econometric Reviews Pages: 93-123 Issue: 2 Volume: 23 Year: 2004 Keywords: Diffusion process, Poisson jump, Self-exciting, GMM, Jump clustering, X-DOI: 10.1081/ETC-120039605 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-120039605 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:23:y:2004:i:2:p:93-123 Template-Type: ReDIF-Article 1.0 Author-Name: William Greene Author-X-Name-First: William Author-X-Name-Last: Greene Title: Fixed Effects and Bias Due to the Incidental Parameters Problem in the Tobit Model Abstract: The maximum likelihood estimator (MLE) in nonlinear panel data models with fixed effects is widely understood (with a few exceptions) to be biased and inconsistent when T, the length of the panel, is small and fixed. However, there is surprisingly little theoretical or empirical evidence on the behavior of the estimator on which to base this conclusion. The received studies have focused almost exclusively on coefficient estimation in two binary choice models, the probit and logit models. In this note, we use Monte Carlo methods to examine the behavior of the MLE of the fixed effects tobit model. We find that the estimator's behavior is quite unlike that of the estimators of the binary choice models. Among our findings are that the location coefficients in the tobit model, unlike those in the probit and logit models, are unaffected by the “incidental parameters problem.” But, a surprising result related to the disturbance variance emerges instead - the finite sample bias appears here rather than in the slopes. This has implications for estimation of marginal effects and asymptotic standard errors, which are also examined in this paper. The effects are also examined for the probit and truncated regression models, extending the range of received results in the first of these beyond the widely cited biases in the coefficient estimators. Journal: Econometric Reviews Pages: 125-147 Issue: 2 Volume: 23 Year: 2004 Keywords: Panel data, Fixed effects, Computation, Monte Carlo, Tobit, Finite sample, Incidental parameters problem, Marginal effects, X-DOI: 10.1081/ETC-120039606 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-120039606 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:23:y:2004:i:2:p:125-147 Template-Type: ReDIF-Article 1.0 Author-Name: Richard Harris Author-X-Name-First: Richard Author-X-Name-Last: Harris Author-Name: Elias Tzavalis Author-X-Name-First: Elias Author-X-Name-Last: Tzavalis Title: Testing for Unit Roots in Dynamic Panels in the Presence of a Deterministic Trend: Re-examining the Unit Root Hypothesis for Real Stock Prices and Dividends Abstract: In this paper, we suggest a similar unit root test statistic for dynamic panel data with fixed effects. The test is based on the LM, or score, principle and is derived under the assumption that the time dimension of the panel is fixed, which is typical in many panel data studies. It is shown that the limiting distribution of the test statistic is standard normal. The similarity of the test with respect to both the initial conditions of the panel and the fixed effects is achieved by allowing for a trend in the model using a parameterisation that has the same interpretation under both the null and alternative hypotheses. This parameterisation can be expected to increase the power of the test statistic. Simulation evidence suggests that the proposed test has empirical size that is very close to the nominal level and considerably more power than other panel unit root tests that assume that the time dimension of the panel is large. As an application of the test, we re-examine the stationarity of real stock prices and dividends using disaggregated panel data over a relatively short period of time. Our results suggest that while real stock prices contain a unit root, real dividends are trend stationary. Journal: Econometric Reviews Pages: 149-166 Issue: 2 Volume: 23 Year: 2004 Keywords: Panel data, Unit roots, Fixed effects, Central limit theorem, Score vector, Real dividends, Stock prices, X-DOI: 10.1081/ETC-120039607 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-120039607 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:23:y:2004:i:2:p:149-166 Template-Type: ReDIF-Article 1.0 Author-Name: Markus Frolich Author-X-Name-First: Markus Author-X-Name-Last: Frolich Title: A Note on the Role of the Propensity Score for Estimating Average Treatment Effects Abstract: Hahn [Hahn, J. (1998). On the role of the propensity score in efficient semiparametric estimation of average treatment effects. Econometrica 66:315-331] derived the semiparametric efficiency bounds for estimating the average treatment effect (ATE) and the average treatment effect on the treated (ATET). The variance of ATET depends on whether the propensity score is known or unknown. Hahn attributes this to “dimension reduction.” In this paper, an alternative explanation is given: Knowledge of the propensity score improves upon the estimation of the distribution of the confounding variables. Journal: Econometric Reviews Pages: 167-174 Issue: 2 Volume: 23 Year: 2004 Keywords: Evaluation, Matching, Causal effect, Semiparametric efficiency bound, X-DOI: 10.1081/ETC-120039608 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-120039608 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:23:y:2004:i:2:p:167-174 Template-Type: ReDIF-Article 1.0 Author-Name: George Christodoulakis Author-X-Name-First: George Author-X-Name-Last: Christodoulakis Author-Name: Stephen Satchell Author-X-Name-First: Stephen Author-X-Name-Last: Satchell Title: Forecast Evaluation in the Presence of Unobserved Volatility Abstract: A number of volatility forecasting studies have led to the perception that the ARCH- and Stochastic Volatility-type models provide poor out-of-sample forecasts of volatility. This is primarily based on the use of traditional forecast evaluation criteria concerning the accuracy and the unbiasedness of forecasts. In this paper we provide an analytical assessment of volatility forecasting performance. We use the volatility and log volatility framework to prove how the inherent noise in the approximation of the true- and unobservable-volatility by the squared return, results in a misleading forecast evaluation, inflating the observed mean squared forecast error and invalidating the Diebold-Mariano statistic. We analytically characterize this noise and explicitly quantify its effects assuming normal errors. We extend our results using more general error structures such as the Compound Normal and the Gram-Charlier classes of distributions. We argue that evaluation problems are likely to be exacerbated by non-normality of the shocks and that non-linear and utility-based criteria can be more suitable for the evaluation of volatility forecasts. Journal: Econometric Reviews Pages: 175-198 Issue: 3 Volume: 23 Year: 2005 Keywords: Compound normal, Expected utility, Forecasting, Gram-Charlier, Mean squared error, Non-normality, Simulation, Stochastic volatility, X-DOI: 10.1081/ETC-200028199 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-200028199 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:23:y:2005:i:3:p:175-198 Template-Type: ReDIF-Article 1.0 Author-Name: Peter Egger Author-X-Name-First: Peter Author-X-Name-Last: Egger Author-Name: Michael Pfaffermayr Author-X-Name-First: Michael Author-X-Name-Last: Pfaffermayr Title: Estimating Long and Short Run Effects in Static Panel Models Abstract: This paper assesses the biases of four different estimators with respect to the short run and the long run parameters if a static panel model is used, although the data generating process is a dynamic error components model. We analytically derive the associated biases and provide a discussion of the determinants thereof. Our analytical and numerical results as well as Monte Carlo simulations illustrate that the asymptotic bias of both the within and the between parameter with respect to the short run and long run impact can be substantial, depending on the memory of the data generating process, the length of the time series and the importance of the cross-sectional variation in the explanatory variables. Journal: Econometric Reviews Pages: 199-214 Issue: 3 Volume: 23 Year: 2005 Keywords: Short run effects, Long run effects, Small sample bias, Panel econometrics, X-DOI: 10.1081/ETC-200028201 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-200028201 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:23:y:2005:i:3:p:199-214 Template-Type: ReDIF-Article 1.0 Author-Name: Manuel Dominguez Author-X-Name-First: Manuel Author-X-Name-Last: Dominguez Title: On the Power of Bootstrapped Specification Tests Abstract: Decisions based on econometric model estimates may not have the expected effect if the model is misspecified. Thus, specification tests should precede any analysis. Bierens' specification test is consistent and has optimality properties against some local alternatives. A shortcoming is that the test statistic is not distribution free, even asymptotically. This makes the test unfeasible. There have been many suggestions to circumvent this problem, including the use of upper bounds for the critical values. However, these suggestions lead to tests that lose power and optimality against local alternatives. In this paper we show that bootstrap methods allow us to recover power and optimality of Bierens' original test. Bootstrap also provides reliable p-values, which have a central role in Fisher's theory of hypothesis testing. The paper also includes a discussion of the properties of the bootstrap Nonlinear Least Squares Estimator under local alternatives. Journal: Econometric Reviews Pages: 215-228 Issue: 3 Volume: 23 Year: 2005 Keywords: Regression model, Local alternative, Specification test, Stochastic process, Wild bootstrap, X-DOI: 10.1081/ETC-200028205 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-200028205 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:23:y:2005:i:3:p:215-228 Template-Type: ReDIF-Article 1.0 Author-Name: Douglas Hodgson Author-X-Name-First: Douglas Author-X-Name-Last: Hodgson Title: Semiparametric Efficient Estimation of the Mean of a Time Series in the Presence of Conditional Heterogeneity of Unknown Form Abstract: We obtain semiparametric efficiency bounds for estimation of a location parameter in a time series model where the innovations are stationary and ergodic conditionally symmetric martingale differences but otherwise possess general dependence and distributions of unknown form. We then describe an iterative estimator that achieves this bound when the conditional density functions of the sample are known. Finally, we develop a “semi-adaptive” estimator that achieves the bound when these densities are unknown by the investigator. This estimator employs nonparametric kernel estimates of the densities. Monte Carlo results are reported. Journal: Econometric Reviews Pages: 229-257 Issue: 3 Volume: 23 Year: 2005 Keywords: Semiparametric efficiency bounds, Conditional heteroskedasticity, Time series, X-DOI: 10.1081/ETC-200028211 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-200028211 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:23:y:2005:i:3:p:229-257 Template-Type: ReDIF-Article 1.0 Author-Name: Giuseppe Cavaliere Author-X-Name-First: Giuseppe Author-X-Name-Last: Cavaliere Title: Unit Root Tests under Time-Varying Variances Abstract: The paper provides a general framework for investigating the effects of permanent changes in the variance of the errors of an autoregressive process on unit root tests. Such a framework - which is based on a novel asymptotic theory for integrated and near integrated processes with heteroskedastic errors - allows to evaluate how the variance dynamics affect the size and the power function of unit root tests. Contrary to previous studies, it is shown that non-constant variances can both inflate and deflate the rejection frequency of the commonly used unit root tests, both under the null and under the alternative, with early negative and late positive variance changes having the strongest impact on size and power. It is also shown that shifts smoothed across the sample have smaller impacts than shifts occurring as a single abrupt jump, while periodic variances have a negligible effect even when a small number of cycles take place over a given sample. Finally, it is proved that the locally best invariant (LBI) test of a unit root against level stationarity is robust to heteroskedasticity of any form under the null hypothesis. Journal: Econometric Reviews Pages: 259-292 Issue: 3 Volume: 23 Year: 2005 Keywords: Unit root tests, Integrated processes, Structural breaks, Heteroskedasticity, X-DOI: 10.1081/ETC-200028215 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-200028215 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:23:y:2005:i:3:p:259-292 Template-Type: ReDIF-Article 1.0 Author-Name: Hyungsik Roger Moon Author-X-Name-First: Hyungsik Roger Author-X-Name-Last: Moon Author-Name: Benoit Perron Author-X-Name-First: Benoit Author-X-Name-Last: Perron Title: Efficient Estimation of the Seemingly Unrelated Regression Cointegration Model and Testing for Purchasing Power Parity Abstract: This paper studies the efficient estimation of seemingly unrelated linear models with integrated regressors and stationary errors. We consider two cases. The first one has no common regressor among the equations. In this case, we show that by adding leads and lags of the first differences of the regressors and estimating this augmented dynamic regression model by generalized least squares using the long-run covariance matrix, we obtain an efficient estimator of the cointegrating vector that has a limiting mixed normal distribution. In the second case we consider, there is a common regressor to all equations, and we discuss efficient minimum distance estimation in this context. Simulation results suggests that our new estimator compares favorably with others already proposed in the literature. We apply these new estimators to the testing of the proportionality and symmetry conditions implied by purchasing power parity (PPP) among the G-7 countries. The tests based on the efficient estimates easily reject the joint hypotheses of proportionality and symmetry for all countries with either the United States or Germany as numeraire. Based on individual tests, our results suggest that Canada and Germany are the most likely countries for which the proportionality condition holds, and that Italy and Japan for the symmetry condition relative to the United States. Journal: Econometric Reviews Pages: 293-323 Issue: 4 Volume: 23 Year: 2005 Keywords: Seemingly unrelated regressions, Efficient estimation, Purchasing power parity, Minimum distance, X-DOI: 10.1081/ETC-200040777 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-200040777 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:23:y:2005:i:4:p:293-323 Template-Type: ReDIF-Article 1.0 Author-Name: L. G. Godfrey Author-X-Name-First: L. G. Author-X-Name-Last: Godfrey Author-Name: J. M. C. Santos Silva Author-X-Name-First: J. M. C. Santos Author-X-Name-Last: Silva Title: Bootstrap Tests of Nonnested Hypotheses: Some Further Results Abstract: Nonnested models are sometimes tested using a simulated reference distribution for the uncentred log likelihood ratio statistic. This approach has been recommended for the specific problem of testing linear and logarithmic regression models. The general asymptotic validity of the reference distribution test under correct choice of error distributions is questioned. The asymptotic behaviour of the test under incorrect assumptions about error distributions is also examined. In order to complement these analyses, Monte Carlo results for the case of linear and logarithmic regression models are provided. The finite sample properties of several standard tests for testing these alternative functional forms are also studied, under normal and nonnormal error distributions. These regression-based variable-addition tests are implemented using asymptotic and bootstrap critical values. Journal: Econometric Reviews Pages: 325-340 Issue: 4 Volume: 23 Year: 2005 Keywords: Bootstrap, Nonnested hypotheses, Nonnormality, X-DOI: 10.1081/ETC-200040780 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-200040780 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:23:y:2005:i:4:p:325-340 Template-Type: ReDIF-Article 1.0 Author-Name: Gianna Boero Author-X-Name-First: Gianna Author-X-Name-Last: Boero Author-Name: Jeremy Smith Author-X-Name-First: Jeremy Author-X-Name-Last: Smith Author-Name: Kenneth Wallis Author-X-Name-First: Kenneth Author-X-Name-Last: Wallis Title: The Sensitivity of Chi-Squared Goodness-of-Fit Tests to the Partitioning of Data Abstract: The power of Pearson's overall goodness-of-fit test and the components-of-chi-squared or “Pearson analog” tests of Anderson [Anderson, G. (1994). Simple tests of distributional form. J. Econometrics 62:265-276] to detect rejections due to shifts in location, scale, skewness and kurtosis is studied, as the number and position of the partition points is varied. Simulations are conducted for small and moderate sample sizes. It is found that smaller numbers of classes than are used in practice may be appropriate, and that the choice of non-equiprobable classes can result in substantial gains in power. Journal: Econometric Reviews Pages: 341-370 Issue: 4 Volume: 23 Year: 2005 Keywords: Pearson's goodness-of-fit test, Component tests, Monte Carlo, Number of classes, Partitions, X-DOI: 10.1081/ETC-200040782 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-200040782 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:23:y:2005:i:4:p:341-370 Template-Type: ReDIF-Article 1.0 Author-Name: Atsushi Inoue Author-X-Name-First: Atsushi Author-X-Name-Last: Inoue Author-Name: Lutz Kilian Author-X-Name-First: Lutz Author-X-Name-Last: Kilian Title: In-Sample or Out-of-Sample Tests of Predictability: Which One Should We Use? Abstract: It is widely known that significant in-sample evidence of predictability does not guarantee significant out-of-sample predictability. This is often interpreted as an indication that in-sample evidence is likely to be spurious and should be discounted. In this paper, we question this interpretation. Our analysis shows that neither data mining nor dynamic misspecification of the model under the null nor unmodelled structural change under the null are plausible explanations of the observed tendency of in-sample tests to reject the no-predictability null more often than out-of-sample tests. We provide an alternative explanation based on the higher power of in-sample tests of predictability in many situations. We conclude that results of in-sample tests of predictability will typically be more credible than results of out-of-sample tests. Journal: Econometric Reviews Pages: 371-402 Issue: 4 Volume: 23 Year: 2005 Keywords: Predictive ability, Spurious inference, Data mining, Model instability, X-DOI: 10.1081/ETC-200040785 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-200040785 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:23:y:2005:i:4:p:371-402 Template-Type: ReDIF-Article 1.0 Author-Name: Stephen Bond Author-X-Name-First: Stephen Author-X-Name-Last: Bond Author-Name: Frank Windmeijer Author-X-Name-First: Frank Author-X-Name-Last: Windmeijer Title: RELIABLE INFERENCE FOR GMM ESTIMATORS? FINITE SAMPLE PROPERTIES OF ALTERNATIVE TEST PROCEDURES IN LINEAR PANEL DATA MODELS Abstract: We compare the finite sample performance of a range of tests of linear restrictions for linear panel data models estimated using the generalized method of moments (GMM). These include standard asymptotic Wald tests based on one-step and two-step GMM estimators; two bootstrapped versions of these Wald tests; a version of the two-step Wald test that uses a finite sample corrected estimate of the variance of the two-step GMM estimator; the LM test; and three criterion-based tests that have recently been proposed. We consider both the AR(1) panel model and a design with predetermined regressors. The corrected two-step Wald test performs similarly to the standard one-step Wald test, whilst the bootstrapped one-step Wald test, the LM test, and a simple criterion-difference test can provide more reliable finite sample inference in some cases. Journal: Econometric Reviews Pages: 1-37 Issue: 1 Volume: 24 Year: 2005 Keywords: Finite sample inference, Generalized method of moments, Hypothesis testing, X-DOI: 10.1081/ETC-200049126 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-200049126 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:24:y:2005:i:1:p:1-37 Template-Type: ReDIF-Article 1.0 Author-Name: Badi Baltagi Author-X-Name-First: Badi Author-X-Name-Last: Baltagi Author-Name: Georges Bresson Author-X-Name-First: Georges Author-X-Name-Last: Bresson Author-Name: Alain Pirotte Author-X-Name-First: Alain Author-X-Name-Last: Pirotte Title: ADAPTIVE ESTIMATION OF HETEROSKEDASTIC ERROR COMPONENT MODELS Abstract: This paper checks the sensitivity of two adaptive heteroskedastic estimators suggested by Li and Stengos (1994) and Roy (2002) for an error component regression model to misspecification of the form of heteroskedasticity. In particular, we run Monte Carlo experiments using the heteroskedasticity setup by Li and Stengos (1994) to see how the misspecified Roy (2002) estimator performs. Next, we use the heteroskedasticity setup by Roy (2002) to see how the misspecified Li and Stengos (1994) estimator performs. We also check the sensitivity of these results to the choice of the smoothing parameters, the sample size, and the degree of heteroskedasticity. We find that the Li and Stengos (1994) estimator performs better under this type of misspecification than the corresponding estimator of Roy (2002). However, the former estimator is sensitive to the choice of the bandwidth. Journal: Econometric Reviews Pages: 39-58 Issue: 1 Volume: 24 Year: 2005 Keywords: Adaptive estimation, Bandwidth, Error components, Heteroskedasticity, Panel data, X-DOI: 10.1081/ETC-200049131 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-200049131 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:24:y:2005:i:1:p:39-58 Template-Type: ReDIF-Article 1.0 Author-Name: Nikolay Gospodinov Author-X-Name-First: Nikolay Author-X-Name-Last: Gospodinov Title: ROBUST ASYMPTOTIC INFERENCE IN AUTOREGRESSIVE MODELS WITH MARTINGALE DIFFERENCE ERRORS Abstract: This paper proposes a GMM-based method for asymptotic confidence interval construction in stationary autoregressive models, which is robust to the presence of conditional heteroskedasticity of unknown form. The confidence regions are obtained by inverting the asymptotic acceptance region of the distance metric test for the continuously updated GMM (CU-GMM) estimator. Unlike the predetermined symmetric shape of the Wald confidence intervals, the shape of the proposed confidence intervals is data-driven owing an estimated sequence of nonuniform weights. It appears that the flexibility of the CU-GMM estimator in downweighting certain observations proves advantageous for confidence interval construction. This stands in contrast to some other generalized empirical likelihood estimators with appealing optimality properties such as the empirical likelihood estimator whose objective function prevents such downweighting. A Monte Carlo simulation study illustrates the excellent small-sample properties of the method for AR models with ARCH errors. The procedure is applied to study the dynamics of the federal funds rate. Journal: Econometric Reviews Pages: 59-81 Issue: 1 Volume: 24 Year: 2005 Keywords: Conditional heteroskedasticity, Confidence intervals, Generalized empirical likelihood, GMM, Test inversion, X-DOI: 10.1081/ETC-200049135 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-200049135 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:24:y:2005:i:1:p:59-81 Template-Type: ReDIF-Article 1.0 Author-Name: Artur C. B. da Silva Lopes Author-X-Name-First: Artur C. B. da Silva Author-X-Name-Last: Lopes Author-Name: Antonio Montanes Author-X-Name-First: Antonio Author-X-Name-Last: Montanes Title: THE BEHAVIOR OF HEGY TESTS FOR QUARTERLY TIME SERIES WITH SEASONAL MEAN SHIFTS Abstract: This paper studies the behavior of the HEGY statistics for quarterly data, for seasonal autoregressive unit roots, when the analyzed time series is deterministic seasonal stationary but exhibits a change in the seasonal pattern. We analyze also the HEGY test for the nonseasonal unit root. the data generation process being trend stationary too. Our results show that when the break magnitudes are finite, the HEGY test statistics are not asymptotically biased toward the nonrejection of the seasonal and nonseasonal unit root hypotheses. However, the finite sample power properties may be substantially affected, the behavior of the tests depending on the type of the break. Journal: Econometric Reviews Pages: 83-108 Issue: 1 Volume: 24 Year: 2005 Keywords: HEGY tests, Seasonality, Structural breaks, Unit roots, X-DOI: 10.1081/ECR-200049141 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ECR-200049141 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:24:y:2005:i:1:p:83-108 Template-Type: ReDIF-Article 1.0 Author-Name: Sourafel Girma Author-X-Name-First: Sourafel Author-X-Name-Last: Girma Title: Book Review: Panel Data Econometrics Abstract: Journal: Econometric Reviews Pages: 109-111 Issue: 1 Volume: 24 Year: 2005 X-DOI: 10.1081/ETC-200049145 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-200049145 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:24:y:2005:i:1:p:109-111 Template-Type: ReDIF-Article 1.0 Author-Name: Dominique Guegan Author-X-Name-First: Dominique Author-X-Name-Last: Guegan Title: How can we Define the Concept of Long Memory? An Econometric Survey Abstract: In this paper we discuss different aspects of long memory behavior and applicable parametric models. We discuss the confusion that can arise when the empirical autocorrelation function decreases in a hyperbolic way. Journal: Econometric Reviews Pages: 113-149 Issue: 2 Volume: 24 Year: 2005 Keywords: Estimation theory, Long memory, Returns, Spectral domain, Switching, X-DOI: 10.1081/ETC-200067887 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-200067887 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:24:y:2005:i:2:p:113-149 Template-Type: ReDIF-Article 1.0 Author-Name: Jorg Breitung Author-X-Name-First: Jorg Author-X-Name-Last: Breitung Title: A Parametric approach to the Estimation of Cointegration Vectors in Panel Data Abstract: In this article, a parametric framework for estimation and inference in cointegrated panel data models is considered that is based on a cointegrated VAR(p) model. A convenient two-step estimator is suggested where, in the first step, all individual specific parameters are estimated, and in the second step, the long-run parameters are estimated from a pooled least-squares regression. The two-step estimator and related test procedures can easily be modified to account for contemporaneously correlated errors, a feature that is often encountered in multi-country studies. Monte Carlo simulations suggest that the two-step estimator and related test procedures outperform semiparametric alternatives such as the fully modified OLS approach, especially if the number of time periods is small. Journal: Econometric Reviews Pages: 151-173 Issue: 2 Volume: 24 Year: 2005 Keywords: Cointegrated systems, Estimation, Inference, Panel data, X-DOI: 10.1081/ETC-200067895 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-200067895 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:24:y:2005:i:2:p:151-173 Template-Type: ReDIF-Article 1.0 Author-Name: Myoung-Jae Lee Author-X-Name-First: Myoung-Jae Author-X-Name-Last: Lee Title: Monotonicity Conditions and Inequality Imputation for Sample-Selection and Non-Response Problems Abstract: Under a sample selection or non-response problem, where a response variable y is observed only when a condition δ = 1 is met, the identified mean E(y&7Cδ = 1) is not equal to the desired mean E(y). But the monotonicity condition E(y&7Cδ = 1) ≤ E(y&7Cδ =  0) yields an informative bound E(y&7Cδ = 1) ≤ E(y), which is enough for certain inferences. For example, in a majority voting with δ being the vote-turnout, it is enough to know if E(y) > 0.5 or not, for which E(y&7Cδ = 1) > 0.5 is sufficient under the monotonicity. The main question is then whether the monotonicity condition is testable, and if not, when it is plausible. Answering to these queries, when there is a 'proxy' variable z related to y but fully observed, we provide a test for the monotonicity; when z is not available, we provide primitive conditions and plausible models for the monotonicity. Going further, when both y and z are binary, bivariate monotonicities of the type P(y, z&7Cδ = 1) ≤ P(y, z&7Cδ = 0) are considered, which can lead to sharper bounds for P(y). As an empirical example, a data set on the 1996 U.S. presidential election is analyzed to see if the Republican candidate could have won had everybody voted, i.e., to see if P(y) > 0.5, where y = 1 is voting for the Republican candidate. Journal: Econometric Reviews Pages: 175-194 Issue: 2 Volume: 24 Year: 2005 Keywords: Imputation, Monotonicity, Non-response, Orthant dependence, Sample selection, X-DOI: 10.1081/ETC-200067910 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-200067910 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:24:y:2005:i:2:p:175-194 Template-Type: ReDIF-Article 1.0 Author-Name: Wendelin Schnedler Author-X-Name-First: Wendelin Author-X-Name-Last: Schnedler Title: Likelihood Estimation for Censored Random Vectors Abstract: This article shows how to construct a likelihood for a general class of censoring problems. This likelihood is proven to be valid, i.e. its maximizer is consistent and the respective root-n estimator is asymptotically efficient and normally distributed under regularity conditions. The method generalizes ordinary maximum likelihood estimation as well as several standard estimators for censoring problems (e.g. tobit type I-tobit type V). Journal: Econometric Reviews Pages: 195-217 Issue: 2 Volume: 24 Year: 2005 Keywords: Censored variables, Likelihood, Limited dependent variables, Multivariate methods, Random censoring, X-DOI: 10.1081/ETC-200067925 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-200067925 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:24:y:2005:i:2:p:195-217 Template-Type: ReDIF-Article 1.0 Author-Name: Emmanuel Flachaire Author-X-Name-First: Emmanuel Author-X-Name-Last: Flachaire Title: More Efficient Tests Robust to Heteroskedasticity of Unknown Form Abstract: In the presence of heteroskedasticity of unknown form, the Ordinary Least Squares parameter estimator becomes inefficient, and its covariance matrix estimator inconsistent. Eicker (1963) and White (1980) were the first to propose a robust consistent covariance matrix estimator, that permits asymptotically correct inference. This estimator is widely used in practice. Cragg (1983) proposed a more efficient estimator, but concluded that tests basd on it are unreliable. Thus, this last estimator has not been used in practice. This article is concerned with finite sample properties of tests robust to heteroskedasticity of unknown form. Our results suggest that reliable and more efficient tests can be obtained with the Cragg estimators in small samples. Journal: Econometric Reviews Pages: 219-241 Issue: 2 Volume: 24 Year: 2005 Keywords: Heteroskedasticity-robust test, Regression model, Wild bootstrap, X-DOI: 10.1081/ETC-200067942 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-200067942 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:24:y:2005:i:2:p:219-241 Template-Type: ReDIF-Article 1.0 Author-Name: Scott Atkinson Author-X-Name-First: Scott Author-X-Name-Last: Atkinson Title: A Review of: “Stochastic Frontier Analysis” Abstract: Journal: Econometric Reviews Pages: 243-245 Issue: 2 Volume: 24 Year: 2005 X-DOI: 10.1081/ETC-200067955 File-URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-200067955 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:24:y:2005:i:2:p:243-245 Template-Type: ReDIF-Article 1.0 Author-Name: Patrik Guggenberger Author-X-Name-First: Patrik Author-X-Name-Last: Guggenberger Author-Name: Jinyong Hahn Author-X-Name-First: Jinyong Author-X-Name-Last: Hahn Title: Finite Sample Properties of the Two-Step Empirical Likelihood Estimator Abstract: We investigate the finite sample properties of two-step empirical likelihood (EL) estimators. These estimators are shown to have the same third-order bias properties as EL itself. The Monte Carlo study provides evidence that (i) higher order asymptotics fails to provide a good approximation in the sense that the bias of the two-step EL estimators can be substantial and sensitive to the number of moment restrictions and (ii) the two-step EL estimators may have heavy tails. Journal: Econometric Reviews Pages: 247-263 Issue: 3 Volume: 24 Year: 2005 Keywords: Empirical likelihood estimator, Finite sample performance, High order bias, Two-step empirical likelihood estimator, X-DOI: 10.1080/07474930500242987 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930500242987 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:24:y:2005:i:3:p:247-263 Template-Type: ReDIF-Article 1.0 Author-Name: Evzen Kocenda Author-X-Name-First: Evzen Author-X-Name-Last: Kocenda Author-Name: Lubos Briatka Author-X-Name-First: Lubos Author-X-Name-Last: Briatka Title: Optimal Range for the iid Test Based on Integration Across the Correlation Integral Abstract: This paper builds on Kocenda (2001) and extends it in three ways. First, new intervals of the proximity parameter ε (over which the correlation integral is calculated) are specified. For these ε-ranges new critical values for various lengths of the data sets are introduced, and through Monte Carlo studies it is shown that within new ε-ranges the test is even more powerful than within the original ε-range. The range that maximizes the power of the test is suggested as the optimal range. Second, an extensive comparison with existing results of the controlled competition of Barnett et al. (1997) as well as broad power tests on various nonlinear and chaotic data are provided. Test performance with real (exchange rate) data is provided as well. The results of the comparison strongly favor our robust procedure and confirm the ability of the test in finding nonlinear dependencies as well its function as a specification test. Finally, new user-friendly and fast software is introduced. Journal: Econometric Reviews Pages: 265-296 Issue: 3 Volume: 24 Year: 2005 Keywords: Chaos, Correlation integral, High-frequency economic and financial data, Monte Carlo, Nonlinear dynamics, Power tests, Single-blind competition, X-DOI: 10.1080/07474930500243001 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930500243001 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:24:y:2005:i:3:p:265-296 Template-Type: ReDIF-Article 1.0 Author-Name: Joakim Westerlund Author-X-Name-First: Joakim Author-X-Name-Last: Westerlund Title: New Simple Tests for Panel Cointegration Abstract: In this paper, two new simple residual-based panel data tests are proposed for the null of no cointegration. The tests are simple because they do not require any correction for the temporal dependencies of the data. Yet they are able to accommodate individual specific short-run dynamics, individual specific intercept and trend terms, and individual specific slope parameters. The limiting distributions of the tests are derived and are shown to be free of nuisance parameters. The Monte Carlo results in this paper suggest that the asymptotic results are borne out well even in very small samples. Journal: Econometric Reviews Pages: 297-316 Issue: 3 Volume: 24 Year: 2005 Keywords: Monte Carlo simulation, Panel cointegration, Residual-based tests, X-DOI: 10.1080/07474930500243019 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930500243019 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:24:y:2005:i:3:p:297-316 Template-Type: ReDIF-Article 1.0 Author-Name: Manabu Asai Author-X-Name-First: Manabu Author-X-Name-Last: Asai Author-Name: Michael McAleer Author-X-Name-First: Michael Author-X-Name-Last: McAleer Title: Dynamic Asymmetric Leverage in Stochastic Volatility Models Abstract: In the class of stochastic volatility (SV) models, leverage effects are typically specified through the direct correlation between the innovations in both returns and volatility, resulting in the dynamic leverage (DL) model. Recently, two asymmetric SV models based on threshold effects have been proposed in the literature. As such models consider only the sign of the previous return and neglect its magnitude, this paper proposes a dynamic asymmetric leverage (DAL) model that accommodates the direct correlation as well as the sign and magnitude of the threshold effects. A special case of the DAL model with zero direct correlation between the innovations is the asymmetric leverage (AL) model. The dynamic asymmetric leverage models are estimated by the Monte Carlo likelihood (MCL) method. Monte Carlo experiments are presented to examine the finite sample properties of the estimator. For a sample size of T = 2000 with 500 replications, the sample means, standard deviations, and root mean squared errors of the MCL estimators indicate only a small finite sample bias. The empirical estimates for S&P 500 and TOPIX financial returns, and USD/AUD and YEN/USD exchange rates, indicate that the DAL class, including the DL and AL models, is generally superior to threshold SV models with respect to AIC and BIC, with AL typically providing the best fit to the data. Journal: Econometric Reviews Pages: 317-332 Issue: 3 Volume: 24 Year: 2005 Keywords: Asymmetric effects, Monte Carlo likelihood, Stochastic volatility, Threshold effects, X-DOI: 10.1080/07474930500243035 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930500243035 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:24:y:2005:i:3:p:317-332 Template-Type: ReDIF-Article 1.0 Author-Name: Esfandiar Maasoumi Author-X-Name-First: Esfandiar Author-X-Name-Last: Maasoumi Author-Name: Daniel Millimet Author-X-Name-First: Daniel Author-X-Name-Last: Millimet Author-Name: Vasudha Rangaprasad Author-X-Name-First: Vasudha Author-X-Name-Last: Rangaprasad Title: Class Size and Educational Policy: Who Benefits from Smaller Classes? Abstract: The impact of class size on student achievement remains an open question despite hundreds of empirical studies and the perception among parents, teachers, and policymakers that larger classes are a significant detriment to student development. This study sheds new light on this ambiguity by utilizing nonparametric tests for stochastic dominance to analyze unconditional and conditional test score distributions across students facing different class sizes. Analyzing the conditional distributions of test scores (purged of observables using class-size specific returns), we find that there is little causal effect of marginal reductions in class size on test scores within the range of 20 or more students. However, reductions in class size from above 20 students to below 20 students, as well as marginal reductions in classes with fewer than 20 students, increase test scores for students below the median, but decrease test scores above the median. This nonuniform impact of class size suggests that compensatory school policies, whereby lower-performing students are placed in smaller classes and higher-performing students are placed in larger classes, improves the academic achievement of not just the lower-performing students but also the higher-performing students. Journal: Econometric Reviews Pages: 333-368 Issue: 4 Volume: 24 Year: 2005 Keywords: Class size, Program evaluation, Quantile treatment effects, School quality: Stochastic dominance, Student achievement, X-DOI: 10.1080/07474930500405485 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930500405485 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:24:y:2005:i:4:p:333-368 Template-Type: ReDIF-Article 1.0 Author-Name: Todd Clark Author-X-Name-First: Todd Author-X-Name-Last: Clark Author-Name: Michael McCracken Author-X-Name-First: Michael Author-X-Name-Last: McCracken Title: Evaluating Direct Multistep Forecasts Abstract: This paper examines the asymptotic and finite-sample properties of tests of equal forecast accuracy and encompassing applied to direct, multistep predictions from nested regression models. We first derive asymptotic distributions; these nonstandard distributions depend on the parameters of the data-generating process. We then use Monte Carlo simulations to examine finite-sample size and power. Our asymptotic approximation yields good size and power properties for some, but not all, of the tests; a bootstrap works reasonably well for all tests. The paper concludes with a reexamination of the predictive content of capacity utilization for inflation. Journal: Econometric Reviews Pages: 369-404 Issue: 4 Volume: 24 Year: 2005 Keywords: Causality, Long horizon, Prediction, X-DOI: 10.1080/07474930500405683 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930500405683 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:24:y:2005:i:4:p:369-404 Template-Type: ReDIF-Article 1.0 Author-Name: Morten Ørregaard Nielsen Author-X-Name-First: Morten Ørregaard Author-X-Name-Last: Nielsen Author-Name: Per Houmann Frederiksen Author-X-Name-First: Per Houmann Author-X-Name-Last: Frederiksen Title: Finite Sample Comparison of Parametric, Semiparametric, and Wavelet Estimators of Fractional Integration Abstract: In this paper we compare through Monte Carlo simulations the finite sample properties of estimators of the fractional differencing parameter, d. This involves frequency domain, time domain, and wavelet based approaches, and we consider both parametric and semiparametric estimation methods. The estimators are briefly introduced and compared, and the criteria adopted for measuring finite sample performance are bias and root mean squared error. Most importantly, the simulations reveal that (1) the frequency domain maximum likelihood procedure is superior to the time domain parametric methods, (2) all the estimators are fairly robust to conditionally heteroscedastic errors, (3) the local polynomial Whittle and bias-reduced log-periodogram regression estimators are shown to be more robust to short-run dynamics than other semiparametric (frequency domain and wavelet) estimators and in some cases even outperform the time domain parametric methods, and (4) without sufficient trimming of scales the wavelet-based estimators are heavily biased. Journal: Econometric Reviews Pages: 405-443 Issue: 4 Volume: 24 Year: 2005 Keywords: Bias, Finite sample distribution, Fractional integration, Maximum likelihood, Monte Carlo simulation, Parametric estimation, Semiparametric estimation, Wavelet, X-DOI: 10.1080/07474930500405790 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930500405790 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:24:y:2005:i:4:p:405-443 Template-Type: ReDIF-Article 1.0 Author-Name: Achim Zeileis Author-X-Name-First: Achim Author-X-Name-Last: Zeileis Title: A Unified Approach to Structural Change Tests Based on ML Scores, F Statistics, and OLS Residuals Abstract: Three classes of structural change tests (or tests for parameter instability) that have been receiving much attention in both the statistics and the econometrics communities but have been developed in rather loosely connected lines of research are unified by embedding them into the framework of generalized M-fluctuation tests (Zeileis and Hornik, 2003). These classes are tests based on maximum likelihood scores (including the Nyblom-Hansen test), on F statistics (sup F, ave F, exp F tests), and on OLS residuals (OLS-based CUSUM and MOSUM tests). We show that (representatives from) these classes are special cases of the generalized M-fluctuation tests, based on the same functional central limit theorem but employing different functionals for capturing excessive fluctuations. After embedding these tests into the same framework and thus understanding the relationship between these procedures for testing in historical samples, it is shown how the tests can also be extended to a monitoring situation. This is achieved by establishing a general M-fluctuation monitoring procedure and then applying the different functionals corresponding to monitoring with ML scores, F statistics, and OLS residuals. In particular, an extension of the sup F test to a monitoring scenario is suggested and illustrated on a real-world data set. Journal: Econometric Reviews Pages: 445-466 Issue: 4 Volume: 24 Year: 2005 Keywords: Aggregation functional, Fluctuation test, Functional central limit theorem, Monitoring, Nyblom-Hansen test, OLS-based CUSUM test, Parameter instability, Structural change, sup <i>F</i> test, X-DOI: 10.1080/07474930500406053 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930500406053 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:24:y:2005:i:4:p:445-466 Template-Type: ReDIF-Article 1.0 Author-Name: Takashi Yamagata Author-X-Name-First: Takashi Author-X-Name-Last: Yamagata Author-Name: Chris Orme Author-X-Name-First: Chris Author-X-Name-Last: Orme Title: On Testing Sample Selection Bias Under the Multicollinearity Problem Abstract: This paper reviews and extends the literature on the finite sample behavior of tests for sample selection bias. Monte Carlo results show that, when the “multicollinearity problem” identified by Nawata (1993) is severe, (i) the t-test based on the Heckman-Greene variance estimator can be unreliable, (ii) the Likelihood Ratio test remains powerful, and (iii) nonnormality can be interpreted as severe sample selection bias by Maximum Likelihood methods, leading to negative Wald statistics. We also confirm previous findings (Leung and Yu, 1996) that the standard regression-based t-test (Heckman, 1979) and the asymptotically efficient Lagrange Multiplier test (Melino, 1982), are robust to nonnormality but have very little power. Journal: Econometric Reviews Pages: 467-481 Issue: 4 Volume: 24 Year: 2005 Keywords: Lagrange multiplier test, Likelihood ratio test, Sample selection bias, <i>t</i>-test, Wald test, X-DOI: 10.1080/02770900500406132 File-URL: http://www.tandfonline.com/doi/abs/10.1080/02770900500406132 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:24:y:2005:i:4:p:467-481 Template-Type: ReDIF-Article 1.0 Author-Name: Justin Tobias Author-X-Name-First: Justin Author-X-Name-Last: Tobias Title: Estimation, Learning and Parameters of Interest in a Multiple Outcome Selection Model Abstract: We describe estimation, learning, and prediction in a treatment-response model with two outcomes. The introduction of potential outcomes in this model introduces four cross-regime correlation parameters that are not contained in the likelihood for the observed data and thus are not identified. Despite this inescapable identification problem, we build upon the results of Koop and Poirier (1997) to describe how learning takes place about the four nonidentified correlations through the imposed positive definiteness of the covariance matrix. We then derive bivariate distributions associated with commonly estimated “treatment parameters” (including the Average Treatment Effect and effect of Treatment on the Treated), and use the learning that takes place about the nonidentified correlations to calculate these densities. We illustrate our points in several generated data experiments and apply our methods to estimate the joint impact of child labor on achievement scores in language and mathematics. Journal: Econometric Reviews Pages: 1-40 Issue: 1 Volume: 25 Year: 2006 Keywords: Bayesian econometrics, Treatment effects, X-DOI: 10.1080/07474930500545421 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930500545421 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:25:y:2006:i:1:p:1-40 Template-Type: ReDIF-Article 1.0 Author-Name: Pieter Omtzigt Author-X-Name-First: Pieter Author-X-Name-Last: Omtzigt Author-Name: Stefano Fachin Author-X-Name-First: Stefano Author-X-Name-Last: Fachin Title: The Size and Power of Bootstrap and Bartlett-Corrected Tests of Hypotheses on the Cointegrating Vectors Abstract: In this paper we compare Bartlett-corrected, bootstrap, and fast double bootstrap tests on maximum likelihood estimates of cointegration parameters. The key result is that both the bootstrap and the Bartlett-corrected tests must be based on the unrestricted estimates of the cointegrating vectors: procedures based on the restricted estimates have almost no power. The small sample size bias of the asymptotic test appears so severe as to advise strongly against its use with the sample sizes commonly available; the fast double bootstrap test minimizes size bias, while the Bartlett-corrected test is somehow more powerful. Journal: Econometric Reviews Pages: 41-60 Issue: 1 Volume: 25 Year: 2006 Keywords: Bartlett correction, Bootstrap, Cointegration, Fast double bootstrap, X-DOI: 10.1080/07474930500545439 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930500545439 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:25:y:2006:i:1:p:41-60 Template-Type: ReDIF-Article 1.0 Author-Name: Tommaso Proietti Author-X-Name-First: Tommaso Author-X-Name-Last: Proietti Title: Trend-Cycle Decompositions with Correlated Components Abstract: This paper raises some interpretative issues that arise from univariate trend-cycle decompositions with correlated disturbances. In particular, it discusses whether the interpretation of a negative correlation as providing evidence for the prominence of real, or supply, shocks, can be supported. For this purpose it determines the conditions under which correlated components may originate from the underestimation of the cyclical component in an orthogonal decomposition; from the presence of a growth rate cycle, rather than a deviation cycle; or alternatively, as a consequence of the hysteresis phenomenon. Finally, it considers interpreting correlated components in terms of permanent-transitory decompositions, where the permanent component has richer dynamics than a pure random walk. The consequences for smoothing and signal extraction are discussed: in particular, it is documented that a negative correlation implies that future observations carry most of the information needed to assess cyclical stance. As a result, the components will be subject to underestimation in real time and thus to high revisions. The overall conclusion is that the characterization of economic fluctuations in macroeconomic time series largely remains an open issue. Journal: Econometric Reviews Pages: 61-84 Issue: 1 Volume: 25 Year: 2006 Keywords: Hysteresis, Permanent-transitory decomposition, Revisions, Signal extraction, X-DOI: 10.1080/07474930500545496 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930500545496 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:25:y:2006:i:1:p:61-84 Template-Type: ReDIF-Article 1.0 Author-Name: Jaroslava Hlouskova Author-X-Name-First: Jaroslava Author-X-Name-Last: Hlouskova Author-Name: Martin Wagner Author-X-Name-First: Martin Author-X-Name-Last: Wagner Title: The Performance of Panel Unit Root and Stationarity Tests: Results from a Large Scale Simulation Study Abstract: This paper presents results on the size and power of first generation panel unit root and stationarity tests obtained from a large scale simulation study. The tests developed in the following papers are included: Levin et al. (2002), Harris and Tzavalis (1999), Breitung (2000), Im et al. (1997, 2003), Maddala and Wu (1999), Hadri (2000), and Hadri and Larsson (2005). Our simulation set-up is designed to address inter alia the following issues. First, we assess the performance as a function of the time and the cross-section dimensions. Second, we analyze the impact of serial correlation introduced by positive MA roots, known to have detrimental impact on time series unit root tests, on the performance. Third, we investigate the power of the panel unit root tests (and the size of the stationarity tests) for a variety of first order autoregressive coefficients. Fourth, we consider both of the two usual specifications of deterministic variables in the unit root literature. Journal: Econometric Reviews Pages: 85-116 Issue: 1 Volume: 25 Year: 2006 Keywords: Panel stationarity test, Panel unit root test, Power, Simulation study, Size, X-DOI: 10.1080/07474930500545504 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930500545504 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:25:y:2006:i:1:p:85-116 Template-Type: ReDIF-Article 1.0 Author-Name: Fernanda Peixe Author-X-Name-First: Fernanda Author-X-Name-Last: Peixe Author-Name: Alastair Hall Author-X-Name-First: Alastair Author-X-Name-Last: Hall Author-Name: Kostas Kyriakoulis Author-X-Name-First: Kostas Author-X-Name-Last: Kyriakoulis Title: The Mean Squared Error of the Instrumental Variables Estimator When the Disturbance Has an Elliptical Distribution Abstract: This paper generalizes Nagar's (1959) approximation to the finite sample mean squared error (MSE) of the instrumental variables (IV) estimator to the case in which the errors possess an elliptical distribution whose moments exist up to infinite order. This allows for types of excess kurtosis exhibited by some financial data series. This approximation is compared numerically to Knight's (1985) formulae for the exact moments of the IV estimator under nonnormality. We use the results to explore two questions on instrument selection. First, we complement Buse's (1992) analysis by considering the impact of additional instruments on both bias and MSE. Second, we evaluate the properties of Andrews's (1999) selection method in terms of the bias and MSE of the resulting IV estimator. Journal: Econometric Reviews Pages: 117-138 Issue: 1 Volume: 25 Year: 2006 X-DOI: 10.1080/07474930500545488 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930500545488 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:25:y:2006:i:1:p:117-138 Template-Type: ReDIF-Article 1.0 Author-Name: Esfandiar Maasoumi Author-X-Name-First: Esfandiar Author-X-Name-Last: Maasoumi Author-Name: Michael McAleer Author-X-Name-First: Michael Author-X-Name-Last: McAleer Title: Multivariate Stochastic Volatility: An Overview Abstract: Journal: Econometric Reviews Pages: 139-144 Issue: 2-3 Volume: 25 Year: 2006 X-DOI: 10.1080/07474930600712806 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930600712806 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:25:y:2006:i:2-3:p:139-144 Template-Type: ReDIF-Article 1.0 Author-Name: Manabu Asai Author-X-Name-First: Manabu Author-X-Name-Last: Asai Author-Name: Michael McAleer Author-X-Name-First: Michael Author-X-Name-Last: McAleer Author-Name: Jun Yu Author-X-Name-First: Jun Author-X-Name-Last: Yu Title: Multivariate Stochastic Volatility: A Review Abstract: The literature on multivariate stochastic volatility (MSV) models has developed significantly over the last few years. This paper reviews the substantial literature on specification, estimation, and evaluation of MSV models. A wide range of MSV models is presented according to various categories, namely, (i) asymmetric models, (ii) factor models, (iii) time-varying correlation models, and (iv) alternative MSV specifications, including models based on the matrix exponential transformation, the Cholesky decomposition, and the Wishart autoregressive process. Alternative methods of estimation, including quasi-maximum likelihood, simulated maximum likelihood, and Markov chain Monte Carlo methods, are discussed and compared. Various methods of diagnostic checking and model comparison are also reviewed. Journal: Econometric Reviews Pages: 145-175 Issue: 2-3 Volume: 25 Year: 2006 Keywords: Asymmetry, Diagnostic checking, Estimation, Factor models, Leverage, Model comparison, Multivariate stochastic volatility, Thresholds, Time-varying correlations, Transformations, X-DOI: 10.1080/07474930600713564 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930600713564 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:25:y:2006:i:2-3:p:145-175 Template-Type: ReDIF-Article 1.0 Author-Name: C. Gourieroux Author-X-Name-First: C. Author-X-Name-Last: Gourieroux Title: Continuous Time Wishart Process for Stochastic Risk Abstract: Risks are usually represented and measured by volatility-covolatility matrices. Wishart processes are models for a dynamic analysis of multivariate risk and describe the evolution of stochastic volatility-covolatility matrices, constrained to be symmetric positive definite. The autoregressive Wishart process (WAR) is the multivariate extension of the Cox, Ingersoll, Ross (CIR) process introduced for scalar stochastic volatility. As a CIR process it allows for closed-form solutions for a number of financial problems, such as term structure of T-bonds and corporate bonds, derivative pricing in a multivariate stochastic volatility model, and the structural model for credit risk. Moreover, the Wishart dynamics are very flexible and are serious competitors for less structural multivariate ARCH models. Journal: Econometric Reviews Pages: 177-217 Issue: 2-3 Volume: 25 Year: 2006 Keywords: JEL Number, G12, G13, X-DOI: 10.1080/07474930600713234 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930600713234 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:25:y:2006:i:2-3:p:177-217 Template-Type: ReDIF-Article 1.0 Author-Name: Charles Bos Author-X-Name-First: Charles Author-X-Name-Last: Bos Author-Name: Neil Shephard Author-X-Name-First: Neil Author-X-Name-Last: Shephard Title: Inference for Adaptive Time Series Models: Stochastic Volatility and Conditionally Gaussian State Space Form Abstract: In this paper we model the Gaussian errors in the standard Gaussian linear state space model as stochastic volatility processes. We show that conventional MCMC algorithms for this class of models are ineffective, but that the problem can be alleviated by reparameterizing the model. Instead of sampling the unobserved variance series directly, we sample in the space of the disturbances, which proves to lower correlation in the sampler and thus increases the quality of the Markov chain. Using our reparameterized MCMC sampler, it is possible to estimate an unobserved factor model for exchange rates between a group of n countries. The underlying n + 1 country-specific currency strength factors and the n + 1 currency volatility factors can be extracted using the new methodology. With the factors, a more detailed image of the events around the 1992 EMS crisis is obtained. We assess the fit of competitive models on the panels of exchange rates with an effective particle filter and find that indeed the factor model is strongly preferred by the data. Journal: Econometric Reviews Pages: 219-244 Issue: 2-3 Volume: 25 Year: 2006 Keywords: Markov chain Monte Carlo, Particle filter, State space form, Stochastic volatility, X-DOI: 10.1080/07474930600713275 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930600713275 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:25:y:2006:i:2-3:p:219-244 Template-Type: ReDIF-Article 1.0 Author-Name: David Chan Author-X-Name-First: David Author-X-Name-Last: Chan Author-Name: Robert Kohn Author-X-Name-First: Robert Author-X-Name-Last: Kohn Author-Name: Chris Kirby Author-X-Name-First: Chris Author-X-Name-Last: Kirby Title: Multivariate Stochastic Volatility Models with Correlated Errors Abstract: We develop a Bayesian approach for parsimoniously estimating the correlation structure of the errors in a multivariate stochastic volatility model. Since the number of parameters in the joint correlation matrix of the return and volatility errors is potentially very large, we impose a prior that allows the off-diagonal elements of the inverse of the correlation matrix to be identically zero. The model is estimated using a Markov chain simulation method that samples from the posterior distribution of the volatilities and parameters. We illustrate the approach using both simulated and real examples. In the real examples, the method is applied to equities at three levels of aggregation: returns for firms within the same industry, returns for different industries, and returns aggregated at the index level. We find pronounced correlation effects only at the highest level of aggregation. Journal: Econometric Reviews Pages: 245-274 Issue: 2-3 Volume: 25 Year: 2006 Keywords: Bayesian estimation, Correlation matrix, Leverage, Markov chain Monte Carlo, Model averaging, X-DOI: 10.1080/07474930600713309 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930600713309 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:25:y:2006:i:2-3:p:245-274 Template-Type: ReDIF-Article 1.0 Author-Name: Catherine Doz Author-X-Name-First: Catherine Author-X-Name-Last: Doz Author-Name: Eric Renault Author-X-Name-First: Eric Author-X-Name-Last: Renault Title: Factor Stochastic Volatility in Mean Models: A GMM Approach Abstract: This paper provides a semiparametric framework for modeling multivariate conditional heteroskedasticity. We put forward latent stochastic volatility (SV) factors as capturing the commonality in the joint conditional variance matrix of asset returns. This approach is in line with common features as studied by Engle and Kozicki (1993), and it allows us to focus on identication of factors and factor loadings through first- and second-order conditional moments only. We assume that the time-varying part of risk premiums is based on constant prices of factor risks, and we consider a factor SV in mean model. Additional specification of both expectations and volatility of future volatility of factors provides conditional moment restrictions, through which the parameters of the model are all identied. These conditional moment restrictions pave the way for instrumental variables estimation and GMM inference. Journal: Econometric Reviews Pages: 275-309 Issue: 2-3 Volume: 25 Year: 2006 Keywords: Asset pricing, Common features, Conditional factor models, Generalized method of moments, Multivariate conditional heteroskedasticity, Multiperiod conditional moment restrictions, Stochastic volatility, X-DOI: 10.1080/07474930600713325 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930600713325 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:25:y:2006:i:2-3:p:275-309 Template-Type: ReDIF-Article 1.0 Author-Name: Alexander Philipov Author-X-Name-First: Alexander Author-X-Name-Last: Philipov Author-Name: Mark Glickman Author-X-Name-First: Mark Author-X-Name-Last: Glickman Title: Factor Multivariate Stochastic Volatility via Wishart Processes Abstract: This paper proposes a high dimensional factor multivariate stochastic volatility (MSV) model in which factor covariance matrices are driven by Wishart random processes. The framework allows for unrestricted specification of intertemporal sensitivities, which can capture the persistence in volatilities, kurtosis in returns, and correlation breakdowns and contagion effects in volatilities. The factor structure allows addressing high dimensional setups used in portfolio analysis and risk management, as well as modeling conditional means and conditional variances within the model framework. Owing to the complexity of the model, we perform inference using Markov chain Monte Carlo simulation from the posterior distribution. A simulation study is carried out to demonstrate the efficiency of the estimation algorithm. We illustrate our model on a data set that includes 88 individual equity returns and the two Fama-French size and value factors. With this application, we demonstrate the ability of the model to address high dimensional applications suitable for asset allocation, risk management, and asset pricing. Journal: Econometric Reviews Pages: 311-334 Issue: 2-3 Volume: 25 Year: 2006 Keywords: Bayesian time series, Factor models, Stochastic covariance, Time-varying correlation, X-DOI: 10.1080/07474930600713366 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930600713366 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:25:y:2006:i:2-3:p:311-334 Template-Type: ReDIF-Article 1.0 Author-Name: Roman Liesenfeld Author-X-Name-First: Roman Author-X-Name-Last: Liesenfeld Author-Name: Jean-Francois Richard Author-X-Name-First: Jean-Francois Author-X-Name-Last: Richard Title: Classical and Bayesian Analysis of Univariate and Multivariate Stochastic Volatility Models Abstract: In this paper, efficient importance sampling (EIS) is used to perform a classical and Bayesian analysis of univariate and multivariate stochastic volatility (SV) models for financial return series. EIS provides a highly generic and very accurate procedure for the Monte Carlo (MC) evaluation of high-dimensional interdependent integrals. It can be used to carry out ML-estimation of SV models as well as simulation smoothing where the latent volatilities are sampled at once. Based on this EIS simulation smoother, a Bayesian Markov chain Monte Carlo (MCMC) posterior analysis of the parameters of SV models can be performed. Journal: Econometric Reviews Pages: 335-360 Issue: 2-3 Volume: 25 Year: 2006 Keywords: Dynamic latent variables, Markov chain Monte Carlo, Maximum likelihood, Simulation smoother, X-DOI: 10.1080/07474930600713424 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930600713424 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:25:y:2006:i:2-3:p:335-360 Template-Type: ReDIF-Article 1.0 Author-Name: Jun Yu Author-X-Name-First: Jun Author-X-Name-Last: Yu Author-Name: Renate Meyer Author-X-Name-First: Renate Author-X-Name-Last: Meyer Title: Multivariate Stochastic Volatility Models: Bayesian Estimation and Model Comparison Abstract: In this paper we show that fully likelihood-based estimation and comparison of multivariate stochastic volatility (SV) models can be easily performed via a freely available Bayesian software called WinBUGS. Moreover, we introduce to the literature several new specifications that are natural extensions to certain existing models, one of which allows for time-varying correlation coefficients. Ideas are illustrated by fitting, to a bivariate time series data of weekly exchange rates, nine multivariate SV models, including the specifications with Granger causality in volatility, time-varying correlations, heavy-tailed error distributions, additive factor structure, and multiplicative factor structure. Empirical results suggest that the best specifications are those that allow for time-varying correlation coefficients. Journal: Econometric Reviews Pages: 361-384 Issue: 2-3 Volume: 25 Year: 2006 Keywords: DIC, Factors, Granger causality in volatility, Heavy-tailed distributions, MCMC, Multivariate stochastic volatility, Time-varying correlations, X-DOI: 10.1080/07474930600713465 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930600713465 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:25:y:2006:i:2-3:p:361-384 Template-Type: ReDIF-Article 1.0 Author-Name: Borus Jungbacker Author-X-Name-First: Borus Author-X-Name-Last: Jungbacker Author-Name: Siem Jan Koopman Author-X-Name-First: Siem Jan Author-X-Name-Last: Koopman Title: Monte Carlo Likelihood Estimation for Three Multivariate Stochastic Volatility Models Abstract: Estimating parameters in a stochastic volatility (SV) model is a challenging task. Among other estimation methods and approaches, efficient simulation methods based on importance sampling have been developed for the Monte Carlo maximum likelihood estimation of univariate SV models. This paper shows that importance sampling methods can be used in a general multivariate SV setting. The sampling methods are computationally efficient. To illustrate the versatility of this approach, three different multivariate stochastic volatility models are estimated for a standard data set. The empirical results are compared to those from earlier studies in the literature. Monte Carlo simulation experiments, based on parameter estimates from the standard data set, are used to show the effectiveness of the importance sampling methods. Journal: Econometric Reviews Pages: 385-408 Issue: 2-3 Volume: 25 Year: 2006 Keywords: Importance sampling, Monte Carlo likelihood, Stochastic volatility, X-DOI: 10.1080/07474930600712848 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930600712848 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:25:y:2006:i:2-3:p:385-408 Template-Type: ReDIF-Article 1.0 Author-Name: Ben Tims Author-X-Name-First: Ben Author-X-Name-Last: Tims Author-Name: Ronald Mahieu Author-X-Name-First: Ronald Author-X-Name-Last: Mahieu Title: A Range-Based Multivariate Stochastic Volatility Model for Exchange Rates Abstract: In this paper we present a parsimonious multivariate model for exchange rate volatilities based on logarithmic high-low ranges of daily exchange rates. The multivariate stochastic volatility model decomposes the log range of each exchange rate into two independent latent factors, which could be interpreted as the underlying currency specific components. Owing to the empirical normality of the logarithmic range measure the model can be estimated conveniently with the standard Kalman filter methodology. Our results show that our model fits the exchange rate data quite well. Exchange rate news seems to be currency specific and allows identification of currency contributions to both exchange rate levels and exchange rate volatilities. Journal: Econometric Reviews Pages: 409-424 Issue: 2-3 Volume: 25 Year: 2006 Keywords: Exchange rates, Multivariate stochastic volatility models, Range-based volatility, X-DOI: 10.1080/07474930600712814 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930600712814 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:25:y:2006:i:2-3:p:409-424 Template-Type: ReDIF-Article 1.0 Author-Name: Michael Smith Author-X-Name-First: Michael Author-X-Name-Last: Smith Author-Name: Andrew Pitts Author-X-Name-First: Andrew Author-X-Name-Last: Pitts Title: Foreign Exchange Intervention by the Bank of Japan: Bayesian Analysis Using a Bivariate Stochastic Volatility Model Abstract: A bivariate stochastic volatility model is employed to measure the effect of intervention by the Bank of Japan (BOJ) on daily returns and volume in the USD/YEN foreign exchange market. Missing observations are accounted for, and a data-based Wishart prior for the precision matrix of the errors to the transition equation that is in line with the likelihood is suggested. Empirical results suggest there is strong conditional heteroskedasticity in the mean-corrected volume measure, as well as contemporaneous correlation in the errors to both the observation and transition equations. A threshold model is used for the BOJ reaction function, which is estimated jointly with the bivariate stochastic volatility model via Markov chain Monte Carlo. This accounts for endogeneity between volatility in the market and the BOJ reaction function, something that has hindered much previous empirical analysis in the literature on central bank intervention. The empirical results suggest there was a shift in behavior by the BOJ, with a movement away from a policy of market stabilization and toward a role of support for domestic monetary policy objectives. Throughout, we observe “leaning against the wind” behavior, something that is a feature of most previous empirical analysis of central bank intervention. A comparison with a bivariate EGARCH model suggests that the bivariate stochastic volatility model produces estimates that better capture spikes in in-sample volatility. This is important in improving estimates of a central bank reaction function because it is at these periods of high daily volatility that central banks more frequently intervene. Journal: Econometric Reviews Pages: 425-451 Issue: 2-3 Volume: 25 Year: 2006 Keywords: Central bank intervention, Foreign exchange volume, Markov chain Monte Carlo, Missing observations, Multivariate stochastic volatility, Threshold model, X-DOI: 10.1080/07474930600712897 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930600712897 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:25:y:2006:i:2-3:p:425-451 Template-Type: ReDIF-Article 1.0 Author-Name: Manabu Asai Author-X-Name-First: Manabu Author-X-Name-Last: Asai Author-Name: Michael McAleer Author-X-Name-First: Michael Author-X-Name-Last: McAleer Title: Asymmetric Multivariate Stochastic Volatility Abstract: This paper proposes and analyses two types of asymmetric multivariate stochastic volatility (SV) models, namely, (i) the SV with leverage (SV-L) model, which is based on the negative correlation between the innovations in the returns and volatility, and (ii) the SV with leverage and size effect (SV-LSE) model, which is based on the signs and magnitude of the returns. The paper derives the state space form for the logarithm of the squared returns, which follow the multivariate SV-L model, and develops estimation methods for the multivariate SV-L and SV-LSE models based on the Monte Carlo likelihood (MCL) approach. The empirical results show that the multivariate SV-LSE model fits the bivariate and trivariate returns of the S&P 500, the Nikkei 225, and the Hang Seng indexes with respect to AIC and BIC more accurately than does the multivariate SV-L model. Moreover, the empirical results suggest that the univariate models should be rejected in favor of their bivariate and trivariate counterparts. Journal: Econometric Reviews Pages: 453-473 Issue: 2-3 Volume: 25 Year: 2006 Keywords: Asymmetric leverage, Bayesian Markov chain Monte Carlo, Dynamic leverage, Importance sampling, Multivariate stochastic volatility, Numerical likelihood, Size effect, X-DOI: 10.1080/07474930600712913 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930600712913 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:25:y:2006:i:2-3:p:453-473 Template-Type: ReDIF-Article 1.0 Author-Name: Esmeralda Ramalho Author-X-Name-First: Esmeralda Author-X-Name-Last: Ramalho Author-Name: Joaquim Ramalho Author-X-Name-First: Joaquim Author-X-Name-Last: Ramalho Title: Bias-Corrected Moment-Based Estimators for Parametric Models Under Endogenous Stratified Sampling Abstract: This paper provides an integrated approach for estimating parametric models from endogenous stratified samples. We discuss several alternative ways of removing the bias of the moment indicators usually employed under random sampling for estimating the parameters of the structural model and the proportion of the strata in the population. Those alternatives give rise to a number of moment-based estimators that are appropriate for both cases where the marginal strata probabilities are known and unknown. The derivation of our estimators is very simple and intuitive and incorporates as particular cases most of the likelihood-based estimators previously suggested by other authors. Journal: Econometric Reviews Pages: 475-496 Issue: 4 Volume: 25 Year: 2006 Keywords: Bias correction, Endogenous stratified sampling, GMM, Parametric models, X-DOI: 10.1080/07474930600972574 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930600972574 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:25:y:2006:i:4:p:475-496 Template-Type: ReDIF-Article 1.0 Author-Name: Leopold Simar Author-X-Name-First: Leopold Author-X-Name-Last: Simar Author-Name: Valentin Zelenyuk Author-X-Name-First: Valentin Author-X-Name-Last: Zelenyuk Title: On Testing Equality of Distributions of Technical Efficiency Scores Abstract: The challenge of the econometric problem in production efficiency analysis is that the efficiency scores to be analyzed are unobserved. Statistical properties have recently been discovered for a type of estimator popular in the literature, known as data envelopment analysis (DEA). This opens up a wide range of possibilities for well-grounded statistical inference about the true efficiency scores from their DEA estimates. In this paper we investigate the possibility of using existing tests for the equality of two distributions in such a context. Considering the statistical complications pertinent to our context, we consider several approaches to adapting the Li test to the context and explore their performance in terms of the size and power of the test in various Monte Carlo experiments. One of these approaches shows good performance for both the size and the power of the test, thus encouraging its use in empirical studies. We also present an empirical illustration analyzing the efficiency distributions of countries in the world, following up a recent study by Kumar and Russell (2002), and report very interesting results. Journal: Econometric Reviews Pages: 497-522 Issue: 4 Volume: 25 Year: 2006 Keywords: Bootstrap, DEA, Kernel density estimation and tests, X-DOI: 10.1080/07474930600972582 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930600972582 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:25:y:2006:i:4:p:497-522 Template-Type: ReDIF-Article 1.0 Author-Name: Jeffery Racine Author-X-Name-First: Jeffery Author-X-Name-Last: Racine Author-Name: Jeffrey Hart Author-X-Name-First: Jeffrey Author-X-Name-Last: Hart Author-Name: Qi Li Author-X-Name-First: Qi Author-X-Name-Last: Li Title: Testing the Significance of Categorical Predictor Variables in Nonparametric Regression Models Abstract: In this paper we propose a test for the significance of categorical predictors in nonparametric regression models. The test is fully data-driven and employs cross-validated smoothing parameter selection while the null distribution of the test is obtained via bootstrapping. The proposed approach allows applied researchers to test hypotheses concerning categorical variables in a fully nonparametric and robust framework, thereby deflecting potential criticism that a particular finding is driven by an arbitrary parametric specification. Simulations reveal that the test performs well, having significantly better power than a conventional frequency-based nonparametric test. The test is applied to determine whether OECD and non-OECD countries follow the same growth rate model or not. Our test suggests that OECD and non-OECD countries follow different growth rate models, while the tests based on a popular parametric specification and the conventional frequency-based nonparametric estimation method fail to detect any significant difference. Journal: Econometric Reviews Pages: 523-544 Issue: 4 Volume: 25 Year: 2006 Keywords: Discrete regressors, Inference, Kernel smoothing, X-DOI: 10.1080/07474930600972590 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930600972590 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:25:y:2006:i:4:p:523-544 Template-Type: ReDIF-Article 1.0 Author-Name: Massimiliano Caporin Author-X-Name-First: Massimiliano Author-X-Name-Last: Caporin Title: Variance (Non) Causality in Multivariate GARCH Abstract: This paper extends the current literature on the variance-causality topic providing the coefficient restrictions ensuring variance noncausality within multivariate GARCH models with in-mean effects. Furthermore, this paper presents a new multivariate model, the exponential causality GARCH. By the introduction of a multiplicative causality impact function, the variance causality effects becomes directly interpretable and can therefore be used to detect both the existence of causality and its direction; notably, the proposed model allows for increasing and decreasing variance effects. An empirical application evidences negative causality effects between returns and volume of an Italian stock market index future contract. Journal: Econometric Reviews Pages: 1-24 Issue: 1 Volume: 26 Year: 2007 Keywords: Multivariate GARCH, Variance causality, Volatility, X-DOI: 10.1080/07474930600972178 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930600972178 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:26:y:2007:i:1:p:1-24 Template-Type: ReDIF-Article 1.0 Author-Name: Erik Meijer Author-X-Name-First: Erik Author-X-Name-Last: Meijer Author-Name: Tom Wansbeek Author-X-Name-First: Tom Author-X-Name-Last: Wansbeek Title: The Sample Selection Model from a Method of Moments Perspective Abstract: It is shown how the usual two-step estimator for the standard sample selection model can be seen as a method of moments estimator. Standard GMM theory can be brought to bear on this model, greatly simplifying the derivation of the asymptotic properties of this model. Using this setup, the asymptotic variance is derived in detail and a consistent estimator of it is obtained that is guaranteed to be positive definite, in contrast with the estimator given in the literature. It is demonstrated how the MM approach easily accommodates variations on the estimator, like the two-step IV estimator that handles endogenous regressors, and a two-step GLS estimator. Furthermore, it is shown that from the MM formulation, it is straightforward to derive various specification tests, in particular tests for selection bias, equivalence with the censored regression model, normality, homoskedasticity, and exogeneity. Journal: Econometric Reviews Pages: 25-51 Issue: 1 Volume: 26 Year: 2007 Keywords: GMM, Heckman estimator, Tobit, X-DOI: 10.1080/07474930600972194 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930600972194 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:26:y:2007:i:1:p:25-51 Template-Type: ReDIF-Article 1.0 Author-Name: Eric Ghysels Author-X-Name-First: Eric Author-X-Name-Last: Ghysels Author-Name: Arthur Sinko Author-X-Name-First: Arthur Author-X-Name-Last: Sinko Author-Name: Rossen Valkanov Author-X-Name-First: Rossen Author-X-Name-Last: Valkanov Title: MIDAS Regressions: Further Results and New Directions Abstract: We explore mixed data sampling (henceforth MIDAS) regression models. The regressions involve time series data sampled at different frequencies. Volatility and related processes are our prime focus, though the regression method has wider applications in macroeconomics and finance, among other areas. The regressions combine recent developments regarding estimation of volatility and a not-so-recent literature on distributed lag models. We study various lag structures to parameterize parsimoniously the regressions and relate them to existing models. We also propose several new extensions of the MIDAS framework. The paper concludes with an empirical section where we provide further evidence and new results on the risk-return trade-off. We also report empirical evidence on microstructure noise and volatility forecasting. Journal: Econometric Reviews Pages: 53-90 Issue: 1 Volume: 26 Year: 2007 Keywords: Microstructure noise, Nonlinear MIDAS, Risk, Tick-by-tick applications, Volatility, X-DOI: 10.1080/07474930600972467 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930600972467 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:26:y:2007:i:1:p:53-90 Template-Type: ReDIF-Article 1.0 Author-Name: Isabel Casas Author-X-Name-First: Isabel Author-X-Name-Last: Casas Author-Name: Jiti Gao Author-X-Name-First: Jiti Author-X-Name-Last: Gao Title: Nonparametric Methods in Continuous Time Model Specification Abstract: Some popular parametric diffusion processes have been assumed as such underlying diffusion processes. This paper considers an important case where both the drift and volatility functions of the underlying diffusion process are unknown functions of the underlying process, and then proposes using two novel testing procedures for the parametric specification of both the drift and diffusion functions. The finite-sample properties of the proposed tests are assessed through using data generated from four popular parametric models. In our implementation, we suggest using a simulated critical value for each case in addition to the use of an asymptotic critical value. Our detailed studies show that there is little size distortion when using a simulated critical value while the proposed tests have some size distortions when using an asymptotic critical value in each case. Journal: Econometric Reviews Pages: 91-106 Issue: 1 Volume: 26 Year: 2007 Keywords: Continuous-time model, Financial econometrics, Nonparametric kernel, Specification testing, X-DOI: 10.1080/07474930600972558 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930600972558 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:26:y:2007:i:1:p:91-106 Template-Type: ReDIF-Article 1.0 Author-Name: Gary Koop Author-X-Name-First: Gary Author-X-Name-Last: Koop Author-Name: Herman K. van Dijk Author-X-Name-First: Herman K. Author-X-Name-Last: van Dijk Title: Editors' Introduction to the Special Issue of Econometric Reviews on Bayesian Dynamic Econometrics Abstract: Journal: Econometric Reviews Pages: 107-112 Issue: 2-4 Volume: 26 Year: 2007 X-DOI: 10.1080/07474930701220675 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930701220675 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:26:y:2007:i:2-4:p:107-112 Template-Type: ReDIF-Article 1.0 Author-Name: Sungbae An Author-X-Name-First: Sungbae Author-X-Name-Last: An Author-Name: Frank Schorfheide Author-X-Name-First: Frank Author-X-Name-Last: Schorfheide Title: Bayesian Analysis of DSGE Models Abstract: This paper reviews Bayesian methods that have been developed in recent years to estimate and evaluate dynamic stochastic general equilibrium (DSGE) models. We consider the estimation of linearized DSGE models, the evaluation of models based on Bayesian model checking, posterior odds comparisons, and comparisons to vector autoregressions, as well as the non-linear estimation based on a second-order accurate model solution. These methods are applied to data generated from correctly specified and misspecified linearized DSGE models and a DSGE model that was solved with a second-order perturbation method. Journal: Econometric Reviews Pages: 113-172 Issue: 2-4 Volume: 26 Year: 2007 Keywords: Bayesian analysis, DSGE models, Model evaluation, Vector autoregressions, X-DOI: 10.1080/07474930701220071 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930701220071 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:26:y:2007:i:2-4:p:113-172 Template-Type: ReDIF-Article 1.0 Author-Name: Malin Adolfson Author-X-Name-First: Malin Author-X-Name-Last: Adolfson Author-Name: Jesper Linde Author-X-Name-First: Jesper Author-X-Name-Last: Linde Author-Name: Mattias Villani Author-X-Name-First: Mattias Author-X-Name-Last: Villani Title: Bayesian Analysis of DSGE Models—Some Comments Abstract: Sungbae An and Frank Schorfheide have provided an excellent review of the main elements of Bayesian inference in Dynamic Stochastic General Equilibrium (DSGE) models. Bayesian methods have, for reasons clearly outlined in the paper, a very natural role to play in DSGE analysis, and the appeal of the Bayesian paradigm is indeed strongly evidenced by the flood of empirical applications in the area over the last couple of years. We expect their paper to be the natural starting point for applied economists interested in learning about Bayesian techniques for analyzing DSGE models, and as such the paper is likely to have a strong influence on what will be considered best practice for estimating DSGE models. The authors have, for good reasons, chosen a stylized six-equation model to present the methodology. We shall use here the large-scale model in Adolfson et al. (2005), henceforth ALLV, to illustrate a few econometric problems which we have found to be especially important as the size of the model increases. The model in ALLV is an open economy extension of the closed economy model in Christiano et al. (2005). It consists of 25 log-linearized equations, which can be written as a state space representation with 60 state variables, many of them unobserved. Fifteen observed unfiltered time series are used to estimate 51 structural parameters. An additional complication compared to the model in An and Schorfheide's paper is that some of the coefficients in the measurement equation are non-linear functions of the structural parameters. The model is currently the main vehicle for policy analysis at Sveriges Riksbank (Central Bank of Sweden) and similar models are being developed in many other policy institutions, which testifies to the model's practical relevance. The version considered here is estimated on Euro area data over the period 1980Q1-2002Q4. We refer to ALLV for details. Journal: Econometric Reviews Pages: 173-185 Issue: 2-4 Volume: 26 Year: 2007 Keywords: Bayesian, DSGE, MCMC, Marginal likelihood, X-DOI: 10.1080/07474930701220121 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930701220121 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:26:y:2007:i:2-4:p:173-185 Template-Type: ReDIF-Article 1.0 Author-Name: Fabio Canova Author-X-Name-First: Fabio Author-X-Name-Last: Canova Title: Bayesian Analysis of DSGE Models by S. An and F. Schorfheide Abstract: The paper that An and Schorfheide have written is an excellent piece of work and will become a useful reference for teaching and consultation purposes. The paper discusses in an articulate and convincing manner almost everything that one could think of covering in such a review. This makes the task of the commentator difficult. Nevertheless, I will attempt to add few insights on three issues which, in my opinion, play an important role in applied work and in the interpretation of the estimation result. In particular, I will discuss a) the sensitivity of posterior distributions to prior spreads; b) the effects of model misspecification and an approach to model respecification; c) parameter identification and its consequences for posterior inference. Journal: Econometric Reviews Pages: 187-192 Issue: 2-4 Volume: 26 Year: 2007 Keywords: Bayesian analysis, DSGE models, Model evaluation, Vector autoregressions, X-DOI: 10.1080/07474930701220162 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930701220162 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:26:y:2007:i:2-4:p:187-192 Template-Type: ReDIF-Article 1.0 Author-Name: John Geweke Author-X-Name-First: John Author-X-Name-Last: Geweke Title: Comment Abstract: The article provides detailed and accurate illustrations of Bayesian analysis of DSGE models that are likely to be used increasingly in support of central bank policy making. These comments identify a dozen aspects of these methods, discussing how their application and improvement can contribute to effective support of policy. Journal: Econometric Reviews Pages: 193-200 Issue: 2-4 Volume: 26 Year: 2007 Keywords: Bayesian, DSGE models, Markov Chain Monte Carlo, Model selection, X-DOI: 10.1080/07474930701220196 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930701220196 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:26:y:2007:i:2-4:p:193-200 Template-Type: ReDIF-Article 1.0 Author-Name: Fabio Milani Author-X-Name-First: Fabio Author-X-Name-Last: Milani Author-Name: Dale J. Poirier Author-X-Name-First: Dale J. Author-X-Name-Last: Poirier Title: Econometric Issues in DSGE Models Abstract: Journal: Econometric Reviews Pages: 201-204 Issue: 2-4 Volume: 26 Year: 2007 X-DOI: 10.1080/07474930701220204 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930701220204 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:26:y:2007:i:2-4:p:201-204 Template-Type: ReDIF-Article 1.0 Author-Name: Tao Zha Author-X-Name-First: Tao Author-X-Name-Last: Zha Title: Comment on An and Schorfheide's Bayesian Analysis of DSGE Models Abstract: An and Schorfheide's article provides an excellent review of Bayesian estimation of DSGE models. Rather than recapitulating the points already made in this article, my comment focuses on three aspects. It proposes a convergence measure to take account of serial correlation of MCMC draws, explains why the DSGE-VAR framework for policy analysis can be improved by avoiding the ad hoc identification assumption, and discusses an alternative structural approach to model misspecification. Journal: Econometric Reviews Pages: 205-210 Issue: 2-4 Volume: 26 Year: 2007 Keywords: Ad hoc identification, Beliefs, B/W ratio, Off-equilibrium paths, Self-confirming equilibrium, X-DOI: 10.1080/07474930701220212 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930701220212 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:26:y:2007:i:2-4:p:205-210 Template-Type: ReDIF-Article 1.0 Author-Name: Sungbae An Author-X-Name-First: Sungbae Author-X-Name-Last: An Author-Name: Frank Schorfheide Author-X-Name-First: Frank Author-X-Name-Last: Schorfheide Title: Bayesian Analysis of DSGE Models—Rejoinder Abstract: We would like to thank all the discussants for their stimulating comments. While our article to a large extent reviews current practice of Bayesian analysis of Dynamic Stochastic General Equilibrium (DSGE) models the discussants provide many ideas to improve upon the current practice, thereby outlining a research agenda for the years to come. In our rejoinder we will briefly revisit some of the issues that were raised. Journal: Econometric Reviews Pages: 211-219 Issue: 2-4 Volume: 26 Year: 2007 Keywords: Bayesian analysis, DSGE models, Hybrid MCMC algorithm, Identification, X-DOI: 10.1080/07474930701220246 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930701220246 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:26:y:2007:i:2-4:p:211-219 Template-Type: ReDIF-Article 1.0 Author-Name: James D. Hamilton Author-X-Name-First: James D. Author-X-Name-Last: Hamilton Author-Name: Daniel F. Waggoner Author-X-Name-First: Daniel F. Author-X-Name-Last: Waggoner Author-Name: Tao Zha Author-X-Name-First: Tao Author-X-Name-Last: Zha Title: Normalization in Econometrics Abstract: The issue of normalization arises whenever two different values for a vector of unknown parameters imply the identical economic model. A normalization implies not just a rule for selecting which among equivalent points to call the maximum likelihood estimate (MLE), but also governs the topography of the set of points that go into a small-sample confidence interval associated with that MLE. A poor normalization can lead to multimodal distributions, disjoint confidence intervals, and very misleading characterizations of the true statistical uncertainty. This paper introduces an identification principle as a framework upon which a normalization should be imposed, according to which the boundaries of the allowable parameter space should correspond to loci along which the model is locally unidentified. We illustrate these issues with examples taken from mixture models, structural vector autoregressions, and cointegration models. Journal: Econometric Reviews Pages: 221-252 Issue: 2-4 Volume: 26 Year: 2007 Keywords: Cointegration, Local identification, Mixture distributions, Maximum likelihood estimate, Numerical Bayesian methods, Regime-switching, Small sample distributions, Vector autoregressions, Weak identification, X-DOI: 10.1080/07474930701220329 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930701220329 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:26:y:2007:i:2-4:p:221-252 Template-Type: ReDIF-Article 1.0 Author-Name: Hashem Pesaran Author-X-Name-First: Hashem Author-X-Name-Last: Pesaran Author-Name: Davide Pettenuzzo Author-X-Name-First: Davide Author-X-Name-Last: Pettenuzzo Author-Name: Allan Timmermann Author-X-Name-First: Allan Author-X-Name-Last: Timmermann Title: Learning, Structural Instability, and Present Value Calculations Abstract: Present value calculations require predictions of cash flows both at near and distant future points in time. Such predictions are generally surrounded by considerable uncertainty and may critically depend on assumptions about parameter values as well as the form and stability of the data generating process underlying the cash flows. This paper presents new theoretical results for the existence of the infinite sum of discounted expected future values under uncertainty about the parameters characterizing the growth rate of the cash flow process. Furthermore, we explore the consequences for present values of relaxing the stability assumption in a way that allows for past and future breaks to the underlying cash flow process. We find that such breaks can lead to considerable changes in present values. Journal: Econometric Reviews Pages: 253-288 Issue: 2-4 Volume: 26 Year: 2007 Keywords: Bayesian learning, Present value, Stock prices, Structural breaks, X-DOI: 10.1080/07474930701220352 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930701220352 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:26:y:2007:i:2-4:p:253-288 Template-Type: ReDIF-Article 1.0 Author-Name: Malin Adolfson Author-X-Name-First: Malin Author-X-Name-Last: Adolfson Author-Name: Jesper Linde Author-X-Name-First: Jesper Author-X-Name-Last: Linde Author-Name: Mattias Villani Author-X-Name-First: Mattias Author-X-Name-Last: Villani Title: Forecasting Performance of an Open Economy DSGE Model Abstract: This paper analyzes the forecasting performance of an open economy dynamic stochastic general equilibrium (DSGE) model, estimated with Bayesian methods, for the Euro area during 1994Q1-2002Q4. We compare the DSGE model and a few variants of this model to various reduced-form forecasting models such as vector autoregressions (VARs) and vector error correction models (VECM), estimated both by maximum likelihood and two different Bayesian approaches, and traditional benchmark models, e.g., the random walk. The accuracy of point forecasts, interval forecasts and the predictive distribution as a whole are assessed in an out-of-sample rolling event evaluation using several univariate and multivariate measures. The results show that the open economy DSGE model compares well with more empirical models and thus that the tension between rigor and fit in older generations of DSGE models is no longer present. We also critically examine the role of Bayesian model probabilities and other frequently used low-dimensional summaries, e.g., the log determinant statistic, as measures of overall forecasting performance. Journal: Econometric Reviews Pages: 289-328 Issue: 2-4 Volume: 26 Year: 2007 Keywords: Bayesian inference, Forecasting, Open economy DSGE model, Vector autoregressive models, X-DOI: 10.1080/07474930701220543 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930701220543 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:26:y:2007:i:2-4:p:289-328 Template-Type: ReDIF-Article 1.0 Author-Name: Jana Eklund Author-X-Name-First: Jana Author-X-Name-Last: Eklund Author-Name: Sune Karlsson Author-X-Name-First: Sune Author-X-Name-Last: Karlsson Title: Forecast Combination and Model Averaging Using Predictive Measures Abstract: We extend the standard approach to Bayesian forecast combination by forming the weights for the model averaged forecast from the predictive likelihood rather than the standard marginal likelihood. The use of predictive measures of fit offers greater protection against in-sample overfitting when uninformative priors on the model parameters are used and improves forecast performance. For the predictive likelihood we argue that the forecast weights have good large and small sample properties. This is confirmed in a simulation study and in an application to forecasts of the Swedish inflation rate, where forecast combination using the predictive likelihood outperforms standard Bayesian model averaging using the marginal likelihood. Journal: Econometric Reviews Pages: 329-363 Issue: 2-4 Volume: 26 Year: 2007 Keywords: Bayesian model averaging, Inflation rate, Partial Bayes factor, Predictive likelihood, Training sample, Uninformative priors, X-DOI: 10.1080/07474930701220550 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930701220550 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:26:y:2007:i:2-4:p:329-363 Template-Type: ReDIF-Article 1.0 Author-Name: L. Bauwens Author-X-Name-First: L. Author-X-Name-Last: Bauwens Author-Name: J. V. K. Rombouts Author-X-Name-First: J. V. K. Author-X-Name-Last: Rombouts Title: Bayesian Clustering of Many Garch Models Abstract: We consider the estimation of a large number of GARCH models, of the order of several hundreds. Our interest lies in the identification of common structures in the volatility dynamics of the univariate time series. To do so, we classify the series in an unknown number of clusters. Within a cluster, the series share the same model and the same parameters. Each cluster contains therefore similar series. We do not know a priori which series belongs to which cluster. The model is a finite mixture of distributions, where the component weights are unknown parameters and each component distribution has its own conditional mean and variance. Inference is done by the Bayesian approach, using data augmentation techniques. Simulations and an illustration using data on U.S. stocks are provided. Journal: Econometric Reviews Pages: 365-386 Issue: 2-4 Volume: 26 Year: 2007 Keywords: Bayesian inference, Clustering, GARCH, Gibbs sampling, Mixtures, X-DOI: 10.1080/07474930701220576 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930701220576 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:26:y:2007:i:2-4:p:365-386 Template-Type: ReDIF-Article 1.0 Author-Name: Catherine S. Forbes Author-X-Name-First: Catherine S. Author-X-Name-Last: Forbes Author-Name: Gael M. Martin Author-X-Name-First: Gael M. Author-X-Name-Last: Martin Author-Name: Jill Wright Author-X-Name-First: Jill Author-X-Name-Last: Wright Title: Inference for a Class of Stochastic Volatility Models Using Option and Spot Prices: Application of a Bivariate Kalman Filter Abstract: In this paper Bayesian methods are applied to a stochastic volatility model using both the prices of the asset and the prices of options written on the asset. Posterior densities for all model parameters, latent volatilities and the market price of volatility risk are produced via a Markov Chain Monte Carlo (MCMC) sampling algorithm. Candidate draws for the unobserved volatilities are obtained in blocks by applying the Kalman filter and simulation smoother to a linearization of a nonlinear state space representation of the model. Crucially, information from both the spot and option prices affects the draws via the specification of a bivariate measurement equation, with implied Black-Scholes volatilities used to proxy observed option prices in the candidate model. Alternative models nested within the Heston (1993) framework are ranked via posterior odds ratios, as well as via fit, predictive and hedging performance. The method is illustrated using Australian News Corporation spot and option price data. Journal: Econometric Reviews Pages: 387-418 Issue: 2-4 Volume: 26 Year: 2007 Keywords: Bayesian inference, Markov Chain Monte Carlo, Multi-move sampler, Option pricing, Nonlinear state space model, Volatility risk, X-DOI: 10.1080/07474930701220584 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930701220584 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:26:y:2007:i:2-4:p:387-418 Template-Type: ReDIF-Article 1.0 Author-Name: Petros Dellaportas Author-X-Name-First: Petros Author-X-Name-Last: Dellaportas Author-Name: David G. T. Denison Author-X-Name-First: David G. T. Author-X-Name-Last: Denison Author-Name: Chris Holmes Author-X-Name-First: Chris Author-X-Name-Last: Holmes Title: Flexible Threshold Models for Modelling Interest Rate Volatility Abstract: This paper focuses on interest rate models with regime switching and extends previous nonlinear threshold models by relaxing the assumption of a fixed number of regimes. Instead we suggest automatic model determination through Bayesian inference via the reversible jump Markov Chain Monte Carlo (MCMC) algorithm. Moreover, we allow the thresholds in the volatility to be driven not only by the interest rate but also by other economic factors. We illustrate our methodology by applying it to interest rates and other economic factors of the American economy. Journal: Econometric Reviews Pages: 419-437 Issue: 2-4 Volume: 26 Year: 2007 Keywords: Interest rates, Markov Chain Monte Carlo, Reversible jump, Threshold model, X-DOI: 10.1080/07474930701220600 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930701220600 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:26:y:2007:i:2-4:p:419-437 Template-Type: ReDIF-Article 1.0 Author-Name: Rodney W. Strachan Author-X-Name-First: Rodney W. Author-X-Name-Last: Strachan Title: Bayesian Inference in Cointegrated I (2) Systems: A Generalization of the Triangular Model Abstract: This paper generalizes the cointegrating model of Phillips (1991) to allow for I (0), I (1) and I (2) processes. The model has a simple form that permits a wider range of I (2) processes than are usually considered, including a more flexible form of polynomial cointegration. Further, the specification relaxes restrictions identified by Phillips (1991) on the I (1) and I (2) cointegrating vectors and restrictions on how the stochastic trends enter the system. To date there has been little work on Bayesian I (2) analysis and so this paper attempts to address this gap in the literature. A method of Bayesian inference in potentially I (2) processes is presented with application to Australian money demand using a Jeffreys prior and a shrinkage prior. Journal: Econometric Reviews Pages: 439-468 Issue: 2-4 Volume: 26 Year: 2007 Keywords: Cointegration, Bayesian, <i>I</i>(2) Analysis, Money demand, X-DOI: 10.1080/07474930701220618 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930701220618 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:26:y:2007:i:2-4:p:439-468 Template-Type: ReDIF-Article 1.0 Author-Name: Luc Bauwens Author-X-Name-First: Luc Author-X-Name-Last: Bauwens Author-Name: Michel Lubrano Author-X-Name-First: Michel Author-X-Name-Last: Lubrano Title: Bayesian Inference in Dynamic Disequilibrium Models: An Application to the Polish Credit Market Abstract: We propose a Bayesian approach for inference in a dynamic disequilibrium model. To circumvent the difficulties raised by the Maddala and Nelson (1974) specification in the dynamic case, we analyze a dynamic extended version of the disequilibrium model of Ginsburgh et al. (1980). We develop a Gibbs sampler based on the simulation of the missing observations. The feasibility of the approach is illustrated by an empirical analysis of the Polish credit market, for which we conduct a specification search using the posterior deviance criterion of Spiegelhalter et al. (2002). Journal: Econometric Reviews Pages: 469-486 Issue: 2-4 Volume: 26 Year: 2007 Keywords: Bayesian inference, Credit rationing, Data augmentation, Disequilibrium model, Latent variables, Poland, X-DOI: 10.1080/07474930701220634 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930701220634 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:26:y:2007:i:2-4:p:469-486 Template-Type: ReDIF-Article 1.0 Author-Name: Bent Nielsen Author-X-Name-First: Bent Author-X-Name-Last: Nielsen Author-Name: J. James Reade Author-X-Name-First: J. James Author-X-Name-Last: Reade Title: Simulating Properties of the Likelihood Ratio Test for a Unit Root in an Explosive Second-Order Autoregression Abstract: This paper provides a means of accurately simulating explosive autoregressive processes and uses this method to analyze the distribution of the likelihood ratio test statistic for an explosive second-order autoregressive process of a unit root. While the standard Dickey-Fuller distribution is known to apply in this case, simulations of statistics in the explosive region are beset by the magnitude of the numbers involved, which cause numerical inaccuracies. This has previously constituted a bar on supporting asymptotic results by means of simulation, and analyzing the finite sample properties of tests in the explosive region. Journal: Econometric Reviews Pages: 487-501 Issue: 5 Volume: 26 Year: 2007 Keywords: Explosive autoregression, Simulation, Unit root test, X-DOI: 10.1080/07474930701512055 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930701512055 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:26:y:2007:i:5:p:487-501 Template-Type: ReDIF-Article 1.0 Author-Name: Florenz Plassmann Author-X-Name-First: Florenz Author-X-Name-Last: Plassmann Author-Name: Neha Khanna Author-X-Name-First: Neha Author-X-Name-Last: Khanna Title: Assessing the Precision of Turning Point Estimates in Polynomial Regression Functions Abstract: Researchers often report point estimates of turning point(s) obtained in polynomial regression models but rarely assess the precision of these estimates. We discuss three methods to assess the precision of such turning point estimates. The first is the delta method that leads to a normal approximation of the distribution of the turning point estimator. The second method uses the exact distribution of the turning point estimator of quadratic regression functions. The third method relies on Markov chain Monte Carlo methods to provide a finite sample approximation of the exact distribution of the turning point estimator. We argue that the delta method may lead to misleading inference and that the other two methods are more reliable. We compare the three methods using two data sets from the environmental Kuznets curve literature, where the presence and location of a turning point in the income-pollution relationship is the focus of much empirical work. Journal: Econometric Reviews Pages: 503-528 Issue: 5 Volume: 26 Year: 2007 Keywords: Asymmetric confidence interval, Environmental Kuznets curve hypothesis, MCMC, Quantiles, X-DOI: 10.1080/07474930701512105 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930701512105 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:26:y:2007:i:5:p:503-528 Template-Type: ReDIF-Article 1.0 Author-Name: Mingliang Li Author-X-Name-First: Mingliang Author-X-Name-Last: Li Title: Bayesian Proportional Hazard Analysis of the Timing of High School Dropout Decisions Abstract: In this paper, I study the timing of high school dropout decisions using data from High School and Beyond. I propose a Bayesian proportional hazard analysis framework that takes into account the specification of piecewise constant baseline hazard, the time-varying covariate of dropout eligibility, and individual, school, and state level random effects in the dropout hazard. I find that students who have reached their state compulsory school attendance ages are more likely to drop out of high school than those who have not reached compulsory school attendance ages. Regarding the school quality effects, a student is more likely to drop out of high school if the school she attends is associated with a higher pupil-teacher ratio or lower district expenditure per pupil. An interesting finding of the paper that comes along with the empirical results is that failure to account for the time-varying heterogeneity in the hazard, in this application, results in upward biases in the duration dependence estimates. Moreover, these upward biases are comparable in magnitude to the well-known downward biases in the duration dependence estimates when the modeling of the time-invariant heterogeneity in the hazard is absent. Journal: Econometric Reviews Pages: 529-556 Issue: 5 Volume: 26 Year: 2007 Keywords: Bayesian analysis, High school dropout behavior, Proportional hazard analysis, X-DOI: 10.1080/07474930701509416 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930701509416 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:26:y:2007:i:5:p:529-556 Template-Type: ReDIF-Article 1.0 Author-Name: Yasemin Ulu Author-X-Name-First: Yasemin Author-X-Name-Last: Ulu Title: A Comparison of the Runs Test for Volatility Forecastability and the LM Test for GARCH Using Aggregated Returns Abstract: Christoffersen and Diebold (2000) have introduced a runs test for forecastable volatility in aggregated returns. In this note, we compare the size and power of their runs test and the more conventional LM test for GARCH by Monte Carlo simulation. When the true daily process is GARCH, EGARCH, or stochastic volatility, the LM test has better power than the runs test for the moderate-horizon returns considered by Christoffersen and Diebold. For long-horizon returns, however, the tests have very similar power. We also consider a qualitative threshold GARCH model. For this process, we find that the runs test has greater power than the LM test. Theresults support the use of the runs test with aggregated returns. Journal: Econometric Reviews Pages: 557-566 Issue: 5 Volume: 26 Year: 2007 Keywords: Aggregated returns, Forecast horizon, GARCH, LM test, Monte Carlo simulation, Runs test, Volatility forecastability, X-DOI: 10.1080/07474930701512147 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930701512147 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:26:y:2007:i:5:p:557-566 Template-Type: ReDIF-Article 1.0 Author-Name: Kuan Xu Author-X-Name-First: Kuan Author-X-Name-Last: Xu Title: U-Statistics and Their Asymptotic Results for Some Inequality and Poverty Measures Abstract: U-statistics form a general class of statistics that have certain important features in common. This class arises as a generalization of the sample mean and the sample variance, and typically members of the class are asymptotically normal with good consistency properties. The class encompasses some widely used income inequality and poverty measures, in particular the variance, the Gini index, the poverty rate, the average poverty gap ratios, the Foster-Greer-Thorbecke index, and the Sen index and its modified form. This paper illustrates how these measures come together within the class of U-statistics, and thereby why U-statistics are useful in econometrics. Journal: Econometric Reviews Pages: 567-577 Issue: 5 Volume: 26 Year: 2007 Keywords: Asymptotic theory, Inequality, Measures, Poverty, U-statistics, X-DOI: 10.1080/07474930701512170 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930701512170 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:26:y:2007:i:5:p:567-577 Template-Type: ReDIF-Article 1.0 Author-Name: Camilo Dagum Author-X-Name-First: Camilo Author-X-Name-Last: Dagum Author-Name: Giorgio Vittadini Author-X-Name-First: Giorgio Author-X-Name-Last: Vittadini Author-Name: Pietro Giorgio Lovaglio Author-X-Name-First: Pietro Giorgio Author-X-Name-Last: Lovaglio Title: Formative Indicators and Effects of a Causal Model for Household Human Capital with Application Abstract: Dagum and Slottje (2000) estimated household human capital (HC) as a latent variable (LV) and proposed its monetary estimation by means of an actuarial approach. This paper introduces an improved method for the estimation of household HC as an LV by means of formative and reflective indicators in agreement with the accepted economic definition of HC. The monetary value of HC is used in a recursive causal model to obtain short- and long-term multipliers that measure the direct and total effects of the variables that determine household HC. The new method is applied to estimate US household HC for year 2004. Journal: Econometric Reviews Pages: 579-596 Issue: 5 Volume: 26 Year: 2007 Keywords: Formative and reflective indicators, Latent variable, Short-term and long-term multipliers, U.S. household human capital distribution, X-DOI: 10.1080/07474930701512246 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930701512246 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:26:y:2007:i:5:p:579-596 Template-Type: ReDIF-Article 1.0 Author-Name: Massimo Guidolin Author-X-Name-First: Massimo Author-X-Name-Last: Guidolin Title: A Review of: “Book Review: Empirical Dynamic Asset Pricing” Abstract: Journal: Econometric Reviews Pages: 597-604 Issue: 5 Volume: 26 Year: 2007 X-DOI: 10.1080/07474930701512410 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930701512410 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:26:y:2007:i:5:p:597-604 Template-Type: ReDIF-Article 1.0 Author-Name: Silvia Goncalves Author-X-Name-First: Silvia Author-X-Name-Last: Goncalves Author-Name: Lutz Kilian Author-X-Name-First: Lutz Author-X-Name-Last: Kilian Title: Asymptotic and Bootstrap Inference for AR(∞) Processes with Conditional Heteroskedasticity Abstract: The main contribution of this paper is a proof of the asymptotic validity of the application of the bootstrap to AR(∞) processes with unmodelled conditional heteroskedasticity. We first derive the asymptotic properties of the least-squares estimator of the autoregressive sieve parameters when the data are generated by a stationary linear process with martingale difference errors that are possibly subject to conditional heteroskedasticity of unknown form. These results are then used in establishing that a suitably constructed bootstrap estimator will have the same limit distribution as the least-squares estimator. Our results provide theoretical justification for the use of either the conventional asymptotic approximation based on robust standard errors or the bootstrap approximation of the distribution of autoregressive parameters. A simulation study suggests that the bootstrap approach tends to be more accurate in small samples. Journal: Econometric Reviews Pages: 609-641 Issue: 6 Volume: 26 Year: 2007 Keywords: Autoregression, Bootstrap, GARCH, X-DOI: 10.1080/07474930701624462 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930701624462 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:26:y:2007:i:6:p:609-641 Template-Type: ReDIF-Article 1.0 Author-Name: Zhijie Xiao Author-X-Name-First: Zhijie Author-X-Name-Last: Xiao Author-Name: Luiz Renato Lima Author-X-Name-First: Luiz Renato Author-X-Name-Last: Lima Title: Testing Covariance Stationarity Abstract: In this paper, we show that the widely used stationarity tests such as the Kwiatkowski Phillips, Schmidt, and Shin (KPSS) test have power close to size in the presence of time-varying unconditional variance. We propose a new test as a complement of the existing tests. Monte Carlo experiments show that the proposed test possesses the following characteristics: (i) in the presence of unit root or a structural change in the mean, the proposed test is as powerful as the KPSS and other tests; (ii) in the presence of a changing variance, the traditional tests perform badly whereas the proposed test has high power comparing to the existing tests; (iii) the proposed test has the same size as traditional stationarity tests under the null hypothesis of stationarity. An application to daily observations of return on U.S. Dollar/Euro exchange rate reveals the existence of instability in the unconditional variance when the entire sample is considered, but stability is found in subsamples. Journal: Econometric Reviews Pages: 643-667 Issue: 6 Volume: 26 Year: 2007 Keywords: Asymptotic theory, KPSS, Stationarity testing, Time-varying variance, X-DOI: 10.1080/07474930701639080 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930701639080 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:26:y:2007:i:6:p:643-667 Template-Type: ReDIF-Article 1.0 Author-Name: Walter Beckert Author-X-Name-First: Walter Author-X-Name-Last: Beckert Title: Specification and Identification of Stochastic Demand Models Abstract: This paper is concerned with stochastic demand systems for continuous choices that arise from structural random utility models. It examines under which nonparametric conditions on the structural random utility specification the implied reduced form model is nonsingular and invertible. For parametric members within this class of random utility models, the paper provides conditions for local identification from the reduced form under moment assumptions. Journal: Econometric Reviews Pages: 669-683 Issue: 6 Volume: 26 Year: 2007 Keywords: Invertibility, Local identification, Random utility, Stochastic demand, X-DOI: 10.1080/07474930701653719 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930701653719 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:26:y:2007:i:6:p:669-683 Template-Type: ReDIF-Article 1.0 Author-Name: Timothy Halliday Author-X-Name-First: Timothy Author-X-Name-Last: Halliday Title: Testing for State Dependence with Time-Variant Transition Probabilities Abstract: We derive a simple result that allows us to test for the presence of state dependence in a dynamic Logit model with time-variant transition probabilities and an arbitrary distribution of the unobserved heterogeneity. Monte Carlo evidence suggests that this test has desirable properties even when there are some violations of the model's assumptions. We also consider alternative tests that will have desirable properties only when the transition probabilities do not depend on time and provide evidence that there is an “acceptable” range in which ignoring time-dependence does not matter too much. We conclude with an application to the Barker Hypothesis. Journal: Econometric Reviews Pages: 685-703 Issue: 6 Volume: 26 Year: 2007 Keywords: Dynamic panel data models, Health, State dependence, X-DOI: 10.1080/07474930701653768 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930701653768 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:26:y:2007:i:6:p:685-703 Template-Type: ReDIF-Article 1.0 Author-Name: Yoichi Arai Author-X-Name-First: Yoichi Author-X-Name-Last: Arai Author-Name: Eiji Kurozumi Author-X-Name-First: Eiji Author-X-Name-Last: Kurozumi Title: Testing for the Null Hypothesis of Cointegration with a Structural Break Abstract: In this paper we propose residual-based tests for the null hypothesis of cointegration with a structural break against the alternative of no cointegration. The Lagrange Multiplier (LM) test is proposed and its limiting distribution is obtained for the case in which the timing of a structural break is known. Then the test statistic is extended to deal with a structural break of unknown timing. The test statistic, a plug-in version of the test statistic for known timing, replaces the true break point by the estimated one. We show the limiting properties of the test statistic under the null as well as the alternative. Critical values are calculated for the tests by simulation methods. Finite-sample simulations show that the empirical size of the test is close to the nominal one unless the regression error is very persistent and that the test rejects the null when no cointegrating relationship with a structural break is present. We provide empirical examples based on the present-value model, the term structure model, and the money-output relationship model. Journal: Econometric Reviews Pages: 705-739 Issue: 6 Volume: 26 Year: 2007 Keywords: Cointegration, Integrated time series, No cointegration, Structural break, X-DOI: 10.1080/07474930701653776 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930701653776 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:26:y:2007:i:6:p:705-739 Template-Type: ReDIF-Article 1.0 Author-Name: James Davidson Author-X-Name-First: James Author-X-Name-Last: Davidson Title: A Review of: “Book Review: Mathematical and Statistical Foundations” Abstract: Journal: Econometric Reviews Pages: 605-607 Issue: 5 Volume: 26 Year: 2007 X-DOI: 10.1080/07474930701512436 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930701512436 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:26:y:2007:i:5:p:605-607 Template-Type: ReDIF-Article 1.0 Author-Name: Esfandiar Maasoumi Author-X-Name-First: Esfandiar Author-X-Name-Last: Maasoumi Author-Name: Michael McAleer Author-X-Name-First: Michael Author-X-Name-Last: McAleer Title: Realized Volatility and Long Memory: An Overview Abstract: The challenge of modeling, estimating, testing, and forecasting financial volatility is both intellectually worthwhile and also central to the successful analysis of financial returns and optimal investment strategies. In each of the three primary areas of volatility modeling, namely, conditional (or generalized autoregressive conditional heteroskedasticity) volatility, stochastic volatility and realized volatility (RV), numerous univariate volatility models of individual financial assets and multivariate volatility models of portfolios of assets have been established. This special issue has eleven innovative articles, eight of which are focused directly on RV and three on long memory, while two are concerned with both RV and long memory. Journal: Econometric Reviews Pages: 1-9 Issue: 1-3 Volume: 27 Year: 2008 Keywords: Forecasting, Integrated variance, Realized quarticity, Realized volatility, Returns, Risk, Securities, X-DOI: 10.1080/07474930701853459 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930701853459 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:27:y:2008:i:1-3:p:1-9 Template-Type: ReDIF-Article 1.0 Author-Name: Michael McAleer Author-X-Name-First: Michael Author-X-Name-Last: McAleer Author-Name: Marcelo Medeiros Author-X-Name-First: Marcelo Author-X-Name-Last: Medeiros Title: Realized Volatility: A Review Abstract: This article reviews the exciting and rapidly expanding literature on realized volatility. After presenting a general univariate framework for estimating realized volatilities, a simple discrete time model is presented in order to motivate the main results. A continuous time specification provides the theoretical foundation for the main results in this literature. Cases with and without microstructure noise are considered, and it is shown how microstructure noise can cause severe problems in terms of consistent estimation of the daily realized volatility. Independent and dependent noise processes are examined. The most important methods for providing consistent estimators are presented, and a critical exposition of different techniques is given. The finite sample properties are discussed in comparison with their asymptotic properties. A multivariate model is presented to discuss estimation of the realized covariances. Various issues relating to modelling and forecasting realized volatilities are considered. The main empirical findings using univariate and multivariate methods are summarized. Journal: Econometric Reviews Pages: 10-45 Issue: 1-3 Volume: 27 Year: 2008 Keywords: Continuous time processes, Finance, Financial econometrics, Forecasting, High frequency data, Quadratic variation, Realized volatility, Risk, Trading rules, X-DOI: 10.1080/07474930701853509 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930701853509 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:27:y:2008:i:1-3:p:10-45 Template-Type: ReDIF-Article 1.0 Author-Name: Fulvio Corsi Author-X-Name-First: Fulvio Author-X-Name-Last: Corsi Author-Name: Stefan Mittnik Author-X-Name-First: Stefan Author-X-Name-Last: Mittnik Author-Name: Christian Pigorsch Author-X-Name-First: Christian Author-X-Name-Last: Pigorsch Author-Name: Uta Pigorsch Author-X-Name-First: Uta Author-X-Name-Last: Pigorsch Title: The Volatility of Realized Volatility Abstract: In recent years, with the availability of high-frequency financial market data modeling realized volatility has become a new and innovative research direction. The construction of “observable” or realized volatility series from intra-day transaction data and the use of standard time-series techniques has lead to promising strategies for modeling and predicting (daily) volatility. In this article, we show that the residuals of commonly used time-series models for realized volatility and logarithmic realized variance exhibit non-Gaussianity and volatility clustering. We propose extensions to explicitly account for these properties and assess their relevance for modeling and forecasting realized volatility. In an empirical application for S&P 500 index futures we show that allowing for time-varying volatility of realized volatility and logarithmic realized variance substantially improves the fit as well as predictive performance. Furthermore, the distributional assumption for residuals plays a crucial role in density forecasting. Journal: Econometric Reviews Pages: 46-78 Issue: 1-3 Volume: 27 Year: 2008 Keywords: Density forecasting, Finance, HAR-GARCH, Normal inverse Gaussian distribution, Realized quarticity, Realized volatility, X-DOI: 10.1080/07474930701853616 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930701853616 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:27:y:2008:i:1-3:p:46-78 Template-Type: ReDIF-Article 1.0 Author-Name: Peter Hansen Author-X-Name-First: Peter Author-X-Name-Last: Hansen Author-Name: Jeremy Large Author-X-Name-First: Jeremy Author-X-Name-Last: Large Author-Name: Asger Lunde Author-X-Name-First: Asger Author-X-Name-Last: Lunde Title: Moving Average-Based Estimators of Integrated Variance Abstract: We examine moving average (MA) filters for estimating the integrated variance (IV) of a financial asset price in a framework where high-frequency price data are contaminated with market microstructure noise. We show that the sum of squared MA residuals must be scaled to enable a suitable estimator of IV. The scaled estimator is shown to be consistent, first-order efficient, and asymptotically Gaussian distributed about the integrated variance under restrictive assumptions. Under more plausible assumptions, such as time-varying volatility, the MA model is misspecified. This motivates an extensive simulation study of the merits of the MA-based estimator under misspecification. Specifically, we consider nonconstant volatility combined with rounding errors and various forms of dependence between the noise and efficient returns. We benchmark the scaled MA-based estimator to subsample and realized kernel estimators and find that the MA-based estimator performs well despite the misspecification. Journal: Econometric Reviews Pages: 79-111 Issue: 1-3 Volume: 27 Year: 2008 Keywords: Bias correction, High-frequency data, Integrated variance, Moving average, Realized variance, Realized volatility, X-DOI: 10.1080/07474930701853640 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930701853640 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:27:y:2008:i:1-3:p:79-111 Template-Type: ReDIF-Article 1.0 Author-Name: Toshiya Hoshikawa Author-X-Name-First: Toshiya Author-X-Name-Last: Hoshikawa Author-Name: Keiji Nagai Author-X-Name-First: Keiji Author-X-Name-Last: Nagai Author-Name: Taro Kanatani Author-X-Name-First: Taro Author-X-Name-Last: Kanatani Author-Name: Yoshihiko Nishiyama Author-X-Name-First: Yoshihiko Author-X-Name-Last: Nishiyama Title: Nonparametric Estimation Methods of Integrated Multivariate Volatilities Abstract: Estimation of integrated multivariate volatilities of an Ito process is an interesting and important issue in finance, for example, in order to evaluate portfolios. New non-parametric estimators have been recently proposed by Malliavin and Mancino (2002) and Hayashi and Yoshida (2005a) as alternative methods to classical realized quadratic covariation. The purpose of this article is to compare these alternative estimators both theoretically and empirically, when high frequency data is available. We found that the Hayashi-Yoshida estimator performs the best among the alternatives in view of the bias and the MSE. The other estimators are shown to have possibly heavy bias mostly toward the origin. We also applied these estimators to Japanese Government Bond futures to obtain the results consistent with our simulation. Journal: Econometric Reviews Pages: 112-138 Issue: 1-3 Volume: 27 Year: 2008 Keywords: High frequency data, Integrated volatility, Nonparametric estimators, Weighted realized volatility, X-DOI: 10.1080/07474930701853855 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930701853855 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:27:y:2008:i:1-3:p:112-138 Template-Type: ReDIF-Article 1.0 Author-Name: Silvia Goncalves Author-X-Name-First: Silvia Author-X-Name-Last: Goncalves Author-Name: Nour Meddahi Author-X-Name-First: Nour Author-X-Name-Last: Meddahi Title: Edgeworth Corrections for Realized Volatility Abstract: The quality of the asymptotic normality of realized volatility can be poor if sampling does not occur at very high frequencies. In this article we consider an alternative approximation to the finite sample distribution of realized volatility based on Edgeworth expansions. In particular, we show how confidence intervals for integrated volatility can be constructed using these Edgeworth expansions. The Monte Carlo study we conduct shows that the intervals based on the Edgeworth corrections have improved properties relatively to the conventional intervals based on the normal approximation. Contrary to the bootstrap, the Edgeworth approach is an analytical approach that is easily implemented, without requiring any resampling of one's data. A comparison between the bootstrap and the Edgeworth expansion shows that the bootstrap outperforms the Edgeworth corrected intervals. Thus, if we are willing to incur in the additional computational cost involved in computing bootstrap intervals, these are preferred over the Edgeworth intervals. Nevertheless, if we are not willing to incur in this additional cost, our results suggest that Edgeworth corrected intervals should replace the conventional intervals based on the first order normal approximation. Journal: Econometric Reviews Pages: 139-162 Issue: 1-3 Volume: 27 Year: 2008 Keywords: Confidence intervals, Edgeworth expansions, Realized volatility, X-DOI: 10.1080/07474930701870420 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930701870420 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:27:y:2008:i:1-3:p:139-162 Template-Type: ReDIF-Article 1.0 Author-Name: Federico Bandi Author-X-Name-First: Federico Author-X-Name-Last: Bandi Author-Name: Jeffrey Russell Author-X-Name-First: Jeffrey Author-X-Name-Last: Russell Author-Name: Yinghua Zhu Author-X-Name-First: Yinghua Author-X-Name-Last: Zhu Title: Using High-Frequency Data in Dynamic Portfolio Choice Abstract: This article evaluates the economic benefit of methods that have been suggested to optimally sample (in an MSE sense) high-frequency return data for the purpose of realized variance/covariance estimation in the presence of market microstructure noise (Bandi and Russell, 2005a, 2008). We compare certainty equivalents derived from volatility-timing trading strategies relying on optimally-sampled realized variances and covariances, on realized variances and covariances obtained by sampling every 5 minutes, and on realized variances and covariances obtained by sampling every 15 minutes. In our sample, we show that a risk-averse investor who is given the option of choosing variance/covariance forecasts derived from MSE-based optimal sampling methods versus forecasts obtained from 5- and 15-minute intervals (as generally proposed in the literature) would be willing to pay up to about 80 basis points per year to achieve the level of utility that is guaranteed by optimal sampling. We find that the gains yielded by optimal sampling are economically large, statistically significant, and robust to realistic transaction costs. Journal: Econometric Reviews Pages: 163-198 Issue: 1-3 Volume: 27 Year: 2008 Keywords: Dynamic portfolio choice, Market microstructure noise, Realized covariance, Realized variance, X-DOI: 10.1080/07474930701870461 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930701870461 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:27:y:2008:i:1-3:p:163-198 Template-Type: ReDIF-Article 1.0 Author-Name: Michiel de Pooter Author-X-Name-First: Michiel Author-X-Name-Last: de Pooter Author-Name: Martin Martens Author-X-Name-First: Martin Author-X-Name-Last: Martens Author-Name: Dick van Dijk Author-X-Name-First: Dick Author-X-Name-Last: van Dijk Title: Predicting the Daily Covariance Matrix for S&P 100 Stocks Using Intraday Data—But Which Frequency to Use? Abstract: This article investigates the merits of high-frequency intraday data when forming mean-variance efficient stock portfolios with daily rebalancing from the individual constituents of the S&P 100 index. We focus on the issue of determining the optimal sampling frequency as judged by the performance of these portfolios. The optimal sampling frequency ranges between 30 and 65 minutes, considerably lower than the popular five-minute frequency, which typically is motivated by the aim of striking a balance between the variance and bias in covariance matrix estimates due to market microstructure effects such as non-synchronous trading and bid-ask bounce. Bias-correction procedures, based on combining low-frequency and high-frequency covariance matrix estimates and on the addition of leads and lags do not substantially affect the optimal sampling frequency or the portfolio performance. Our findings are also robust to the presence of transaction costs and to the portfolio rebalancing frequency. Journal: Econometric Reviews Pages: 199-229 Issue: 1-3 Volume: 27 Year: 2008 Keywords: Bias-correction, High-frequency data, Mean-variance analysis, Realized volatility, Tracking error, Volatility timing, X-DOI: 10.1080/07474930701873333 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930701873333 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:27:y:2008:i:1-3:p:199-229 Template-Type: ReDIF-Article 1.0 Author-Name: Jim Griffin Author-X-Name-First: Jim Author-X-Name-Last: Griffin Author-Name: Roel Oomen Author-X-Name-First: Roel Author-X-Name-Last: Oomen Title: Sampling Returns for Realized Variance Calculations: Tick Time or Transaction Time? Abstract: This article introduces a new model for transaction prices in the presence of market microstructure noise in order to study the properties of the price process on two different time scales, namely, transaction time where prices are sampled with every transaction and tick time where prices are sampled with every price change. Both sampling schemes have been used in the literature on realized variance, but a formal investigation into their properties has been lacking. Our empirical and theoretical results indicate that the return dynamics in transaction time are very different from those in tick time and the choice of sampling scheme can therefore have an important impact on the properties of realized variance. For RV we find that tick time sampling is superior to transaction time sampling in terms of mean-squared-error, especially when the level of noise, number of ticks, or the arrival frequency of efficient price moves is low. Importantly, we show that while the microstructure noise may appear close to IID in transaction time, in tick time it is highly dependent. As a result, bias correction procedures that rely on the noise being independent, can fail in tick time and are better implemented in transaction time. Journal: Econometric Reviews Pages: 230-253 Issue: 1-3 Volume: 27 Year: 2008 Keywords: Market microstructure noise, Optimal sampling, Pure jump process, Realized variance, Tick time, Transaction time, X-DOI: 10.1080/07474930701873341 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930701873341 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:27:y:2008:i:1-3:p:230-253 Template-Type: ReDIF-Article 1.0 Author-Name: Offer Lieberman Author-X-Name-First: Offer Author-X-Name-Last: Lieberman Author-Name: Peter Phillips Author-X-Name-First: Peter Author-X-Name-Last: Phillips Title: Refined Inference on Long Memory in Realized Volatility Abstract: There is an emerging consensus in empirical finance that realized volatility series typically display long range dependence with a memory parameter (d) around 0.4 (Andersen et al., 2001; Martens et al., 2004). The present article provides some illustrative analysis of how long memory may arise from the accumulative process underlying realized volatility. The article also uses results in Lieberman and Phillips (2004, 2005) to refine statistical inference about d by higher order theory. Standard asymptotic theory has an O(n-1/2) error rate for error rejection probabilities, and the theory used here refines the approximation to an error rate of o(n-1/2). The new formula is independent of unknown parameters, is simple to calculate and user-friendly. The method is applied to test whether the reported long memory parameter estimates of Andersen et al. (2001) and Martens et al. (2004) differ significantly from the lower boundary (d = 0.5) of nonstationary long memory, and generally confirms earlier findings. Journal: Econometric Reviews Pages: 254-267 Issue: 1-3 Volume: 27 Year: 2008 Keywords: Edgeworth expansion, Long memory, Realized volatility, X-DOI: 10.1080/07474930701873374 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930701873374 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:27:y:2008:i:1-3:p:254-267 Template-Type: ReDIF-Article 1.0 Author-Name: Afonso Goncalves da Silva Author-X-Name-First: Afonso Goncalves Author-X-Name-Last: da Silva Author-Name: Peter Robinson Author-X-Name-First: Peter Author-X-Name-Last: Robinson Title: Finite Sample Performance in Cointegration Analysis of Nonlinear Time Series with Long Memory Abstract: Nonlinear functions of multivariate financial time series can exhibit long memory and fractional cointegration. However, tools for analysing these phenomena have principally been justified under assumptions that are invalid in this setting. Determination of asymptotic theory under more plausible assumptions can be complicated and lengthy. We discuss these issues and present a Monte Carlo study, showing that asymptotic theory should not necessarily be expected to provide a good approximation to finite-sample behavior. Journal: Econometric Reviews Pages: 268-297 Issue: 1-3 Volume: 27 Year: 2008 Keywords: Fractional cointegration, Memory estimation, Stochastic volatility, X-DOI: 10.1080/07474930701873382 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930701873382 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:27:y:2008:i:1-3:p:268-297 Template-Type: ReDIF-Article 1.0 Author-Name: Leonardo Rocha Souza Author-X-Name-First: Leonardo Rocha Author-X-Name-Last: Souza Title: Why Aggregate Long Memory Time Series? Abstract: This article shows that, for large samples, temporally aggregating a true long memory time series (in order to get an improved estimator) may make little or no sense, as the practitioner can get virtually the same estimates as those from the aggregated series by choosing the appropriate bandwidths on the original one, provided some fairly general conditions apply. Besides, the practitioner has a wider choice of bandwidths than she has of aggregating levels. However, these results apply only to two specific and commonly used estimators, and do not apply to the aggregation procedure undertaken to compute the realized volatility. Also, aggregating a time series in order to test true versus spurious long memory (as in Ohanissian et al., 2008) is a relevant issue, particularly regarding stochastic and/or realized volatility, as many nonlinear processes display spurious long memory where the above result does not apply. Journal: Econometric Reviews Pages: 298-316 Issue: 1-3 Volume: 27 Year: 2008 Keywords: Bandwidth, Long memory, Spectrum, Temporal aggregation, X-DOI: 10.1080/07474930701873408 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930701873408 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:27:y:2008:i:1-3:p:298-316 Template-Type: ReDIF-Article 1.0 Author-Name: Amos Golan Author-X-Name-First: Amos Author-X-Name-Last: Golan Author-Name: Esfandiar Maasoumi Author-X-Name-First: Esfandiar Author-X-Name-Last: Maasoumi Title: Information Theoretic and Entropy Methods: An Overview Abstract: Journal: Econometric Reviews Pages: 317-328 Issue: 4-6 Volume: 27 Year: 2008 Keywords: Entropy, Information, Information and entropy econometrics, Information theory, Information-theoretic estimators, X-DOI: 10.1080/07474930801959685 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930801959685 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:27:y:2008:i:4-6:p:317-328 Template-Type: ReDIF-Article 1.0 Author-Name: Steve Pincus Author-X-Name-First: Steve Author-X-Name-Last: Pincus Title: Approximate Entropy as an Irregularity Measure for Financial Data Abstract: The need to assess subtle, potentially exploitable changes in serial structure is paramount in the analysis of financial and econometric data. We demonstrate the utility of approximate entropy (ApEn), a model-independent measure of sequential irregularity, towards this goal, via several distinct applications, both empirical data and model-based. We also consider cross-ApEn, a related two-variable measure of asynchrony that provides a more robust and ubiquitous measure of bivariate correspondence than does correlation, and the resultant implications to diversification strategies. We provide analytic expressions for and statistical properties of ApEn, and compare ApEn to nonlinear (complexity) measures, correlation and spectral analyses, and other entropy measures. Journal: Econometric Reviews Pages: 329-362 Issue: 4-6 Volume: 27 Year: 2008 Keywords: Approximate entropy, Asynchrony, Complexity, Irregularity, X-DOI: 10.1080/07474930801959750 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930801959750 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:27:y:2008:i:4-6:p:329-362 Template-Type: ReDIF-Article 1.0 Author-Name: Andreas Koutris Author-X-Name-First: Andreas Author-X-Name-Last: Koutris Author-Name: Maria Heracleous Author-X-Name-First: Maria Author-X-Name-Last: Heracleous Author-Name: Aris Spanos Author-X-Name-First: Aris Author-X-Name-Last: Spanos Title: Testing for Nonstationarity Using Maximum Entropy Resampling: A Misspecification Testing Perspective Abstract: One of the most important assumptions in empirical modeling is the constancy of the statistical model parameters which usually reflects the stationarity of the underlying stochastic process. In the 1980s and 1990s, the issue of nonstationarity in economic time series has been discussed in the context of unit roots vs. mean trends in AR(p) models. This perspective was subsequently extended to include structural breaks. In this article we take a much broader perspective by allowing for more general forms of nonstationarity. The focus of the article is primarily on misspecification testing. The proposed test relies on Maximum Entropy (ME) resampling techniques to enhance the information in the data in an attempt to capture heterogeneity “locally” using rolling window estimators. The t-heterogeneity of the primary moments of the process is generically captured using orthogonal Bernstein polynomials. The effectiveness of the testing procedure is assessed using Monte Carlo simulations. Journal: Econometric Reviews Pages: 363-384 Issue: 4-6 Volume: 27 Year: 2008 Keywords: Berstein polynomials, <i>t</i>-Heterogeneity, Maximum Entropy bootstrap, Nonstationarity, Parameter <i>t</i>-invariance, Rolling window estimates, X-DOI: 10.1080/07474930801959776 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930801959776 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:27:y:2008:i:4-6:p:363-384 Template-Type: ReDIF-Article 1.0 Author-Name: Jan Jacobs Author-X-Name-First: Jan Author-X-Name-Last: Jacobs Author-Name: Pieter Otter Author-X-Name-First: Pieter Author-X-Name-Last: Otter Title: Determining the Number of Factors and Lag Order in Dynamic Factor Models: A Minimum Entropy Approach Abstract: This article proposes a solution to one of the issues in the rapidly growing literature on dynamic factor models, i.e., how to determine the optimal number of factors. Our formal test, based upon the canonical correlation procedure related to concepts from information theory, produces estimates of the number of factors and the lag order simultaneously. Simulation experiments illustrate the potential of our approach. Journal: Econometric Reviews Pages: 385-397 Issue: 4-6 Volume: 27 Year: 2008 Keywords: Canonical correlation, Factor analysis, Model selection, X-DOI: 10.1080/07474930801960196 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930801960196 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:27:y:2008:i:4-6:p:385-397 Template-Type: ReDIF-Article 1.0 Author-Name: Alastair Hall Author-X-Name-First: Alastair Author-X-Name-Last: Hall Author-Name: Atsushi Inoue Author-X-Name-First: Atsushi Author-X-Name-Last: Inoue Author-Name: Changmock Shin Author-X-Name-First: Changmock Author-X-Name-Last: Shin Title: Entropy-Based Moment Selection in the Presence of Weak Identification Abstract: Hall et al. (2007) propose a method for moment selection based on an information criterion that is a function of the entropy of the limiting distribution of the Generalized Method of Moments (GMM) estimator. They establish the consistency of the method subject to certain conditions that include the identification of the parameter vector by at least one of the moment conditions being considered. In this article, we examine the limiting behavior of this moment selection method when the parameter vector is weakly identified by all the moment conditions being considered. It is shown that the selected moment condition is random and hence not consistent in any meaningful sense. As a result, we propose a two-step procedure for moment selection in which identification is first tested using a statistic proposed by Stock and Yogo (2003) and then only if this statistic indicates identification does the researcher proceed to the second step in which the aforementioned information criterion is used to select moments. The properties of this two-step procedure are contrasted with those of strategies based on either using all available moments or using the information criterion without the identification pre-test. The performances of these strategies are compared via an evaluation of the finite sample behavior of various methods for inference about the parameter vector. The inference methods considered are based on the Wald statistic, Anderson and Rubin's (1949) statistic, Kleibergen (2002) K statistic, and combinations thereof in which the choice is based on the outcome of the test for weak identification. Journal: Econometric Reviews Pages: 398-427 Issue: 4-6 Volume: 27 Year: 2008 Keywords: Generalized method of moments, Inference, Moment selection, Weak identification, X-DOI: 10.1080/07474930801960261 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930801960261 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:27:y:2008:i:4-6:p:398-427 Template-Type: ReDIF-Article 1.0 Author-Name: Thomas Mazzuchi Author-X-Name-First: Thomas Author-X-Name-Last: Mazzuchi Author-Name: Ehsan Soofi Author-X-Name-First: Ehsan Author-X-Name-Last: Soofi Author-Name: Refik Soyer Author-X-Name-First: Refik Author-X-Name-Last: Soyer Title: Bayes Estimate and Inference for Entropy and Information Index of Fit Abstract: This article defines a quantized entropy and develops Bayes estimates and inference for the entropy and a Kullback-Leibler information index of the model fit. We use a Dirichlet process prior for the unknown data-generating distribution with a maximum entropy candidate model as the expected distribution. This formulation produces prior and posterior distributions for the quantized entropy, the information index of fit, the moments, and the model parameters. The posterior mean of the quantized entropy provides a Bayes estimate of entropy under quadratic loss. The consistency of the Bayes estimates and the information index are shown. The implementation and the performances of the Bayes estimates are illustrated using data simulated from exponential, gamma, and lognormal distributions. Journal: Econometric Reviews Pages: 428-456 Issue: 4-6 Volume: 27 Year: 2008 Keywords: Dirichlet process, Kullback-Leibler, Model selection, Nonparametric Bayes, X-DOI: 10.1080/07474930801960311 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930801960311 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:27:y:2008:i:4-6:p:428-456 Template-Type: ReDIF-Article 1.0 Author-Name: M. Ryan Haley Author-X-Name-First: M. Ryan Author-X-Name-Last: Haley Author-Name: Charles Whiteman Author-X-Name-First: Charles Author-X-Name-Last: Whiteman Title: Generalized Safety First and a New Twist on Portfolio Performance Abstract: We propose a Generalization of Roy's (1952) Safety First (SF) principle and relate it to the IID versions of Stutzer's (Stutzer's 2000, 2003) Portfolio Performance Index and underperformance probability Decay-Rate Maximization criteria. Like the original SF, the Generalized Safety First (GSF) rule seeks to minimize an upper bound on the probability of ruin (or shortfall, more generally) in a single drawing from a return distribution. We show that this upper bound coincides with what Stutzer showed will maximize the rate at which the probability of shortfall in the long-run average return shrinks to zero in repeated drawings from the return distribution. Our setup is simple enough that we can illustrate via direct calculation a deep result from Large Deviations theory: in the IID case the GSF probability bound and the decay rate correspond to the Kullback-Leibler (KL) divergence between the one-shot portfolio distribution and the “closest” mean-shortfall distribution. This enables us to produce examples in which minimizing the upper bound on the underperformance probability does not lead to the same decision as minimizing the underperformance probability itself, and thus that the decay-rate maximizing strategy may require the investor to take positions that do not minimize the probability of shortfall in each successive period. It also makes clear that the relationship between the marginal distribution of the one-period portfolio return and the mean-shortfall distribution is the same as that between the source density and the target density in importance sampling. Thus Geweke's (1989) measure of Relative Numerical Efficiency can be used as a measure of the quality of the divergence measure. Our interpretation of the decay rate maximizing criterion in terms of a one-shot problem enables us to use the tools of importance sampling to develop a “performance index” (standard error) for the Portfolio Performance Index (PPI). It turns out that in a simple stock portfolio example, portfolios within one (divergence) standard error of one another can have very different weights on individual securities. Journal: Econometric Reviews Pages: 457-483 Issue: 4-6 Volume: 27 Year: 2008 Keywords: Entropy, Importance sampling, Kullback-Leibler divergence, Portfolio choice, Portfolio performance, Safety first, Shortfall, X-DOI: 10.1080/07474930801960360 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930801960360 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:27:y:2008:i:4-6:p:457-483 Template-Type: ReDIF-Article 1.0 Author-Name: Anil Bera Author-X-Name-First: Anil Author-X-Name-Last: Bera Author-Name: Sung Park Author-X-Name-First: Sung Author-X-Name-Last: Park Title: Optimal Portfolio Diversification Using the Maximum Entropy Principle Abstract: Markowitz's mean-variance (MV) efficient portfolio selection is one of the most widely used approaches in solving portfolio diversification problem. However, contrary to the notion of diversification, MV approach often leads to portfolios highly concentrated on a few assets. Also, this method leads to poor out-of-sample performances. Entropy is a well-known measure of diversity and also has a shrinkage interpretation. In this article, we propose to use cross- entropy measure as the objective function with side conditions coming from the mean and variance-covariance matrix of the resampled asset returns. This automatically captures the degree of imprecision of input estimates. Our approach can be viewed as a shrinkage estimation of portfolio weights (probabilities) which are shrunk towards the predetermined portfolio, for example, equally weighted portfolio or minimum variance portfolio. Our procedure is illustrated with an application to the international equity indexes. Journal: Econometric Reviews Pages: 484-512 Issue: 4-6 Volume: 27 Year: 2008 Keywords: Diversification, Entropy measure, Portfolio selection, Shrinkage rule, Simulation methods, X-DOI: 10.1080/07474930801960394 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930801960394 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:27:y:2008:i:4-6:p:484-512 Template-Type: ReDIF-Article 1.0 Author-Name: Marian Grendar Author-X-Name-First: Marian Author-X-Name-Last: Grendar Author-Name: George Judge Author-X-Name-First: George Author-X-Name-Last: Judge Title: Large-Deviations Theory and Empirical Estimator Choice Abstract: In this article, we consider the problem of criterion choice in information recovery and inference in a large-deviations (LD) context. Kitamura and Stutzer recognize that the Maximum Entropy Empirical Likelihood estimator can be given a LD justification (Kitamura and Stutzer, 2002). We demonstrate there exists a similar LD justification for Owen's Empirical Likelihood estimator (Owen, 2001). We tie the two empirical estimators and related LD theorems to two basic ill-posed inverse problems α and β. We note that other estimators in this family lack an LD footing and provide an extensive discussion of the implications of these results. The appendix contains formal statements regarding relevant LD theorems. Journal: Econometric Reviews Pages: 513-525 Issue: 4-6 Volume: 27 Year: 2008 Keywords: Boltzmann Jaynes inverse problem, Criterion choice problem, Empirical likelihood, Entropy, Information theory, Large deviations, Probabilistic laws, X-DOI: 10.1080/07474930801960402 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930801960402 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:27:y:2008:i:4-6:p:513-525 Template-Type: ReDIF-Article 1.0 Author-Name: Patrik Guggenberger Author-X-Name-First: Patrik Author-X-Name-Last: Guggenberger Title: Finite Sample Evidence Suggesting a Heavy Tail Problem of the Generalized Empirical Likelihood Estimator Abstract: Comprehensive Monte Carlo evidence is provided that compares the finite sample properties of generalized empirical likelihood (GEL) estimators to the ones of k-class estimators in the linear instrumental variables (IV) model. We focus on sample median, mean, mean squared error, and on the coverage probability and length of confidence intervals obtained from inverting a t-statistic based on the various estimators. The results indicate that in terms of the above criteria, all the GEL estimators and the limited information maximum likelihood (LIML) estimator behave very similarly. This suggests that GEL estimators might also share the “no-moment” problem of LIML. At sample sizes as in our Monte Carlo study, there is no systematic bias advantage of GEL estimators over k-class estimators. On the other hand, the standard deviation of GEL estimators is pronouncedly higher than for some of the k-class estimators. Therefore, if mean squared error is used as the underlying loss function, our study suggests the use of computationally simple estimators, such as two-stage least squares, in the linear IV model rather than GEL. Based on the properties of confidence intervals, we cannot recommend the use of GEL estimators either in the linear IV model. Journal: Econometric Reviews Pages: 526-541 Issue: 4-6 Volume: 27 Year: 2008 Keywords: Generalized empirical likelihood estimator, Generalized method of moments, Monte Carlo simulation, No-moment problem, X-DOI: 10.1080/07474930801960410 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930801960410 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:27:y:2008:i:4-6:p:526-541 Template-Type: ReDIF-Article 1.0 Author-Name: Carlos Martins-Filho Author-X-Name-First: Carlos Author-X-Name-Last: Martins-Filho Author-Name: Santosh Mishra Author-X-Name-First: Santosh Author-X-Name-Last: Mishra Author-Name: Aman Ullah Author-X-Name-First: Aman Author-X-Name-Last: Ullah Title: A Class of Improved Parametrically Guided Nonparametric Regression Estimators Abstract: In this article we define a class of estimators for a nonparametric regression model with the aim of reducing bias. The estimators in the class are obtained via a simple two-stage procedure. In the first stage, a potentially misspecified parametric model is estimated and in the second stage the parametric estimate is used to guide the derivation of a final semiparametric estimator. Mathematically, the proposed estimators can be thought as the minimization of a suitably defined Cressie-Read discrepancy that can be shown to produce conventional nonparametric estimators, such as the local polynomial estimator, as well as existing two-stage multiplicative estimators, such as that proposed by Glad (1998). We show that under fairly mild conditions the estimators in the proposed class are [image omitted] asymptotically normal and explore their finite sample (simulation) behavior. Journal: Econometric Reviews Pages: 542-573 Issue: 4-6 Volume: 27 Year: 2008 Keywords: Asymptotic normality, Combined semiparametric estimation, X-DOI: 10.1080/07474930801960444 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930801960444 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:27:y:2008:i:4-6:p:542-573 Template-Type: ReDIF-Article 1.0 Author-Name: Avinash Singh Bhati Author-X-Name-First: Avinash Singh Author-X-Name-Last: Bhati Title: A Generalized Cross-Entropy Approach for Modeling Spatially Correlated Counts Abstract: This article discusses and applies an information-theoretic framework for incorporating knowledge of the spatial structure in a sample while extracting from it information about processes resulting in count outcomes. The framework, an application of the Generalized Cross-Entropy (GCE) method of estimating count outcome models, allows researchers to incorporate such real-world features as unobserved heterogeneity—with or without spatial clustering—when modeling spatially correlated counts. The information-recovering potential of the approach is investigated using a limited set of simulations. It is then used to study the determinants of counts of homicides recorded in 343 neighborhoods in Chicago, Illinois. Journal: Econometric Reviews Pages: 574-595 Issue: 4-6 Volume: 27 Year: 2008 Keywords: Count outcomes, Generalized Cross-Entropy estimation, Homicide rate, Spatial processes, Unobserved heterogeneity, X-DOI: 10.1080/07474930801960451 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930801960451 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:27:y:2008:i:4-6:p:574-595 Template-Type: ReDIF-Article 1.0 Author-Name: R. Bernardini Papalia Author-X-Name-First: R. Bernardini Author-X-Name-Last: Papalia Title: A Composite Generalized Cross-Entropy Formulation in Small Samples Estimation Abstract: This article introduces a maximum entropy-based estimation methodology that can be used both to represent the uncertainty of a partial-incomplete economic data generation process and to consider the direct influence of learning from repeated samples. Then, a composite cross-entropy estimator, incorporating information from a subpopulation based on a small sample and from a population with a larger sample size, is derived. The proposed estimator is employed to estimate the local area expenditure shares of a sub population of Italian households using a system of censored demand equations. Journal: Econometric Reviews Pages: 596-609 Issue: 4-6 Volume: 27 Year: 2008 Keywords: Generalized cross-entropy, Microeconometric models, Repeated samples, Small sample estimation, X-DOI: 10.1080/07474930801960469 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930801960469 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:27:y:2008:i:4-6:p:596-609 Template-Type: ReDIF-Article 1.0 Author-Name: Estela Bee Dagum Author-X-Name-First: Estela Bee Author-X-Name-Last: Dagum Author-Name: Silvano Bordignon Author-X-Name-First: Silvano Author-X-Name-Last: Bordignon Title: Editorial: Special Issue on Statistical Inference on Time Series Stochastic and Deterministic Dynamics Abstract: Journal: Econometric Reviews Pages: 1-3 Issue: 1-3 Volume: 28 Year: 2009 X-DOI: 10.1080/07474930802387720 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930802387720 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:28:y:2009:i:1-3:p:1-3 Template-Type: ReDIF-Article 1.0 Author-Name: Richard Ashley Author-X-Name-First: Richard Author-X-Name-Last: Ashley Author-Name: Randal Verbrugge Author-X-Name-First: Randal Author-X-Name-Last: Verbrugge Title: Frequency Dependence in Regression Model Coefficients: An Alternative Approach for Modeling Nonlinear Dynamic Relationships in Time Series Abstract: This article proposes a new class of nonlinear time series models in which one of the coefficients of an existing regression model is frequency dependent—that is, the relationship between the dependent variable and this explanatory variable varies across its frequency components. We show that such frequency dependence implies that the relationship between the dependent variable and this explanatory variable is nonlinear. Past efforts to detect frequency dependence have not been satisfactory; for example, we note that the two-sided bandpass filtering used in such efforts yields inconsistent estimates of frequency dependence where there is feedback in the relationship. Consequently, we provide an explicit procedure for partitioning an explanatory variable into frequency components using one-sided bandpass filters. This procedure allows us to test for and quantify frequency dependence even where feedback may be present. A distinguishing feature of these new models is their potentially tight connection to macroeconomic theory; indeed, they are perhaps best introduced by reference to the frequency dependence in the marginal propensity to consume posited by the Permanent Income Hypothesis (PIH) of consumption theory. An illustrative empirical application is given, in which the Phillips Curve relationship between inflation and unemployment is found to be negligible at low frequencies, corresponding to periods ≥ 18 months, but inverse at higher frequencies, just as predicted by Friedman and Phelps in the 1960s. Journal: Econometric Reviews Pages: 4-20 Issue: 1-3 Volume: 28 Year: 2009 Keywords: Frequency dependence, Nonlinear dependence, Nonlinear modelling, Phillips Curve, Spectral regression, X-DOI: 10.1080/07474930802387753 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930802387753 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:28:y:2009:i:1-3:p:4-20 Template-Type: ReDIF-Article 1.0 Author-Name: Anthony Atkinson Author-X-Name-First: Anthony Author-X-Name-Last: Atkinson Title: Econometric Applications of the Forward Search in Regression: Robustness, Diagnostics, and Graphics Abstract: The article illustrates the use of the forward search to provide robust analyses of econometric data. The emphasis is on informative plots that reveal the inferential importance of each observation. The division of observations into “good” and “bad” leverage points is shown to be potentially misleading. Journal: Econometric Reviews Pages: 21-39 Issue: 1-3 Volume: 28 Year: 2009 Keywords: Bad leverage point, Fan plot, Leverage, LTS, Outliers, Residuals, Very robust methods, X-DOI: 10.1080/07474930802387803 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930802387803 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:28:y:2009:i:1-3:p:21-39 Template-Type: ReDIF-Article 1.0 Author-Name: Estela Bee Dagum Author-X-Name-First: Estela Bee Author-X-Name-Last: Dagum Author-Name: Alessandra Luati Author-X-Name-First: Alessandra Author-X-Name-Last: Luati Title: A Cascade Linear Filter to Reduce Revisions and False Turning Points for Real Time Trend-Cycle Estimation Abstract: The problem of identifying the direction of the short-term trend (nonstationary mean) of seasonally adjusted series contaminated by high levels of variability has become of relevant interest in recent years. In fact, major financial and economic changes of global character have introduced a large amount of noise in time series data, particularly, in socioeconomic indicators used for real time economic analysis. The aim of this study is to construct a cascade linear filter via the convolution of several noise suppression, trend estimation, and extrapolation linear filters. The cascading approach approximates the steps followed by the nonlinear Dagum (1996) trend-cycle estimator, a modified version of the 13-term Henderson filter. The former consists of first extending the seasonally adjusted series with ARIMA extrapolations, and then applying a very strict replacement of extreme values. The nonlinear Dagum filter has been shown to improve significantly the size of revisions and number of false turning points with respect to H13. We construct a linear approximation of the nonlinear filter because it offers several advantages. For one, its application is direct and hence does not require some knowledge on ARIMA model identification. Furthermore, linear filtering preserves the crucial additive constraint by which the trend of an aggregated variable should be equal to the algebraic addition of its component trends, thus avoiding the selection problem of direct versus indirect adjustments. Finally, the properties of a linear filter concerning signal passing and noise suppression can always be compared to those of other linear filters by means of spectral analysis. Journal: Econometric Reviews Pages: 40-59 Issue: 1-3 Volume: 28 Year: 2009 Keywords: False turning points, Gain function, Smoothing, Symmetric linear filter, 13-Term Henderson filter, X-DOI: 10.1080/07474930802387837 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930802387837 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:28:y:2009:i:1-3:p:40-59 Template-Type: ReDIF-Article 1.0 Author-Name: Silvano Bordignon Author-X-Name-First: Silvano Author-X-Name-Last: Bordignon Author-Name: Massimiliano Caporin Author-X-Name-First: Massimiliano Author-X-Name-Last: Caporin Author-Name: Francesco Lisi Author-X-Name-First: Francesco Author-X-Name-Last: Lisi Title: Periodic Long-Memory GARCH Models Abstract: A distinguishing feature of the intraday time-varying volatility of financial time series is given by the presence of long-range dependence of periodic type, due mainly to time-of-the-day phenomena. In this work, we introduce a model able to describe the empirical evidence given by this periodic long-memory behaviour. The model, named PLM-GARCH (Periodic Long-Memory GARCH), represents a natural extension of the FIGARCH model proposed for modelling long-range persistence of volatility. Periodic long memory versions of EGARCH (PLM-EGARCH) and of Log-GARCH (PLM-LGARCH) models are also examined. Some properties and characteristics of the models are given and finite sample performance of quasi-maximum likelihood estimation are studied with Monte Carlo simulations. Further possible extensions of the model to take into account multiple sources of periodic long-memory behaviour are proposed. Two empirical applications on intra-day financial time series are also provided. Journal: Econometric Reviews Pages: 60-82 Issue: 1-3 Volume: 28 Year: 2009 Keywords: GARCH models, Intra-day volatility, Long-memory, Periodicity, X-DOI: 10.1080/07474930802387860 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930802387860 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:28:y:2009:i:1-3:p:60-82 Template-Type: ReDIF-Article 1.0 Author-Name: Yongjae Kwon Author-X-Name-First: Yongjae Author-X-Name-Last: Kwon Author-Name: Hamparsum Bozdogan Author-X-Name-First: Hamparsum Author-X-Name-Last: Bozdogan Author-Name: Halima Bensmail Author-X-Name-First: Halima Author-X-Name-Last: Bensmail Title: Performance of Model Selection Criteria in Bayesian Threshold VAR (TVAR) Models Abstract: This article presents a new Bayesian modeling and information-theoretic model selection criteria for threshold vector autoregressive (TVAR) models. The analytical framework of Bayesian modeling for threshold VAR models are developed. Markov Chain Monte Carlo (MCMC) simulation and importance/rejection sampling methods are used to estimate the parameters of the model and to obtain posterior samples. We propose reliable modeling procedures using Bayes factor, and the information-theoretic model selection criteria such as, Akaike's (1973) Information Criterion (AIC), Schwarz (1978) Bayesian Criterion (SBC), Information Complexity (ICOMP) Criterion of Bozdogan (1990, 1994, 2000), Extended Consistent (AIC) with Fisher Information (CAICFE), and the new Bayesian Model Selection (BMS) Criterion of Bozdogan and Ueno (2000). We study the performance of these criteria under different design of the simulation protocol with varying sample sizes in TVAR models. Our results show that these criteria perform well in small sample as well as large samples to avoid heavy computational burden in conventional procedures. Journal: Econometric Reviews Pages: 83-101 Issue: 1-3 Volume: 28 Year: 2009 Keywords: Bayesian modeling, Information-theoretic model selection criteria and model selection, Threshold autoregressive models, X-DOI: 10.1080/07474930802387894 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930802387894 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:28:y:2009:i:1-3:p:83-101 Template-Type: ReDIF-Article 1.0 Author-Name: Giovanni Luca Author-X-Name-First: Giovanni Author-X-Name-Last: Luca Author-Name: Giampiero Gallo Author-X-Name-First: Giampiero Author-X-Name-Last: Gallo Title: Time-Varying Mixing Weights in Mixture Autoregressive Conditional Duration Models Abstract: Financial market price formation and exchange activity can be investigated by means of ultra-high frequency data. In this article, we investigate an extension of the Autoregressive Conditional Duration (ACD) model of Engle and Russell (1998) by adopting a mixture of distribution approach with time-varying weights. Empirical estimation of the Mixture ACD model shows that the limitations of the standard base model and its inadequacy of modelling the behavior in the tail of the distribution are suitably solved by our model. When the weights are made dependent on some market activity data, the model lends itself to some structural interpretation related to price formation and information diffusion in the market. Journal: Econometric Reviews Pages: 102-120 Issue: 1-3 Volume: 28 Year: 2009 Keywords: Autoregressive, Conditional Durations, Financial durations, Mixture of distributions, Time-varying weights, X-DOI: 10.1080/07474930802387944 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930802387944 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:28:y:2009:i:1-3:p:102-120 Template-Type: ReDIF-Article 1.0 Author-Name: Søren Johansen Author-X-Name-First: Søren Author-X-Name-Last: Johansen Title: Representation of Cointegrated Autoregressive Processes with Application to Fractional Processes Abstract: We analyze vector autoregressive processes using the matrix valued characteristic polynomial. The purpose of this article is to give a survey of the mathematical results on inversion of a matrix polynomial in case there are unstable roots, to study integrated and cointegrated processes. The new results are in the I(2) representation, which contains explicit formulas for the first two terms and a useful property of the third. We define a new error correction model for fractional processes and derive a representation of the solution. Journal: Econometric Reviews Pages: 121-145 Issue: 1-3 Volume: 28 Year: 2009 Keywords: Error correction models, Fractional autoregressive model, Granger representation, Integration of order 1 and 2, X-DOI: 10.1080/07474930802387977 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930802387977 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:28:y:2009:i:1-3:p:121-145 Template-Type: ReDIF-Article 1.0 Author-Name: Fabrizio Laurini Author-X-Name-First: Fabrizio Author-X-Name-Last: Laurini Author-Name: Jonathan Tawn Author-X-Name-First: Jonathan Author-X-Name-Last: Tawn Title: Regular Variation and Extremal Dependence of GARCH Residuals with Application to Market Risk Measures Abstract: Stock returns exhibit heavy tails and volatility clustering. These features, motivating the use of GARCH models, make it difficult to predict times and sizes of losses that might occur. Estimation of losses, like the Value-at-Risk, often assume that returns, normalized by the level of volatility, are Gaussian. Often under ARMA-GARCH modeling, such scaled returns are heavy tailed and show extremal dependence, whose strength reduces when increasing extreme levels. We model heavy tails of scaled returns with generalized Pareto distributions, while extremal dependence can be reduced by declustering data. Journal: Econometric Reviews Pages: 146-169 Issue: 1-3 Volume: 28 Year: 2009 Keywords: Declustering, Expected shortfalls, Extremal dependence, Generalized Pareto distribution, Regular variation, Value-at-Risk, X-DOI: 10.1080/07474930802387985 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930802387985 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:28:y:2009:i:1-3:p:146-169 Template-Type: ReDIF-Article 1.0 Author-Name: Cristiano Varin Author-X-Name-First: Cristiano Author-X-Name-Last: Varin Author-Name: Paolo Vidoni Author-X-Name-First: Paolo Author-X-Name-Last: Vidoni Title: Pairwise Likelihood Inference for General State Space Models Abstract: This article concerns parameter estimation for general state space models, following a frequentist likelihood-based approach. Since exact methods for computing and maximizing the likelihood function are usually not feasible, approximate solutions, based on Monte Carlo or numerical methods, have to be considered. Here, we concentrate on a different approach based on a simple pseudolikelihood, called “pairwise likelihood.” Its merit is to reduce the computational burden so that it is possible to fit highly structured statistical models, even when the use of standard likelihood methods is not possible. We discuss pairwise likelihood inference for state space models, and we present some touchstone examples concerning autoregressive models with additive observation noise and switching regimes, the local level model and a non-Makovian generalization of the dynamic Tobit model. Journal: Econometric Reviews Pages: 170-185 Issue: 1-3 Volume: 28 Year: 2009 Keywords: Composite likelihood, Efficiency, Pairwise likelihood, Pseudolikelihood, Regime switching, State space model, Tobit model, X-DOI: 10.1080/07474930802388009 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930802388009 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:28:y:2009:i:1-3:p:170-185 Template-Type: ReDIF-Article 1.0 Author-Name: Tommaso Proietti Author-X-Name-First: Tommaso Author-X-Name-Last: Proietti Title: On the Model-Based Interpretation of Filters and the Reliability of Trend-Cycle Estimates Abstract: The article explores and illustrates some of the typical trade-offs which arise in designing filters for the measurement of trends and cycles in economic time series, focusing, in particular, on the fundamental trade-off between the reliability of the estimates and the magnitude of the revisions as new observations become available. This assessment is available through a novel model based approach, according to which an important class of highpass and bandpass filters, encompassing the Hodrick-Prescott (HP) filter, are adapted to the particular time series under investigation. Via a suitable decomposition of the innovation process, it is shown that any linear time series with ARIMA representation can be broken down into orthogonal trend and cycle components, for which the class of filters is optimal. The main results then follow from Wiener-Kolmogorov (WK) signal extraction theory, whereas exact finite sample inferences are provided by the Kalman filter and smoother for the relevant state space representation of the decomposition. Journal: Econometric Reviews Pages: 186-208 Issue: 1-3 Volume: 28 Year: 2009 Keywords: Bandpass filters, Kalman filter and Smoother, Revisions, Signal extraction, X-DOI: 10.1080/07474930802388025 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930802388025 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:28:y:2009:i:1-3:p:186-208 Template-Type: ReDIF-Article 1.0 Author-Name: Matteo Grigoletto Author-X-Name-First: Matteo Author-X-Name-Last: Grigoletto Author-Name: Corrado Provasi Author-X-Name-First: Corrado Author-X-Name-Last: Provasi Title: Misspecification Testing for the Conditional Distribution Model in GARCH-Type Processes Abstract: In this article, we study goodness of fit tests for some distributions of the innovations which are usually adopted to explain the behavior of financial time series. Inference is developed in the context of GARCH-type models. Functional bootstrap tests are employed, assuming that the conditional means and variances of the model are correctly specified. The performances of the functional tests are assessed with a Monte Carlo experiment, based on some of the most common distributions adopted in the financial framework. The results of an application to the series of squared residuals from a PARCH(1,1) model fitted to a series of foreign exchange rates returns are also shown. Journal: Econometric Reviews Pages: 209-224 Issue: 1-3 Volume: 28 Year: 2009 Keywords: Bootstrap, Functional tests, GARCH model, Goodness of fit, X-DOI: 10.1080/07474930802388033 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930802388033 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:28:y:2009:i:1-3:p:209-224 Template-Type: ReDIF-Article 1.0 Author-Name: Changli He Author-X-Name-First: Changli Author-X-Name-Last: He Author-Name: Timo Terasvirta Author-X-Name-First: Timo Author-X-Name-Last: Terasvirta Author-Name: Andres Gonzalez Author-X-Name-First: Andres Author-X-Name-Last: Gonzalez Title: Testing Parameter Constancy in Stationary Vector Autoregressive Models Against Continuous Change Abstract: In this article we derive a parameter constancy test of a stationary vector autoregressive model against the hypothesis that the parameters of the model change smoothly over time. A single structural break is contained in this alternative hypothesis as a special case. The test is a generalization of a single-equation test of a similar hypothesis proposed in the literature. An advantage here is that the asymptotic distribution theory is standard. The performance of the tests is compared to that of generalized Chow-tests and found satisfactory in terms of both size and power. Journal: Econometric Reviews Pages: 225-245 Issue: 1-3 Volume: 28 Year: 2009 Keywords: JEL, C32, C12, X-DOI: 10.1080/07474930802388041 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930802388041 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:28:y:2009:i:1-3:p:225-245 Template-Type: ReDIF-Article 1.0 Author-Name: Esfandiar Maasoumi Author-X-Name-First: Esfandiar Author-X-Name-Last: Maasoumi Author-Name: Jeffrey Racine Author-X-Name-First: Jeffrey Author-X-Name-Last: Racine Title: A Robust Entropy-Based Test of Asymmetry for Discrete and Continuous Processes Abstract: We consider a metric entropy capable of detecting deviations from symmetry that is suitable for both discrete and continuous processes. A test statistic is constructed from an integrated normed difference between nonparametric estimates of two density functions. The null distribution (symmetry) is obtained by resampling from an artificially lengthened series constructed from a rotation of the original series about its mean (median, mode). Simulations demonstrate that the test has correct size and good power in the direction of interesting alternatives, while applications to updated Nelson and Plosser (1982) data demonstrate its potential power gains relative to existing tests. Journal: Econometric Reviews Pages: 246-261 Issue: 1-3 Volume: 28 Year: 2009 Keywords: Entropy, Kernel, Metric, Nonparametric, Symmetry, Time series, X-DOI: 10.1080/07474930802388066 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930802388066 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:28:y:2009:i:1-3:p:246-261 Template-Type: ReDIF-Article 1.0 Author-Name: Marco Riani Author-X-Name-First: Marco Author-X-Name-Last: Riani Title: Robust Transformations in Univariate and Multivariate Time Series Abstract: It is well known that transformation of the response may improve the homogeneity and the approximate normality of the errors. Unfortunately, the estimated transformation and related test statistic may be sensitive to the presence of one, or several, atypical observations. In addition, it is important to remark that outliers in one transformed scale may not be atypical in another scale. Therefore, it is important to choose a transformation which does not depend on the presence of particular observations. In this article we suggest an efficient procedure based on a robust score test statistic which quantifies the effect of each observation on the choice of the transformation. Journal: Econometric Reviews Pages: 262-278 Issue: 1-3 Volume: 28 Year: 2009 Keywords: Fan plot, Forward search, Kalman filter, Outlier detection, Robust methods, Score test, X-DOI: 10.1080/07474930802388074 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930802388074 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:28:y:2009:i:1-3:p:262-278 Template-Type: ReDIF-Article 1.0 Author-Name: Elena Rusticelli Author-X-Name-First: Elena Author-X-Name-Last: Rusticelli Author-Name: Richard Ashley Author-X-Name-First: Richard Author-X-Name-Last: Ashley Author-Name: Estela Bee Dagum Author-X-Name-First: Estela Bee Author-X-Name-Last: Dagum Author-Name: Douglas Patterson Author-X-Name-First: Douglas Author-X-Name-Last: Patterson Title: A New Bispectral Test for NonLinear Serial Dependence Abstract: Nonconstancy of the bispectrum of a time series has been taken as a measure of non-Gaussianity and nonlinear serial dependence in a stochastic process by Subba Rao and Gabr (1980) and by Hinich (1982), leading to Hinich's statistical test of the null hypothesis of a linear generating mechanism for a time series. Hinich's test has the advantage of focusing directly on nonlinear serial dependence—in contrast to subsequent approaches, which actually test for serial dependence of any kind (nonlinear or linear) on data which have been pre-whitened. The Hinich test tends to have low power, however, and (in common with most statistical procedures in the frequency domain) requires the specification of a smoothing or window-width parameter. In this article, we develop a modification of the Hinich bispectral test which substantially ameliorates both of these problems by the simple expedient of maximizing the test statistic over the feasible values of the smoothing parameter. Monte Carlo simulation results are presented indicating that the new test is well sized and has substantially larger power than the original Hinich test against a number of relevant alternatives; the simulations also indicate that the new test preserves the Hinich test's robustness to misspecifications in the identification of a pre-whitening model. Journal: Econometric Reviews Pages: 279-293 Issue: 1-3 Volume: 28 Year: 2009 Keywords: Bispectrum, Linear prefiltering procedure, Maximization technique, Nonlinearity, Smoothing parameter, X-DOI: 10.1080/07474930802388090 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930802388090 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:28:y:2009:i:1-3:p:279-293 Template-Type: ReDIF-Article 1.0 Author-Name: Claude Lopez Author-X-Name-First: Claude Author-X-Name-Last: Lopez Title: A Panel Unit Root Test with Good Power in Small Samples Abstract: We propose a new pooled panel unit root test allowing for serial and contemporaneous correlation. The test combines Elliott et al. (1996) local-to-unity transformation with a pooled panel ADF test, and accounts for contemporaneous correlation by estimating the residual covariance matrix. The critical values are bootstrapped and Monte Carlo simulations demonstrate enhanced performances, especially when the series are highly persistent and the panel cross-sectional and time series dimensions are relatively small. An application of the test to the real exchange rate convergence for the post Bretton-Woods period leads to strong and reliable rejections of the unit root. Journal: Econometric Reviews Pages: 295-313 Issue: 4 Volume: 28 Year: 2009 Keywords: Bootstrap test, GLS-detrending, Panel unit root test, X-DOI: 10.1080/07474930802458620 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930802458620 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:28:y:2009:i:4:p:295-313 Template-Type: ReDIF-Article 1.0 Author-Name: D. M. Mahinda Samarakoon Author-X-Name-First: D. M. Mahinda Author-X-Name-Last: Samarakoon Author-Name: Keith Knight Author-X-Name-First: Keith Author-X-Name-Last: Knight Title: A Note on Unit Root Tests with Infinite Variance Noise Abstract: In recent years, a number of authors have considered extensions of classical unit root tests to cases where the process is driven by infinite variance innovations, as well as considering their asymptotic properties. Unfortunately, these extensions are typically inefficient as they do not exploit the dynamics of the infinite variance process. In this article, we consider Dickey-Fuller-type tests based on M-estimators and develop the asymptotic theory for these estimators and resulting test statistics. Journal: Econometric Reviews Pages: 314-334 Issue: 4 Volume: 28 Year: 2009 Keywords: Infinite variance, M-estimators, Stable laws, Unit roots, X-DOI: 10.1080/07474930802458638 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930802458638 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:28:y:2009:i:4:p:314-334 Template-Type: ReDIF-Article 1.0 Author-Name: Daiki Maki Author-X-Name-First: Daiki Author-X-Name-Last: Maki Title: Tests for a Unit Root Using Three-Regime TAR Models: Power Comparison and Some Applications Abstract: Tests for a unit root using three-regime threshold autoregressive (TAR) models play a significant role in the empirical analysis of some economic theories. This article compares the powers of recently proposed unit root tests in three-regime TAR models using Monte Carlo experiments. The following results are obtained from the Monte Carlo simulations: Kapetanios and Shin's (2006) Wsup, Wave, and Wexp statistics, which degenerate with respect to the threshold parameters under the null hypothesis, have a better power in the three-regime TAR process with a relatively narrow band of a unit root process and a small sample, whereas their statistics do not perform well when the threshold and sample size increase; Bec et al.'s (2004, BBC) sup W and Park and Shintani's (2005) inf-t statistics and their restricted models, which do not degenerate with respect to the threshold parameters in the limit, perform poorly in the three-regime TAR process with a small threshold even when compared with the Dickey-Fuller test, whereas their statistics perform better in the case of a large threshold; sup W, inf-t, and their restricted models perform much better when the sample size and threshold increase and the outer regimes have a rapid convergence. In order to substantiate the use of our Monte Carlo results for some of the applied work, we apply these tests to the real exchange rates for many countries. Journal: Econometric Reviews Pages: 335-363 Issue: 4 Volume: 28 Year: 2009 Keywords: Power, Three-regime TAR model, Unit root test, X-DOI: 10.1080/07474930802458893 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930802458893 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:28:y:2009:i:4:p:335-363 Template-Type: ReDIF-Article 1.0 Author-Name: Giuseppe Cavaliere Author-X-Name-First: Giuseppe Author-X-Name-Last: Cavaliere Author-Name: A. M. Robert Taylor Author-X-Name-First: A. M. Robert Author-X-Name-Last: Taylor Title: A Note on Testing Covariance Stationarity Abstract: In a recent article, Xiao and Lima (2007) show numerically that the stationarity test of Kwiatkowski et al. (1992) has power close to size when the volatility of the innovation process follows a linear trend. In this article, highlighting published results in Cavaliere and Taylor (2005), we show that this observation does not in general hold under time-varying volatility. We also propose alternative tests of covariance stationarity which we show to improve upon the power properties of the tests proposed in Xiao and Lima (2007) against changes in the unconditional variance. Practical recommendations are also made. Journal: Econometric Reviews Pages: 364-371 Issue: 4 Volume: 28 Year: 2009 Keywords: KPSS, Nonstationary volatility, Stationarity testing, X-DOI: 10.1080/07474930802458992 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930802458992 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:28:y:2009:i:4:p:364-371 Template-Type: ReDIF-Article 1.0 Author-Name: Andrew Patton Author-X-Name-First: Andrew Author-X-Name-Last: Patton Author-Name: Dimitris Politis Author-X-Name-First: Dimitris Author-X-Name-Last: Politis Author-Name: Halbert White Author-X-Name-First: Halbert Author-X-Name-Last: White Title: Correction to “Automatic Block-Length Selection for the Dependent Bootstrap” by D. Politis and H. White Abstract: A correction on the optimal block size algorithms of Politis and White (2004) is given following a correction of Lahiri's (Lahiri 1999) theoretical results by Nordman (2008). Journal: Econometric Reviews Pages: 372-375 Issue: 4 Volume: 28 Year: 2009 Keywords: Block bootstrap, Block size, Circular bootstrap, Stationary bootstrap, X-DOI: 10.1080/07474930802459016 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930802459016 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:28:y:2009:i:4:p:372-375 Template-Type: ReDIF-Article 1.0 Author-Name: Jesus Fernandez-Villaverde Author-X-Name-First: Jesus Author-X-Name-Last: Fernandez-Villaverde Author-Name: Juan Rubio-Ramirez Author-X-Name-First: Juan Author-X-Name-Last: Rubio-Ramirez Title: Two Books on the New Macroeconometrics Abstract: Methods for Applied Macroeconomics Research by Fabio Canova, and Structural Macroeconometrics by David N. DeJong and Chetan Dave are two outstanding new books that provide an excellent introduction to what is sometimes called the New Macroeconometrics. This area of empirical macroeconomics is centered on the estimation and validation of dynamic stochastic general equilibrium (DSGE) models. Canova's and DeJong and Dave's volumes fill a tremendous gap in economists' libraries. Not only does the writing style of both books allow them to be adopted as a reference text for a class, but also the books come filled with applications, exercises, and pointers to computer code that will complement the lectures. Despite sharing the common theme of an introduction to the new macroeconometrics, each book has its own focus. Canova's book aims to survey a long list of techniques relevant to macroeconomists: filters, vector autoregressions (VARs), general method of moments (GMM), simulation methods, dynamic panels, maximum likelihood, and Bayesian econometrics; it also offers two preliminary chapters on probability theory and on DSGE modeling. In contrast, DeJong and Dave have the more modest goal of showing how to compute and estimate DSGE models, which makes it more suitable for a second year graduate class. In exchange, DeJong and Dave often dig a bit deeper into issues of interest to them and build the material at a more leisurely pace. Journal: Econometric Reviews Pages: 376-387 Issue: 4 Volume: 28 Year: 2009 Keywords: Bayesian econometrics, Dynamic macroeconomic models, Likelihood function, Monte Carlo methods, New macroeconometrics, X-DOI: 10.1080/07474930802459040 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930802459040 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:28:y:2009:i:4:p:376-387 Template-Type: ReDIF-Article 1.0 Author-Name: Tong Li Author-X-Name-First: Tong Author-X-Name-Last: Li Title: Book Review Abstract: Journal: Econometric Reviews Pages: 388-392 Issue: 4 Volume: 28 Year: 2009 X-DOI: 10.1080/07474930802459073 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930802459073 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:28:y:2009:i:4:p:388-392 Template-Type: ReDIF-Article 1.0 Author-Name: Giuseppe Cavaliere Author-X-Name-First: Giuseppe Author-X-Name-Last: Cavaliere Author-Name: A. M. Robert Taylor Author-X-Name-First: A. M. Author-X-Name-Last: Robert Taylor Title: Bootstrap M Unit Root Tests Abstract: In this article we propose wild bootstrap implementations of the local generalized least squares (GLS) de-trended M and ADF unit root tests of Stock (1999), Ng and Perron (2001), and Elliott et al. (1996), respectively. The bootstrap statistics are shown to replicate the first-order asymptotic distributions of the original statistics, while numerical evidence suggests that the bootstrap tests perform well in small samples. A recolored version of our bootstrap is also proposed which can further improve upon the finite sample size properties of the procedure when the shocks are serially correlated, in particular ameliorating the significant under-size seen in the M tests against processes with autoregressive or moving average roots close to -1. The wild bootstrap is used because it has the desirable property of preserving in the resampled data the pattern of heteroskedasticity present in the original shocks, thereby allowing for cases where the series under test is driven by martingale difference innovations. Journal: Econometric Reviews Pages: 393-421 Issue: 5 Volume: 28 Year: 2009 Keywords: Conditional heteroskedasticity, Re-colouring, Unit root tests, Wild bootstrap, X-DOI: 10.1080/07474930802467167 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930802467167 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:28:y:2009:i:5:p:393-421 Template-Type: ReDIF-Article 1.0 Author-Name: Michael McAleer Author-X-Name-First: Michael Author-X-Name-Last: McAleer Author-Name: Suhejla Hoti Author-X-Name-First: Suhejla Author-X-Name-Last: Hoti Author-Name: Felix Chan Author-X-Name-First: Felix Author-X-Name-Last: Chan Title: Structure and Asymptotic Theory for Multivariate Asymmetric Conditional Volatility Abstract: Various univariate and multivariate models of volatility have been used to evaluate market risk, asymmetric shocks, thresholds, leverage effects, and Value-at-Risk in economics and finance. This article is concerned with market risk, and develops a constant conditional correlation vector ARMA-asymmetric GARCH (VARMA-AGARCH) model, as an extension of the widely used univariate asymmetric (or threshold) GJR model of Glosten et al. (1992), and establishes its underlying structure, including the unique, strictly stationary, and ergodic solution of the model, its causal expansion, and convenient sufficient conditions for the existence of moments. Alternative empirically verifiable sufficient conditions for the consistency and asymptotic normality of the quasi-maximum likelihood estimator are established under non-normality of the standardized shocks. Journal: Econometric Reviews Pages: 422-440 Issue: 5 Volume: 28 Year: 2009 Keywords: Asymmetric effects, Asymptotic theory, Conditional volatility, Multivariate structure, Regularity conditions, X-DOI: 10.1080/07474930802467217 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930802467217 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:28:y:2009:i:5:p:422-440 Template-Type: ReDIF-Article 1.0 Author-Name: Kenneth West Author-X-Name-First: Kenneth Author-X-Name-Last: West Author-Name: Ka-fu Wong Author-X-Name-First: Ka-fu Author-X-Name-Last: Wong Author-Name: Stanislav Anatolyev Author-X-Name-First: Stanislav Author-X-Name-Last: Anatolyev Title: Instrumental Variables Estimation of Heteroskedastic Linear Models Using All Lags of Instruments Abstract: We propose and evaluate a technique for instrumental variables estimation of linear models with conditional heteroskedasticity. The technique uses approximating parametric models for the projection of right-hand side variables onto the instrument space, and for conditional heteroskedasticity and serial correlation of the disturbance. Use of parametric models allows one to exploit information in all lags of instruments, unconstrained by degrees of freedom limitations. Analytical calculations and simulations indicate that sometimes there are large asymptotic and finite sample efficiency gains relative to conventional estimators (Hansen, 1982), and modest gains or losses depending on data generating process and sample size relative to quasi-maximum likelihood. These results are robust to minor misspecification of the parametric models used by our estimator. [Supplemental materials are available for this article. Go to the publisher's online edition of Econometric Reviews for the following free supplemental resources: two appendices containing additional results from this article.] Journal: Econometric Reviews Pages: 441-467 Issue: 5 Volume: 28 Year: 2009 Keywords: Efficiency, Efficiency bounds, Instrumental variables, Optimal instrument, Stationary time series, X-DOI: 10.1080/07474930802467241 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930802467241 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:28:y:2009:i:5:p:441-467 Template-Type: ReDIF-Article 1.0 Author-Name: Simon Broda Author-X-Name-First: Simon Author-X-Name-Last: Broda Author-Name: Kai Carstensen Author-X-Name-First: Kai Author-X-Name-Last: Carstensen Author-Name: Marc Paolella Author-X-Name-First: Marc Author-X-Name-Last: Paolella Title: Assessing and Improving the Performance of Nearly Efficient Unit Root Tests in Small Samples Abstract: The development of unit root tests continues unabated, with many recent contributions using techniques such as generalized least squares (GLS) detrending and recursive detrending to improve the power of the test. In this article, the relation between the seemingly disparate tests is demonstrated by algebraically nesting all of them as ratios of quadratic forms in normal variables. By doing so, and using the exact sampling distribution of the ratio, it is straightforward to compute, examine, and compare the test' critical values and power functions. It is shown that use of GLS detrending parameters other than those recommended in the literature can lead to substantial power improvements. The open and important question regarding the nature of the first observation is addressed. Tests with high power are proposed irrespective of the distribution of the initial observation, which should be of great use in practical applications. Journal: Econometric Reviews Pages: 468-494 Issue: 5 Volume: 28 Year: 2009 Keywords: GLS detrending, Power loss, Recursive detrending, X-DOI: 10.1080/07474930802467282 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930802467282 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:28:y:2009:i:5:p:468-494 Template-Type: ReDIF-Article 1.0 Author-Name: M. Hashem Pesaran Author-X-Name-First: M. Hashem Author-X-Name-Last: Pesaran Author-Name: Ron Smith Author-X-Name-First: Ron Author-X-Name-Last: Smith Author-Name: Takashi Yamagata Author-X-Name-First: Takashi Author-X-Name-Last: Yamagata Author-Name: Lyudmyla Hvozdyk Author-X-Name-First: Lyudmyla Author-X-Name-Last: Hvozdyk Title: Pairwise Tests of Purchasing Power Parity Abstract: Given nominal exchange rates and price data on N + 1 countries indexed by i = 0,1,2,…, N, the standard procedure for testing purchasing power parity (PPP) is to apply unit root or stationarity tests to N real exchange rates all measured relative to a base country, 0, often taken to be the U.S. Such a procedure is sensitive to the choice of base country, ignores the information in all the other cross-rates and is subject to a high degree of cross-section dependence which has adverse effects on estimation and inference. In this article, we conduct a variety of unit root tests on all possible N(N + 1)/2 real rates between pairs of the N + 1 countries and estimate the proportion of the pairs that are stationary. This proportion can be consistently estimated even in the presence of cross-section dependence. We estimate this proportion using quarterly data on the real exchange rate for 50 countries over the period 1957-2001. The main substantive conclusion is that to reject the null of no adjustment to PPP requires sufficiently large disequilibria to move the real rate out of the band of inaction set by trade costs. In such cases, one can reject the null of no adjustment to PPP up to 90% of the time as compared to around 40% in the whole sample using a linear alternative and almost 60% using a nonlinear alternative. Journal: Econometric Reviews Pages: 495-521 Issue: 6 Volume: 28 Year: 2009 Keywords: Cross-rates, Cross-section dependence, Pairwise approach, Panel data, Purchasing power parity, X-DOI: 10.1080/07474930802473702 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930802473702 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:28:y:2009:i:6:p:495-521 Template-Type: ReDIF-Article 1.0 Author-Name: Suhejla Hoti Author-X-Name-First: Suhejla Author-X-Name-Last: Hoti Author-Name: Esfandiar Maasoumi Author-X-Name-First: Esfandiar Author-X-Name-Last: Maasoumi Author-Name: Michael McAleer Author-X-Name-First: Michael Author-X-Name-Last: McAleer Author-Name: Daniel Slottje Author-X-Name-First: Daniel Author-X-Name-Last: Slottje Title: Measuring the Volatility in U.S. Treasury Benchmarks and Debt Instruments Abstract: As U.S. Treasury securities carry the full faith and credit of the U.S. government, they are free of default risk. Thus, their yields are risk-free rates of return, which allows the most recently issued U.S. Treasury securities to be used as a benchmark to price other fixed-income instruments. This article analyzes the time series properties of interest rates on U.S. Treasury benchmarks and related debt instruments by modelling the conditional mean and conditional volatility for weekly yields on 12 Treasury Bills and other debt instruments for the period January 8, 1982 to August 20, 2004. The conditional correlations between all pairs of debt instruments are also calculated. These estimates are of interest as they enable an assessment of the implications of modelling conditional volatility on forecasting performance. The estimated conditional correlation coefficients indicate whether there is specialization, diversification, or independence in the debt instrument shocks. Constant conditional correlation estimates of the standardized shocks indicate that the shocks to the first differences in the debt instrument yields are generally high and always positively correlated. In general, the primary purpose in holding a portfolio of Treasury Bills and other debt instruments should be to specialize on instruments that provide the largest returns. Tests for Stochastic Dominance are generally consistent with these findings, but find somewhat surprising rankings between debt instruments, with implications for portfolio composition. Thirty year treasuries, Aaa bonds, and mortgages tend to dominate the other instruments, at least to the second order. Journal: Econometric Reviews Pages: 522-554 Issue: 6 Volume: 28 Year: 2009 Keywords: Asymmetry, Conditional correlation, Conditional volatility, Debt instruments, Diversification, Forecasting, Independence, Risk, Specialization, Treasury bills, X-DOI: 10.1080/07474930802473736 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930802473736 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:28:y:2009:i:6:p:522-554 Template-Type: ReDIF-Article 1.0 Author-Name: Joseph Terza Author-X-Name-First: Joseph Author-X-Name-Last: Terza Title: Parametric Nonlinear Regression with Endogenous Switching Abstract: Based on the insightful work of Olsen (1980) for the linear context, a generic and unifying framework is developed that affords a simple extension of the classical method of Heckman (1974, 1976, 1978, 1979) to a broad class of nonlinear regression models involving endogenous switching and its two most common incarnations, endogenous sample selection and endogenous treatment effects. The approach should be appealing to applied researchers for three reasons. First, econometric applications involving endogenous switching abound. Secondly, the approach requires neither linearity of the regression function nor full parametric specification of the model. It can, in fact, be applied under the minimal parametric assumptions—i.e., specification of only the conditional means of the outcome and switching variables. Finally, it is amenable to relatively straightforward estimation methods. Examples of applications of the method are discussed. Journal: Econometric Reviews Pages: 555-580 Issue: 6 Volume: 28 Year: 2009 Keywords: Sample selection, Treatment effects, Two-stage estimation, X-DOI: 10.1080/07474930802473751 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930802473751 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:28:y:2009:i:6:p:555-580 Template-Type: ReDIF-Article 1.0 Author-Name: Gonzalo Camba-Mendez Author-X-Name-First: Gonzalo Author-X-Name-Last: Camba-Mendez Author-Name: George Kapetanios Author-X-Name-First: George Author-X-Name-Last: Kapetanios Title: Statistical Tests and Estimators of the Rank of a Matrix and Their Applications in Econometric Modelling Abstract: Testing and estimating the rank of a matrix of estimated parameters is key in a large variety of econometric modelling scenarios. This article describes general methods to test for and estimate the rank of a matrix, and provides details on a variety of modelling scenarios in the econometrics literature where such methods are required. Four different methods to test for the true rank of a general matrix are described, as well as one method that can handle the case of a matrix subject to parameter constraints associated with defineteness structures. The technical requirements for the implementation of the tests of rank of a general matrix differ and hence there are merits to all of them that justify their use in applied work. Nonetheless, we review available evidence of their small sample properties in the context of different modelling scenarios where all, or some, are applicable. Journal: Econometric Reviews Pages: 581-611 Issue: 6 Volume: 28 Year: 2009 Keywords: Model specification, Multiple time series, Tests of rank, X-DOI: 10.1080/07474930802473785 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930802473785 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:28:y:2009:i:6:p:581-611 Template-Type: ReDIF-Article 1.0 Author-Name: Christian Hafner Author-X-Name-First: Christian Author-X-Name-Last: Hafner Author-Name: Philip Hans Franses Author-X-Name-First: Philip Hans Author-X-Name-Last: Franses Title: A Generalized Dynamic Conditional Correlation Model: Simulation and Application to Many Assets Abstract: In this article, we put forward a generalization of the Dynamic Conditional Correlation (DCC) Model of Engle (2002). Our model allows for asset-specific correlation sensitivities, which is useful in particular if one aims to summarize a large number of asset returns. We propose two estimation methods, one based on a full likelihood maximization, the other on individual correlation estimates. The resultant generalized DCC (GDCC) model is considered for daily data on 39 U.K. stock returns in the FTSE. We find convincing evidence that the GDCC model improves on the DCC model and also on the CCC model of Bollerslev (1990). Journal: Econometric Reviews Pages: 612-631 Issue: 6 Volume: 28 Year: 2009 Keywords: Dynamic conditional correlation, Multivariate GARCH, X-DOI: 10.1080/07474930903038834 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930903038834 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:28:y:2009:i:6:p:612-631 Template-Type: ReDIF-Article 1.0 Author-Name: Bo Li Author-X-Name-First: Bo Author-X-Name-Last: Li Title: Asymptotically Distribution-Free Goodness-of-Fit Testing: A Unifying View Abstract: We outline a general paradigm for constructing asymptotically distribution-free (ADF) goodness-of-fit tests, which can be regarded as a generalization of Khmaladze (1993). This is achieved by a nonorthogonal projection of a class of functions onto the ortho-complement of the extended tangent space (ETS) associated with the null hypothesis. In parallel with the work of Bickel et al. (2006), we obtain transformed empirical processes (TEP) which are the building blocks for constructing omnibus tests such as the usual Kolmogorov-Smirnov type tests and Cramer-von Mise type tests, as well as Portmanteau tests and directional tests. The critical values can be tabulated due to the ADF property. All the tests are capable of detecting local (Pitman) alternative at the root-n scale. We shall illustrate the framework in several examples, mostly in regression model specification testing. Journal: Econometric Reviews Pages: 632-657 Issue: 6 Volume: 28 Year: 2009 Keywords: ADF, Empirical process, Goodness-of-fit tests, Martingale transform, Semiparametric, Tangent space, X-DOI: 10.1080/07474930903038933 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930903038933 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:28:y:2009:i:6:p:632-657 Template-Type: ReDIF-Article 1.0 Author-Name: Youngki Shin Author-X-Name-First: Youngki Author-X-Name-Last: Shin Title: Length-bias Correction in Transformation Models with Supplementary Data Abstract: In this article, I propose an inferential procedure of monotone transformation models with random truncation points, which may not be observable. This class includes length-biased samples that are common in duration analysis. The proposed estimator can be applied to more general situations than existing estimators, since it imposes restrictions on neither the transformation function nor the error terms. Furthermore, it does not require observed truncation points either. It is sufficient for point identification to know the cdf of the truncation variable, which can be estimated from supplementary data that are easily found in applications. The estimator converges to a normal distribution at the rate of [image omitted] and Monte Carlo simulations confirm its robustness to error distributions in finite samples. For an empirical illustration, I estimate the effect of unemployment insurance benefits on unemployment duration, using length-biased microdata and supplementary macrodata. Journal: Econometric Reviews Pages: 658-681 Issue: 6 Volume: 28 Year: 2009 Keywords: Duration models, Length-biased data, Rank estimation, Random truncation, Transformation model, X-DOI: 10.1080/07474930903039246 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930903039246 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:28:y:2009:i:6:p:658-681 Template-Type: ReDIF-Article 1.0 Author-Name: Pål Børing Author-X-Name-First: Pål Author-X-Name-Last: Børing Title: Gamma Unobserved Heterogeneity and Duration Bias Abstract: Røed et al. (1999) demonstrate that the standard result of known negative duration bias does not necessarily hold in a two-state mixed proportional hazard (MPH) model. We show that the duration bias is still ambiguous in a MPH model with a multivariate gamma distribution. A discrete time two-state version of our MPH model is developed to analyze the duration of higher education. The estimation results show that we cannot reject the hypothesis that the two unobserved heterogeneity variables are uncorrelated. Accepting this hypothesis implies that the standard result holds in our analysis. Journal: Econometric Reviews Pages: 1-19 Issue: 1 Volume: 29 Year: 2010 Keywords: Duration bias, Higher education, Multivariate gamma distribution, Unobserved heterogeneity, X-DOI: 10.1080/07474930903323822 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930903323822 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:29:y:2010:i:1:p:1-19 Template-Type: ReDIF-Article 1.0 Author-Name: W. Kwan Author-X-Name-First: W. Author-X-Name-Last: Kwan Author-Name: W. K. Li Author-X-Name-First: W. K. Author-X-Name-Last: Li Author-Name: K. W. Ng Author-X-Name-First: K. W. Author-X-Name-Last: Ng Title: A Multivariate Threshold Varying Conditional Correlations Model Abstract: In this article, a multivariate threshold varying conditional correlation (TVCC) model is proposed. The model extends the idea of Engle (2002) and Tse and Tsui (2002) to a threshold framework. This model retains the interpretation of the univariate threshold GARCH model and allows for dynamic conditional correlations. Techniques of model identification, estimation, and model checking are developed. Some simulation results are reported on the finite sample distribution of the maximum likelihood estimate of the TVCC model. Real examples demonstrate the asymmetric behavior of the mean and the variance in financial time series and the ability of the TVCC model to capture these phenomena. Journal: Econometric Reviews Pages: 20-38 Issue: 1 Volume: 29 Year: 2010 Keywords: Conditional correlation, Multivariate TVCC model, Threshold, Volatility, X-DOI: 10.1080/07474930903327260 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930903327260 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:29:y:2010:i:1:p:20-38 Template-Type: ReDIF-Article 1.0 Author-Name: Kien Tran Author-X-Name-First: Kien Author-X-Name-Last: Tran Author-Name: Efthymios Tsionas Author-X-Name-First: Efthymios Author-X-Name-Last: Tsionas Title: Local GMM Estimation of Semiparametric Panel Data with Smooth Coefficient Models Abstract: In this article, we consider the estimation of semiparametric panel data smooth coefficient models. We propose a class of local generalized method of moments (LGMM) estimators that are simple and easy to implement in practice. We show that the proposed LGMM estimators are consistent and asymptotically normal. Monte Carlo simulations suggest that our proposed estimator performs quite well in finite samples. An empirical application using a large panel of U.K. firms is also presented. Journal: Econometric Reviews Pages: 39-61 Issue: 1 Volume: 29 Year: 2010 Keywords: Local Generalized Method of Moments, Monte Carlo simulation, Semiparametric panel data model, Smooth coefficient, X-DOI: 10.1080/07474930903327856 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930903327856 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:29:y:2010:i:1:p:39-61 Template-Type: ReDIF-Article 1.0 Author-Name: Leopold Simar Author-X-Name-First: Leopold Author-X-Name-Last: Simar Author-Name: Paul Wilson Author-X-Name-First: Paul Author-X-Name-Last: Wilson Title: Inferences from Cross-Sectional, Stochastic Frontier Models Abstract: Conventional approaches for inference about efficiency in parametric stochastic frontier (PSF) models are based on percentiles of the estimated distribution of the one-sided error term, conditional on the composite error. When used as prediction intervals, coverage is poor when the signal-to-noise ratio is low, but improves slowly as sample size increases. We show that prediction intervals estimated by bagging yield much better coverages than the conventional approach, even with low signal-to-noise ratios. We also present a bootstrap method that gives confidence interval estimates for (conditional) expectations of efficiency, and which have good coverage properties that improve with sample size. In addition, researchers who estimate PSF models typically reject models, samples, or both when residuals have skewness in the “wrong” direction, i.e., in a direction that would seem to indicate absence of inefficiency. We show that correctly specified models can generate samples with “wrongly” skewed residuals, even when the variance of the inefficiency process is nonzero. Both our bagging and bootstrap methods provide useful information about inefficiency and model parameters irrespective of whether residuals have skewness in the desired direction. Journal: Econometric Reviews Pages: 62-98 Issue: 1 Volume: 29 Year: 2010 Keywords: Bagging, Bootstrap, Efficiency, Inference, Stochastic frontier, X-DOI: 10.1080/07474930903324523 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930903324523 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:29:y:2010:i:1:p:62-98 Template-Type: ReDIF-Article 1.0 Author-Name: Patrik Guggenberger Author-X-Name-First: Patrik Author-X-Name-Last: Guggenberger Title: Book Review: Identification and Inference for Econometric Models Abstract: Journal: Econometric Reviews Pages: 99-105 Issue: 1 Volume: 29 Year: 2010 X-DOI: 10.1080/07474930903324549 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930903324549 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:29:y:2010:i:1:p:99-105 Template-Type: ReDIF-Article 1.0 Author-Name: Francis Vella Author-X-Name-First: Francis Author-X-Name-Last: Vella Title: Book Review: Econometrics, Statistics and Computational Approaches in Food and Health Sciences Abstract: Journal: Econometric Reviews Pages: 106-109 Issue: 1 Volume: 29 Year: 2010 X-DOI: 10.1080/07474930903324572 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930903324572 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:29:y:2010:i:1:p:106-109 Template-Type: ReDIF-Article 1.0 Author-Name: Christian Gengenbach Author-X-Name-First: Christian Author-X-Name-Last: Gengenbach Author-Name: Franz C. Palm Author-X-Name-First: Franz C. Author-X-Name-Last: Palm Author-Name: Jean-Pierre Urbain Author-X-Name-First: Jean-Pierre Author-X-Name-Last: Urbain Title: Panel Unit Root Tests in the Presence of Cross-Sectional Dependencies: Comparison and Implications for Modelling Abstract: Several panel unit root tests that account for cross-section dependence using a common factor structure have been proposed in the literature recently. Pesaran's (2007) cross-sectionally augmented unit root tests are designed for cases where cross-sectional dependence is due to a single factor. The Moon and Perron (2004) tests which use defactored data are similar in spirit but can account for multiple common factors. The Bai and Ng (2004a) tests allow to determine the source of nonstationarity by testing for unit roots in the common factors and the idiosyncratic factors separately. Breitung and Das (2008) and Sul (2007) propose panel unit root tests when cross-section dependence is present possibly due to common factors, but the common factor structure is not fully exploited. This article makes four contributions: (1) it compares the testing procedures in terms of similarities and differences in the data generation process, tests, null, and alternative hypotheses considered, (2) using Monte Carlo results it compares the small sample properties of the tests in models with up to two common factors, (3) it provides an application which illustrates the use of the tests, and (4) finally, it discusses the use of the tests in modelling in general. Journal: Econometric Reviews Pages: 111-145 Issue: 2 Volume: 29 Year: 2010 Month: 4 X-DOI: 10.1080/07474930903382125 File-URL: http://hdl.handle.net/10.1080/07474930903382125 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:29:y:2010:i:2:p:111-145 Template-Type: ReDIF-Article 1.0 Author-Name: Edward Cripps Author-X-Name-First: Edward Author-X-Name-Last: Cripps Author-Name: Denzil G. Fiebig Author-X-Name-First: Denzil G. Author-X-Name-Last: Fiebig Author-Name: Robert Kohn Author-X-Name-First: Robert Author-X-Name-Last: Kohn Title: Parsimonious Estimation of the Covariance Matrix in Multinomial Probit Models Abstract: This article presents a Bayesian analysis of a multinomial probit model by building on previous work that specified priors on identified parameters. The main contribution of our article is to propose a prior on the covariance matrix of the latent utilities that permits elements of the inverse of the covariance matrix to be identically zero. This allows a parsimonious representation of the covariance matrix when such parsimony exists. The methodology is applied to both simulated and real data, and its ability to obtain more efficient estimators of the covariance matrix and regression coefficients is assessed using simulated data. Journal: Econometric Reviews Pages: 146-157 Issue: 2 Volume: 29 Year: 2010 Month: 4 X-DOI: 10.1080/07474930903382158 File-URL: http://hdl.handle.net/10.1080/07474930903382158 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:29:y:2010:i:2:p:146-157 Template-Type: ReDIF-Article 1.0 Author-Name: Bernd Fitzenberger Author-X-Name-First: Bernd Author-X-Name-Last: Fitzenberger Author-Name: Ralf A. Wilke Author-X-Name-First: Ralf A. Author-X-Name-Last: Wilke Author-Name: Xuan Zhang Author-X-Name-First: Xuan Author-X-Name-Last: Zhang Title: Implementing Box-Cox Quantile Regression Abstract: The Box-Cox quantile regression model introduced by Powell (1991) is a flexible and numerically attractive extension of linear quantile regression techniques. Chamberlain (1994) and Buchinsky (1995) suggest a two stage estimator for this model but the objective function in stage two of their method may not be defined in an application. We suggest a modification of the estimator which is easy to implement. A simulation study demonstrates that the modified estimator works well in situations, where the original estimator is not well defined. Journal: Econometric Reviews Pages: 158-181 Issue: 2 Volume: 29 Year: 2010 Month: 4 X-DOI: 10.1080/07474930903382166 File-URL: http://hdl.handle.net/10.1080/07474930903382166 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:29:y:2010:i:2:p:158-181 Template-Type: ReDIF-Article 1.0 Author-Name: Martin Wagner Author-X-Name-First: Martin Author-X-Name-Last: Wagner Author-Name: Jaroslava Hlouskova Author-X-Name-First: Jaroslava Author-X-Name-Last: Hlouskova Title: The Performance of Panel Cointegration Methods: Results from a Large Scale Simulation Study Abstract: This article presents results concerning the performance of both single equation and system panel cointegration tests and estimators. The study considers the tests developed in Pedroni (1999, 2004), Westerlund (2005), Larsson et al. (2001), and Breitung (2005) and the estimators developed in Phillips and Moon (1999), Pedroni (2000), Kao and Chiang (2000), Mark and Sul (2003), Pedroni (2001), and Breitung (2005). We study the impact of stable autoregressive roots approaching the unit circle, of <italic>I</italic>(2) components, of short-run cross-sectional correlation and of cross-unit cointegration on the performance of the tests and estimators. The data are simulated from three-dimensional individual specific VAR systems with cointegrating ranks varying from zero to two for fourteen different panel dimensions. The usual specifications of deterministic components are considered. Journal: Econometric Reviews Pages: 182-223 Issue: 2 Volume: 29 Year: 2010 Month: 4 X-DOI: 10.1080/07474930903382182 File-URL: http://hdl.handle.net/10.1080/07474930903382182 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:29:y:2010:i:2:p:182-223 Template-Type: ReDIF-Article 1.0 Author-Name: Gary Koop Author-X-Name-First: Gary Author-X-Name-Last: Koop Author-Name: Roberto León-González Author-X-Name-First: Roberto Author-X-Name-Last: León-González Author-Name: Rodney W. Strachan Author-X-Name-First: Rodney W. Author-X-Name-Last: Strachan Title: Efficient Posterior Simulation for Cointegrated Models with Priors on the Cointegration Space Abstract: A message coming out of the recent Bayesian literature on cointegration is that it is important to elicit a prior on the space spanned by the cointegrating vectors (as opposed to a particular identified choice for these vectors). In previous work, such priors have been found to greatly complicate computation. In this article, we develop algorithms to carry out efficient posterior simulation in cointegration models. In particular, we develop a collapsed Gibbs sampling algorithm which can be used with just-identifed models and demonstrate that it has very large computational advantages relative to existing approaches. For over-identifed models, we develop a parameter-augmented Gibbs sampling algorithm and demonstrate that it also has attractive computational properties. Journal: Econometric Reviews Pages: 224-242 Issue: 2 Volume: 29 Year: 2010 Month: 4 X-DOI: 10.1080/07474930903382208 File-URL: http://hdl.handle.net/10.1080/07474930903382208 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:29:y:2010:i:2:p:224-242 Template-Type: ReDIF-Article 1.0 Author-Name: Òscar Jord� Author-X-Name-First: Òscar Author-X-Name-Last: Jord� Title: Book Review: New Introduction to Multiple Time Series Analysis Journal: Econometric Reviews Pages: 243-246 Issue: 2 Volume: 29 Year: 2010 Month: 4 X-DOI: 10.1080/07474930903472868 File-URL: http://hdl.handle.net/10.1080/07474930903472868 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:29:y:2010:i:2:p:243-246 Template-Type: ReDIF-Article 1.0 Author-Name: Gordon Anderson Author-X-Name-First: Gordon Author-X-Name-Last: Anderson Author-Name: Ying Ge Author-X-Name-First: Ying Author-X-Name-Last: Ge Author-Name: Teng Wah Leo Author-X-Name-First: Teng Wah Author-X-Name-Last: Leo Title: Distributional Overlap: Simple, Multivariate, Parametric, and Nonparametric Tests for Alienation, Convergence, and General Distributional Difference Issues Abstract: This paper proposes a convenient measure of the degree of distributional overlap, both parametric and nonparametric, useful in measuring the degree of Polarization, Alienation, and Convergence. We show the measure is asymptotically normally distributed, making it amenable to inference in consequence. This Overlap measure can be used in the univariate and multivariate framework, and three examples are used to illustrate its use. The nonparametric Overlap Index has two sources of bias, the first being a positive bias induced by the unknown intersection point of the underlying distribution and the second being a negative bias induced by the expectation of cell probabilities being less than the conditional expected values. We show that the inconsistency problem generated by the first bias, prevalent within this class of Goodness of Fit measure, is limited by the number of intersection points of the underlying distributions. A Monte Carlo study was used to examine the biases, and it was found that the latter bias dominates the former. These biases can be diluted by increasing the number of partitions, but prevails asymptotically nonetheless. Journal: Econometric Reviews Pages: 247-275 Issue: 3 Volume: 29 Year: 2010 Keywords: Alienation, Convergence, Overlap index, Polarization, X-DOI: 10.1080/07474930903451532 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930903451532 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:29:y:2010:i:3:p:247-275 Template-Type: ReDIF-Article 1.0 Author-Name: Marcelo Fernandes Author-X-Name-First: Marcelo Author-X-Name-Last: Fernandes Author-Name: Breno Neri Author-X-Name-First: Breno Author-X-Name-Last: Neri Title: Nonparametric Entropy-Based Tests of Independence Between Stochastic Processes Abstract: This article develops nonparametric tests of independence between two stochastic processes satisfying β-mixing conditions. The testing strategy boils down to gauging the closeness between the joint and the product of the marginal stationary densities. For that purpose, we take advantage of a generalized entropic measure so as to build a whole family of nonparametric tests of independence. We derive asymptotic normality and local power using the functional delta method for kernels. As a corollary, we also develop a class of entropy-based tests for serial independence. The latter are nuisance parameter free, and hence also qualify for dynamic misspecification analyses. We then investigate the finite-sample properties of our serial independence tests through Monte Carlo simulations. They perform quite well, entailing more power against some nonlinear AR alternatives than two popular nonparametric serial-independence tests. Journal: Econometric Reviews Pages: 276-306 Issue: 3 Volume: 29 Year: 2010 Keywords: Independence, Misspecification testing, Nonparametric theory, Tsallis entropy, X-DOI: 10.1080/07474930903451557 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930903451557 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:29:y:2010:i:3:p:276-306 Template-Type: ReDIF-Article 1.0 Author-Name: Thanasis Stengos Author-X-Name-First: Thanasis Author-X-Name-Last: Stengos Author-Name: Ximing Wu Author-X-Name-First: Ximing Author-X-Name-Last: Wu Title: Information-Theoretic Distribution Test with Application to Normality Abstract: We derive general distribution tests based on the method of maximum entropy (ME) density. The proposed tests are derived from maximizing the differential entropy subject to given moment constraints. By exploiting the equivalence between the ME and maximum likelihood (ML) estimates for the general exponential family, we can use the conventional likelihood ratio (LR), Wald, and Lagrange multiplier (LM) testing principles in the maximum entropy framework. In particular, we use the LM approach to derive tests for normality. Monte Carlo evidence suggests that the proposed tests are compatible with and sometimes outperform some commonly used normality tests. We show that the proposed tests can be extended to tests based on regression residuals and non-i.i.d. data in a straightforward manner. An empirical example on production function estimation is presented. Journal: Econometric Reviews Pages: 307-329 Issue: 3 Volume: 29 Year: 2010 Keywords: Distribution test, Maximum entropy, Normality, X-DOI: 10.1080/07474930903451565 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930903451565 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:29:y:2010:i:3:p:307-329 Template-Type: ReDIF-Article 1.0 Author-Name: Mehmet Caner Author-X-Name-First: Mehmet Author-X-Name-Last: Caner Title: Testing, Estimation in GMM and CUE with Nearly-Weak Identification Abstract: In this article, we analyze Generalized Method of Moments (GMM) and Continuous Updating Estimator (CUE) with strong, nearly-weak, and weak identification. We show that with this mixed system, the limits of the estimators are nonstandard. In the subcase of GMM estimator with only nearly-weak instruments, the correlation between the instruments and the first order conditions decline at a slower rate than root T. We find an important difference between the nearly-weak case and the weak case. Inference with point estimates is possible with the Wald, likelihood ratio (LR), and Lagrange multiplier (LM) tests in GMM estimator with only nearly-weak instruments present in the system. The limit is the standard χ2 limit. This is important from an applied perspective, since tests on the weak case do depend on the true value and can only test simple null. We also show this in the more realistic case of mixed type of strong, weak, and nearly-weak instruments, Anderson and Rubin (1949) and Kleibergen (2005) type of tests are asymptotically pivotal and have χ2 limit. Journal: Econometric Reviews Pages: 330-363 Issue: 3 Volume: 29 Year: 2010 Keywords: Empirical process, Rate of convergence, Triangular central limit theorem, X-DOI: 10.1080/07474930903451599 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930903451599 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:29:y:2010:i:3:p:330-363 Template-Type: ReDIF-Article 1.0 Author-Name: Yingyao Hu Author-X-Name-First: Yingyao Author-X-Name-Last: Hu Author-Name: Geert Ridder Author-X-Name-First: Geert Author-X-Name-Last: Ridder Title: On Deconvolution as a First Stage Nonparametric Estimator Abstract: We reconsider Taupin's (2001) Integrated Nonlinear Regression (INLR) estimator for a nonlinear regression with a mismeasured covariate. We find that if we restrict the distribution of the measurement error to a class of distributions with restricted support, then much weaker smoothness assumptions than hers suffice to ensure [image omitted] consistency of the estimator. In addition, we show that the INLR estimator remains consistent under these weaker smoothness assumptions if the support of the measurement error distribution expands with the sample size. In that case the estimator remains also asymptotically normal with a rate of convergence that is arbitrarily close to [image omitted]. Our results show that deconvolution can be used in a nonparametric first step without imposing restrictive smoothness assumptions on the parametric model. Journal: Econometric Reviews Pages: 365-396 Issue: 4 Volume: 29 Year: 2010 Keywords: Asymptotic normality, Bounded support, Deconvolution, Measurement error model, Nonparametric estimation, Ordinary smooth, X-DOI: 10.1080/07474930903559276 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930903559276 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:29:y:2010:i:4:p:365-396 Template-Type: ReDIF-Article 1.0 Author-Name: Chang Sik Kim Author-X-Name-First: Chang Sik Author-X-Name-Last: Kim Author-Name: Joon Park Author-X-Name-First: Joon Author-X-Name-Last: Park Title: Cointegrating Regressions with Time Heterogeneity Abstract: This article considers the cointegrating regression with errors whose variances change smoothly over time. The model can be used to describe a long-run cointegrating relationship, the tightness of which varies along with time. Heteroskedasticity in the errors is modeled nonparametrically and is assumed to be generated by a smooth function of time. We show that it can be consistently estimated by the kernel method. Given consistent estimates for error variances, the cointegrating relationship can be efficiently estimated by the usual generalized least squares (GLS) correction for heteroskedastic errors. It is shown that the U.S. money demand function, both for M1 and M2, is well fitted to such a cointegrating model with an increasing trend in error variances. Moreover, we found that the bilateral purchasing power parities among the leading industrialized countries such as the United States, Japan, Canada, and the United Kingdom have been changed somewhat conspicuously over the past thirty years. In particular, it appears that they all have generally become more tightened during the period. Journal: Econometric Reviews Pages: 397-438 Issue: 4 Volume: 29 Year: 2010 Keywords: Cointegrating regression, GLS correction for heteroskedasticity, Kernel estimation, Time heterogeneity, X-DOI: 10.1080/07474930903562221 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930903562221 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:29:y:2010:i:4:p:397-438 Template-Type: ReDIF-Article 1.0 Author-Name: Sebastiano Manzan Author-X-Name-First: Sebastiano Author-X-Name-Last: Manzan Author-Name: Dawit Zerom Author-X-Name-First: Dawit Author-X-Name-Last: Zerom Title: A Semiparametric Analysis of Gasoline Demand in the United States Reexamining The Impact of Price Abstract: The evaluation of the impact of an increase in gasoline tax on demand relies crucially on the estimate of the price elasticity. This article presents an extended application of the Partially Linear Additive Model (PLAM) to the analysis of gasoline demand using a panel of U.S. households, focusing mainly on the estimation of the price elasticity. Unlike previous semiparametric studies that use household-level data, we work with vehicle-level data within households that can potentially add richer details to the price variable. Both households and vehicles data are obtained from the Residential Transportation Energy Consumption Survey (RTECS) of 1991 and 1994, conducted by the U.S. Energy Information Administration (EIA). As expected, the derived vehicle-based gasoline price has significant dispersion across the country and across grades of gasoline. By using a PLAM specification for gasoline demand, we obtain a measure of gasoline price elasticity that circumvents the implausible price effects reported in earlier studies. In particular, our results show the price elasticity ranges between -0.2, at low prices, and -0.5, at high prices, suggesting that households might respond differently to price changes depending on the level of price. In addition, we estimate separately the model to households that buy only regular gasoline and those that buy also midgrade/premium gasoline. The results show that the price elasticities for these groups are increasing in price and that regular households are more price sensitive compared to nonregular. Journal: Econometric Reviews Pages: 439-468 Issue: 4 Volume: 29 Year: 2010 Keywords: Gasoline demand, Partially linear additive model, Semiparametric methods, X-DOI: 10.1080/07474930903562320 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930903562320 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:29:y:2010:i:4:p:439-468 Template-Type: ReDIF-Article 1.0 Author-Name: Esfandiar Maasoumi Author-X-Name-First: Esfandiar Author-X-Name-Last: Maasoumi Author-Name: Marcelo Medeiros Author-X-Name-First: Marcelo Author-X-Name-Last: Medeiros Title: The Link Between Statistical Learning Theory and Econometrics: Applications in Economics, Finance, and Marketing Abstract: Statistical Learning refers to statistical aspects of automated extraction of regularities (structure) in datasets. It is a broad area which includes neural networks, regression-trees, nonparametric statistics and sieve approximation, boosting, mixtures of models, computational complexity, computational statistics, and nonlinear models in general. Although Statistical Learning Theory and Econometrics are closely related, much of the development in each of the areas is seemingly proceeding independently. This special issue brings together these two areas, and is intended to stimulate new applications and appreciation in economics, finance, and marketing. This special volume contains ten innovative articles covering a broad range of relevant topics. Journal: Econometric Reviews Pages: 470-475 Issue: 5-6 Volume: 29 Year: 2010 Keywords: Bagging, Forecasting, Mixture of models, Model combination, Neural networks, Nonlinear models, Regression trees, Statistical learning, Support vector regression, X-DOI: 10.1080/07474938.2010.481544 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474938.2010.481544 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:29:y:2010:i:5-6:p:470-475 Template-Type: ReDIF-Article 1.0 Author-Name: Nii Ayi Armah Author-X-Name-First: Nii Author-X-Name-Last: Ayi Armah Author-Name: Norman Swanson Author-X-Name-First: Norman Author-X-Name-Last: Swanson Title: Seeing Inside the Black Box: Using Diffusion Index Methodology to Construct Factor Proxies in Large Scale Macroeconomic Time Series Environments Abstract: In economics, common factors are often assumed to underlie the co-movements of a set of macroeconomic variables. For this reason, many authors have used estimated factors in the construction of prediction models. In this article, we begin by surveying the extant literature on diffusion indexes. We then outline a number of approaches to the selection of factor proxies (observed variables that proxy unobserved estimated factors) using the statistics developed in Bai and Ng (2006a,b). Our approach to factor proxy selection is examined via a small Monte Carlo experiment, where evidence supporting our proposed methodology is presented, and via a large set of prediction experiments using the panel dataset of Stock and Watson (2005). One of our main empirical findings is that our “smoothed” approaches to factor proxy selection appear to yield predictions that are often superior not only to a benchmark factor model, but also to simple linear time series models which are generally difficult to beat in forecasting competitions. In some sense, by using our approach to predictive factor proxy selection, one is able to open up the “black box” often associated with factor analysis, and to identify actual variables that can serve as primitive building blocks for (prediction) models of a host of macroeconomic variables, and that can also serve as policy instruments, for example. Our findings suggest that important observable variables include various S&P500 variables, including stock price indices and dividend series; a 1-year Treasury bond rate; various housing activity variables; industrial production; and exchange rates. Journal: Econometric Reviews Pages: 476-510 Issue: 5-6 Volume: 29 Year: 2010 Keywords: Diffusion index, Factor, Forecast, Macroeconometrics, Parameter estimation error, Proxy, X-DOI: 10.1080/07474938.2010.481549 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474938.2010.481549 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:29:y:2010:i:5-6:p:476-510 Template-Type: ReDIF-Article 1.0 Author-Name: David Rapach Author-X-Name-First: David Author-X-Name-Last: Rapach Author-Name: Jack Strauss Author-X-Name-First: Jack Author-X-Name-Last: Strauss Title: Bagging or Combining (or Both)? An Analysis Based on Forecasting U.S. Employment Growth Abstract: Forecasting a macroeconomic variable is challenging in an environment with many potential predictors whose predictive ability can vary over time. We compare two approaches to forecasting U.S. employment growth in this type of environment. The first approach applies bootstrap aggregating (bagging) to a general-to-specific procedure based on a general dynamic linear regression model with 30 potential predictors. The second approach considers several methods for combining forecasts from 30 individual autoregressive distributed lag (ARDL) models, where each individual ARDL model contains a potential predictor. We analyze bagging and combination forecasts at multiple horizons over four different out-of-sample periods using a mean square forecast error (MSFE) criterion and forecast encompassing tests. We find that bagging forecasts often deliver the lowest MSFE. Interestingly, we also find that incorporating information from both bagging and combination forecasts based on principal components often leads to further gains in forecast accuracy. Journal: Econometric Reviews Pages: 511-533 Issue: 5-6 Volume: 29 Year: 2010 Keywords: Bagging, Combination forecasts, Employment, Forecast encompassing, Principal components, X-DOI: 10.1080/07474938.2010.481550 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474938.2010.481550 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:29:y:2010:i:5-6:p:511-533 Template-Type: ReDIF-Article 1.0 Author-Name: Huiyu Huang Author-X-Name-First: Huiyu Author-X-Name-Last: Huang Author-Name: Tae-Hwy Lee Author-X-Name-First: Tae-Hwy Author-X-Name-Last: Lee Title: To Combine Forecasts or to Combine Information? Abstract: When the objective is to forecast a variable of interest but with many explanatory variables available, one could possibly improve the forecast by carefully integrating them. There are generally two directions one could proceed: combination of forecasts (CF) or combination of information (CI). CF combines forecasts generated from simple models each incorporating a part of the whole information set, while CI brings the entire information set into one super model to generate an ultimate forecast. Through linear regression analysis and simulation, we show the relative merits of each, particularly the circumstances where forecast by CF can be superior to forecast by CI, when CI model is correctly specified and when it is misspecified, and shed some light on the success of equally weighted CF. In our empirical application on prediction of monthly, quarterly, and annual equity premium, we compare the CF forecasts (with various weighting schemes) to CI forecasts (with principal component approach mitigating the problem of parameter proliferation). We find that CF with (close to) equal weights is generally the best and dominates all CI schemes, while also performing substantially better than the historical mean. Journal: Econometric Reviews Pages: 534-570 Issue: 5-6 Volume: 29 Year: 2010 Keywords: Equally weighted combination of forecasts, Equity premium, Factor models, Forecast combination, Forecast combination puzzle, Information sets, Many predictors, Principal components, Shrinkage, X-DOI: 10.1080/07474938.2010.481553 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474938.2010.481553 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:29:y:2010:i:5-6:p:534-570 Template-Type: ReDIF-Article 1.0 Author-Name: Eric Hillebrand Author-X-Name-First: Eric Author-X-Name-Last: Hillebrand Author-Name: Marcelo Medeiros Author-X-Name-First: Marcelo Author-X-Name-Last: Medeiros Title: The Benefits of Bagging for Forecast Models of Realized Volatility Abstract: This article shows that bagging can improve the forecast accuracy of time series models for realized volatility. We consider 23 stocks from the Dow Jones Industrial Average over the sample period 1995 to 2005 and employ two different forecast models, a log-linear specification in the spirit of the heterogeneous autoregressive model and a nonlinear specification with logistic transitions. Both forecast model types benefit from bagging, in particular in the 1990s part of our sample. The log-linear specification shows larger improvements than the nonlinear model. Bagging the log-linear model yields the highest forecast accuracy on our sample. Journal: Econometric Reviews Pages: 571-593 Issue: 5-6 Volume: 29 Year: 2010 Keywords: Bagging, Boostrap, HAR, Realized volatility, X-DOI: 10.1080/07474938.2010.481554 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474938.2010.481554 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:29:y:2010:i:5-6:p:571-593 Template-Type: ReDIF-Article 1.0 Author-Name: Nesreen Ahmed Author-X-Name-First: Nesreen Author-X-Name-Last: Ahmed Author-Name: Amir Atiya Author-X-Name-First: Amir Author-X-Name-Last: Atiya Author-Name: Neamat El Gayar Author-X-Name-First: Neamat El Author-X-Name-Last: Gayar Author-Name: Hisham El-Shishiny Author-X-Name-First: Hisham Author-X-Name-Last: El-Shishiny Title: An Empirical Comparison of Machine Learning Models for Time Series Forecasting Abstract: In this work we present a large scale comparison study for the major machine learning models for time series forecasting. Specifically, we apply the models on the monthly M3 time series competition data (around a thousand time series). There have been very few, if any, large scale comparison studies for machine learning models for the regression or the time series forecasting problems, so we hope this study would fill this gap. The models considered are multilayer perceptron, Bayesian neural networks, radial basis functions, generalized regression neural networks (also called kernel regression), K-nearest neighbor regression, CART regression trees, support vector regression, and Gaussian processes. The study reveals significant differences between the different methods. The best two methods turned out to be the multilayer perceptron and the Gaussian process regression. In addition to model comparisons, we have tested different preprocessing methods and have shown that they have different impacts on the performance. Journal: Econometric Reviews Pages: 594-621 Issue: 5-6 Volume: 29 Year: 2010 Keywords: Comparison study, Gaussian process regression, Machine learning models, Neural network forecasting, Support vector regression, X-DOI: 10.1080/07474938.2010.481556 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474938.2010.481556 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:29:y:2010:i:5-6:p:594-621 Template-Type: ReDIF-Article 1.0 Author-Name: Philip Yu Author-X-Name-First: Philip Author-X-Name-Last: Yu Author-Name: Wai Keung Li Author-X-Name-First: Wai Keung Author-X-Name-Last: Li Author-Name: Shusong Jin Author-X-Name-First: Shusong Author-X-Name-Last: Jin Title: On Some Models for Value-At-Risk Abstract: The idea of statistical learning can be applied in financial risk management. In recent years, value-at-risk (VaR) has become the standard tool for market risk measurement and management. For better VaR estimation, Engle and Manganelli (2004) introduced the conditional autoregressive value-at-risk (CAViaR) model to estimate the VaR directly by quantile regression. To entertain the nonlinearity and structural change in the VaR, we extend the CAViaR idea using two approaches: the threshold GARCH (TGARCH) and the mixture-GARCH models. The estimation method of these models are proposed. Our models should possess all the advantages of the CAViaR model and enhance the nonlinear structure. The methods are applied to the S&P500, Hang Seng, Nikkei and Nasdaq indices to illustrate our models. Journal: Econometric Reviews Pages: 622-641 Issue: 5-6 Volume: 29 Year: 2010 Keywords: GARCH model, Mixtures, Threshold models, Value-at-risk, X-DOI: 10.1080/07474938.2010.481972 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474938.2010.481972 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:29:y:2010:i:5-6:p:622-641 Template-Type: ReDIF-Article 1.0 Author-Name: Alexandre Carvalho Author-X-Name-First: Alexandre Author-X-Name-Last: Carvalho Author-Name: Georgios Skoulakis Author-X-Name-First: Georgios Author-X-Name-Last: Skoulakis Title: Time Series Mixtures of Generalized t Experts: ML Estimation and an Application to Stock Return Density Forecasting Abstract: We propose and analyze a new nonlinear time series model based on local mixtures of linear regressions, referred to as experts, with thick-tailed disturbances. The mean function of each expert is an affine function of covariates that may include lags of the dependent variable and/or lags of external predictors. The mixing of the experts is determined by a latent variable, the distribution of which depends on the same covariates used in the regressions. The expert error terms are assumed to follow the generalized t distribution, a rather flexible parametric form encompassing the standard t and normal distributions as special cases and allowing separate modeling of scale and kurtosis. We show consistency and asymptotic normality of the maximum likelihood estimator, for correctly specified and for misspecified models, and provide Monte Carlo evidence on the performance of standard model selection criteria in selecting the number of experts. We further employ the model to obtain density forecasts for daily stock returns and find evidence to support the model. Journal: Econometric Reviews Pages: 642-687 Issue: 5-6 Volume: 29 Year: 2010 Keywords: Conditional density forecast, Generalized t distribution, Heavy tail distributions, Maximum likelihood estimation, Mixtures-of-experts, Nonlinear time series, X-DOI: 10.1080/07474938.2010.481987 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474938.2010.481987 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:29:y:2010:i:5-6:p:642-687 Template-Type: ReDIF-Article 1.0 Author-Name: Georgi Nalbantov Author-X-Name-First: Georgi Author-X-Name-Last: Nalbantov Author-Name: Philip Hans Franses Author-X-Name-First: Philip Hans Author-X-Name-Last: Franses Author-Name: Patrick Groenen Author-X-Name-First: Patrick Author-X-Name-Last: Groenen Author-Name: Jan Bioch Author-X-Name-First: Jan Author-X-Name-Last: Bioch Title: Estimating the Market Share Attraction Model using Support Vector Regressions Abstract: We propose to estimate the parameters of the Market Share Attraction Model (Cooper and Nakanishi, 1988; Fok and Franses, 2004) in a novel way by using a nonparametric technique for function estimation called Support Vector Regressions (SVR) (Smola, 1996; Vapnik, 1995). Traditionally, the parameters of the Market Share Attraction Model are estimated via a Maximum Likelihood (ML) procedure, assuming that the data are drawn from a conditional Gaussian distribution. However, if the distribution is unknown, Ordinary Least Squares (OLS) estimation may seriously fail (Vapnik, 1982). One way to tackle this problem is to introduce a linear loss function over the errors and a penalty on the magnitude of model coefficients. This leads to qualities such as robustness to outliers and avoidance of the problem of overfitting. This kind of estimation forms the basis of the SVR technique, which, as we will argue, makes it a good candidate for estimating the Market Share Attraction Model. We test the SVR approach to predict (the evolution of) the market shares of 36 car brands simultaneously and report promising results. Journal: Econometric Reviews Pages: 688-716 Issue: 5-6 Volume: 29 Year: 2010 Keywords: Marketing, Market share attraction model, Multi-output forecasting, Shrinkage estimators, Support vector regression, X-DOI: 10.1080/07474938.2010.481989 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474938.2010.481989 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:29:y:2010:i:5-6:p:688-716 Template-Type: ReDIF-Article 1.0 Author-Name: Andre d'Almeida Monteiro Author-X-Name-First: Andre Author-X-Name-Last: d'Almeida Monteiro Title: Estimating Interest Rate Curves by Support Vector Regression Abstract: A model that seeks to estimate an interest rate curve should have two desirable capabilities in addition to the usual characteristics required from any function-estimation model: it should incorporate the bid-ask spreads of the securities from which the curve is extracted and restrict the curve shape. The goal of this article is to estimate interest rate curves by using Support Vector Regression (SVR), a method derived from the Statistical Learning Theory developed by Vapnik (1995). The motivation is that SVR features these extra capabilities at a low estimation cost. The SVR is specified by a loss function, a kernel function and a smoothing parameter. SVR models the daily U.S. dollar interest rate swap curves, from 1997 to 2001. As expected from a priori and sensibility analyses, the SVR equipped with the kernel generating a spline with an infinite number of nodes was the best performing SVR. Comparing this SVR with other models, it achieved the best cross-validation interpolation performance in controlling the bias-variance trade-off and generating the lowest error considering the desired accuracy fixed by the bid-ask spreads. Journal: Econometric Reviews Pages: 717-753 Issue: 5-6 Volume: 29 Year: 2010 Keywords: Bid-ask spread, Interest rate curves, Interest rate swaps, Support Vector Regression, X-DOI: 10.1080/07474938.2010.481998 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474938.2010.481998 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:29:y:2010:i:5-6:p:717-753 Template-Type: ReDIF-Article 1.0 Author-Name: William Rea Author-X-Name-First: William Author-X-Name-Last: Rea Author-Name: Marco Reale Author-X-Name-First: Marco Author-X-Name-Last: Reale Author-Name: Carmela Cappelli Author-X-Name-First: Carmela Author-X-Name-Last: Cappelli Author-Name: Jennifer Brown Author-X-Name-First: Jennifer Author-X-Name-Last: Brown Title: Identification of Changes in Mean with Regression Trees: An Application to Market Research Abstract: In this article we present a computationally efficient method for finding multiple structural breaks at unknown dates based on regression trees. We outline the procedure and present the results of a simulation study to assess the performance of the method and to compare it with the procedure proposed by Bai and Perron. We find the tree-based method performs well in long series which are impractical to analyze with current methods. We apply these methods plus the CUSUM test to the market share of Crest toothpaste between 1958 and 1963. Journal: Econometric Reviews Pages: 754-777 Issue: 5-6 Volume: 29 Year: 2010 Keywords: Identification of multiple structural breaks at unknown times, Time series analysis, X-DOI: 10.1080/07474938.2010.482001 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474938.2010.482001 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:29:y:2010:i:5-6:p:754-777 Template-Type: ReDIF-Article 1.0 Author-Name: Francesco Bravo Author-X-Name-First: Francesco Author-X-Name-Last: Bravo Author-Name: David Jacho-Chavez Author-X-Name-First: David Author-X-Name-Last: Jacho-Chavez Title: Empirical Likelihood for Efficient Semiparametric Average Treatment Effects Abstract: This article considers empirical likelihood in the context of efficient semiparametric estimators of average treatment effects. It shows that the empirical likelihood ratio converges to a nonstandard distribution, and proposes a corrected test statistic that is asymptotically chi-squared. A small Monte Carlo experiment suggests that the corrected empirical likelihood ratio statistic has competitive finite sample properties. The results of the article are applied to estimate the environmental effect of the World Trade Organisation. Journal: Econometric Reviews Pages: 1-24 Issue: 1 Volume: 30 Year: 2011 Keywords: Empirical likelihood, Local polynomial regression, Plug-in principle, Propensity score, Weighted moment conditions, WTO, X-DOI: 10.1080/07474938.2011.520547 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474938.2011.520547 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:30:y:2011:i:1:p:1-24 Template-Type: ReDIF-Article 1.0 Author-Name: Dinghai Xu Author-X-Name-First: Dinghai Author-X-Name-Last: Xu Author-Name: John Knight Author-X-Name-First: John Author-X-Name-Last: Knight Title: Continuous Empirical Characteristic Function Estimation of Mixtures of Normal Parameters Abstract: This article develops an efficient method for estimating the discrete mixtures of normal family based on the continuous empirical characteristic function (CECF). An iterated estimation procedure based on the closed form objective distance function is proposed to improve the estimation efficiency. The results from the Monte Carlo simulation reveal that the CECF estimator produces good finite sample properties. In particular, it outperforms the discrete type of methods when the maximum likelihood estimation fails to converge. An empirical example is provided for illustrative purposes. Journal: Econometric Reviews Pages: 25-50 Issue: 1 Volume: 30 Year: 2011 Keywords: Empirical characteristic function, Mixtures of normal, X-DOI: 10.1080/07474938.2011.520565 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474938.2011.520565 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:30:y:2011:i:1:p:25-50 Template-Type: ReDIF-Article 1.0 Author-Name: Nikolaos Kourogenis Author-X-Name-First: Nikolaos Author-X-Name-Last: Kourogenis Author-Name: Nikitas Pittis Author-X-Name-First: Nikitas Author-X-Name-Last: Pittis Title: Mixing Conditions, Central Limit Theorems, and Invariance Principles: A Survey of the Literature with Some New Results on Heteroscedastic Sequences Abstract: This article is a survey of the main results on the central limit theorem (CLT) and its invariance principle (IP) for mixing sequences that have been obtained in the probabilistic literature in the last fifty years or so with a view towards econometric applications. Each of these theorems specifies a set of moment, dependence, and heterogeneity conditions on the underlying sequence that ensures the validity of CLT and IP. Special emphasis is paid to the case in which the underlying sequence has just barely infinite variance, since this case is relevant to econometrics applications that involve high-frequency financial data. Moreover, two new results on IPs that apply to heteroscedastic sequences are obtained. The first IP applies to sequences whose variances evolve over time in a polynomial-like fashion, whereas the second IP concerns sequences that experience a single variance break at some point within the sample. Journal: Econometric Reviews Pages: 88-108 Issue: 1 Volume: 30 Year: 2011 Keywords: Central limit theorem, Invariance Principle, Mixing, Trending variances, Variance break, X-DOI: 10.1080/07474938.2011.520569 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474938.2011.520569 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:30:y:2011:i:1:p:88-108 Template-Type: ReDIF-Article 1.0 Author-Name: Michael Lechner Author-X-Name-First: Michael Author-X-Name-Last: Lechner Title: The Relation of Different Concepts of Causality Used in Time Series and Microeconometrics Abstract: Granger and Sims noncausality (GSNC), a concept frequently applied in time series econometrics, is compared to noncausality based on concepts popular in microeconometrics, program evaluation, and epidemiology literature (potential outcome noncausality or PONC). GSNC is defined as a set of restrictions on joint distributions of random variables with observable sample counterparts, whereas PONC combines restrictions on partially unobservable variables (potential outcomes) with different identifying assumptions that relate potential outcome variables to their observable counterparts. Based on the Robins' dynamic model of potential outcomes, we find that in general neither of the concepts implies each other without further (untestable) assumptions. However, the identifying assumptions associated with the sequential selection of the observables link these concepts such that GSNC implies PONC, and vice versa. Journal: Econometric Reviews Pages: 109-127 Issue: 1 Volume: 30 Year: 2011 Keywords: Dynamic treatments, Granger causality, Potential outcome model, Rubin causality, Robins causality, Sims causality, X-DOI: 10.1080/07474938.2011.520571 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474938.2011.520571 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:30:y:2011:i:1:p:109-127 Template-Type: ReDIF-Article 1.0 Author-Name: Theis Lange Author-X-Name-First: Theis Author-X-Name-Last: Lange Author-Name: Anders Rahbek Author-X-Name-First: Anders Author-X-Name-Last: Rahbek Author-Name: Søren Tolver Jensen Author-X-Name-First: Søren Tolver Author-X-Name-Last: Jensen Title: Estimation and Asymptotic Inference in the AR-ARCH Model Abstract: This article studies asymptotic properties of the quasi-maximum likelihood estimator (QMLE) for the parameters in the autoregressive (AR) model with autoregressive conditional heteroskedastic (ARCH) errors. A modified QMLE (MQMLE) is also studied. This estimator is based on truncation of individual terms of the likelihood function and is related to the recent so-called self-weighted QMLE in Ling (2007b). We show that the MQMLE is asymptotically normal irrespectively of the existence of finite moments, as geometric ergodicity alone suffice. Moreover, our included simulations show that the MQMLE is remarkably well-behaved in small samples. On the other hand, the ordinary QMLE, as is well-known, requires finite fourth order moments for asymptotic normality. But based on our considerations and simulations, we conjecture that in fact only geometric ergodicity and finite second order moments are needed for the QMLE to be asymptotically normal. Finally, geometric ergodicity for AR-ARCH processes is shown to hold under mild and classic conditions on the AR and ARCH processes. Journal: Econometric Reviews Pages: 129-153 Issue: 2 Volume: 30 Year: 2011 Keywords: ARCH, Asymptotic theory, Geometric ergodicity, Modified QMLE, QMLE, X-DOI: 10.1080/07474938.2011.534031 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474938.2011.534031 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:30:y:2011:i:2:p:129-153 Template-Type: ReDIF-Article 1.0 Author-Name: Gabriel Montes-Rojas Author-X-Name-First: Gabriel Author-X-Name-Last: Montes-Rojas Title: Robust Misspecification Tests for the Heckman's Two-Step Estimator Abstract: This article constructs and evaluates Lagrange multiplier (LM) and Neyman's C(α) tests based on bivariate Edgeworth series expansions for the consistency of the Heckman's two-step estimator in sample selection models, that is, for marginal normality and linearity of the conditional expectation of the error terms. The proposed tests are robust to local misspecification in nuisance distributional parameters. Monte Carlo results show that testing marginal normality and linearity of the conditional expectations separately have a better size performance than testing bivariate normality. Moreover, the robust variants of the tests have better empirical size than nonrobust tests, which determines that these tests can be successfully applied to detect specific departures from the null model of bivariate normality. Finally, the tests are applied to women's labor supply data. Journal: Econometric Reviews Pages: 154-172 Issue: 2 Volume: 30 Year: 2011 Keywords: Heckman's two-step, LM tests, Neyman's C(α) tests, X-DOI: 10.1080/07474938.2011.534035 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474938.2011.534035 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:30:y:2011:i:2:p:154-172 Template-Type: ReDIF-Article 1.0 Author-Name: Qingyan Shang Author-X-Name-First: Qingyan Author-X-Name-Last: Shang Author-Name: Lung-fei Lee Author-X-Name-First: Lung-fei Author-X-Name-Last: Lee Title: Two-Step Estimation of Endogenous and Exogenous Group Effects Abstract: In this article, we propose a two-step method to identify and estimate endogenous and exogenous social interactions in the Manski (1993) and Brock and Durlauf's (2001a,b) discrete choice model with unobserved group variables. Taking advantage of social groups with large group sizes, we first estimate a probit model with group fixed-effects, and then use the instrumental variables method to estimate endogenous and exogenous group effects via the group fixed-effect estimates. Our method is computationally simple. The method is applicable not only to the case of single equilibrium but also the multiple equilibria case without the need to specify an (arbitrary) equilibrium selection mechanism. The article provides a Monte Carlo study on the finite sample performance of such estimators. Journal: Econometric Reviews Pages: 173-207 Issue: 2 Volume: 30 Year: 2011 Keywords: Correlated effect, Discrete choice, Endogenous effect, Exogenous effect, Instrumental variables, Large size group, Monte Carlo, Social interaction, Two-step estimator, X-DOI: 10.1080/07474938.2011.534039 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474938.2011.534039 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:30:y:2011:i:2:p:173-207 Template-Type: ReDIF-Article 1.0 Author-Name: Loukia Meligkotsidou Author-X-Name-First: Loukia Author-X-Name-Last: Meligkotsidou Author-Name: Elias Tzavalis Author-X-Name-First: Elias Author-X-Name-Last: Tzavalis Author-Name: Ioannis Vrontos Author-X-Name-First: Ioannis Author-X-Name-Last: Vrontos Title: A Bayesian Analysis of Unit Roots and Structural Breaks in the Level, Trend, and Error Variance of Autoregressive Models of Economic Series Abstract: In this article, a Bayesian approach is suggested to compare unit root models with stationary autoregressive models when the level, the trend, and the error variance are subject to structural changes (known as breaks) of an unknown date. Ignoring structural breaks in the error variance may be responsible for not rejecting the unit root hypothesis, even if allowance is made in the inferential procedures for breaks in the mean. The article utilizes analytic and Monte Carlo integration techniques for calculating the marginal likelihoods of the models under consideration, in order to compute the posterior model probabilities. The performance of the method is assessed by simulation experiments. Some empirical applications of the method are conducted with the aim to investigate if it can detect structural breaks in financial series, especially with changes in the error variance. Journal: Econometric Reviews Pages: 208-249 Issue: 2 Volume: 30 Year: 2011 Keywords: Autoregressive models, Bayesian inference, Model comparison, Structural breaks, Unit roots, X-DOI: 10.1080/07474938.2011.534046 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474938.2011.534046 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:30:y:2011:i:2:p:208-249 Template-Type: ReDIF-Article 1.0 Author-Name: Fuchun Li Author-X-Name-First: Fuchun Author-X-Name-Last: Li Author-Name: Greg Tkacz Author-X-Name-First: Greg Author-X-Name-Last: Tkacz Title: A Consistent Test for Multivariate Conditional Distributions Abstract: We propose a new test for a multivariate parametric conditional distribution of a vector of variables yt given a conditional vector xt. The proposed test is shown to have an asymptotic normal distribution under the null hypothesis, while being consistent for all fixed alternatives, and having nontrivial power against a sequence of local alternatives. Monte Carlo simulations show that our test has reasonable size and good power for both univariate and multivariate models, even for highly persistent dependent data with sample sizes often encountered in empirical finance. Journal: Econometric Reviews Pages: 251-273 Issue: 3 Volume: 30 Year: 2011 Keywords: Absolutely regular process, Consistent test, Degenerate U-statistics, Stochastic differential equation, X-DOI: 10.1080/07474938.2011.553518 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474938.2011.553518 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:30:y:2011:i:3:p:251-273 Template-Type: ReDIF-Article 1.0 Author-Name: Rehim Kılıc Author-X-Name-First: Rehim Author-X-Name-Last: Kılıc Title: Testing for a unit root in a stationary ESTAR process Abstract: This article develops a statistic for testing the null of a linear unit root process against the alternative of a stationary exponential smooth transition autoregressive model. The asymptotic distribution of the test is shown to be nonstandard but nuisance parameter-free and hence critical values are obtained by simulations. Simulations show that the proposed statistic has considerable power under various data generating scenarios. Applications to real exchange rates also illustrate the ability of our test to reject null of unit root when some of the alternative tests do not. Journal: Econometric Reviews Pages: 274-302 Issue: 3 Volume: 30 Year: 2011 Keywords: ESTAR model, Nonlinearity, Unit root, X-DOI: 10.1080/07474938.2011.553511 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474938.2011.553511 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:30:y:2011:i:3:p:274-302 Template-Type: ReDIF-Article 1.0 Author-Name: Emma Iglesias Author-X-Name-First: Emma Author-X-Name-Last: Iglesias Author-Name: Garry Phillips Author-X-Name-First: Garry Author-X-Name-Last: Phillips Title: Small Sample Estimation Bias in GARCH Models with Any Number of Exogenous Variables in the Mean Equation Abstract: In this article we show how bias approximations for the quasi maximum likelihood estimators of the parameters in Generalized Autoregressive Conditional Heteroskedastic (GARCH)(p, q) models change when any number of exogenous variables are included in the mean equation. The approximate biases are shown to vary in an additive and proportional way in relation to the number of exogenous variables, and they do not depend on the moments of the regressors under the correct specification of the model. This suggests a rule of thumb in testing for misspecification in GARCH models. We also extend the theoretical bias approximations given in Linton (1997) for the GARCH(1, 1). Because the expressions are not in closed form, we concentrate in detail, and for simplicity of interpretation, on the ARCH(1) model. At each stage, we check our theoretical results by simulation and generally, we find that the approximations are quite accurate for sample sizes of at least 50. We find that the biases are not trivial in some circumstances and we discuss how the bias approximations may be used, in practice, to reduce the bias. We also carry out simulations for the GARCH(1,1) model and show that the biases change as predicted by the approximations when the mean equation is augmented. Finally, we illustrate the usefulness of our approach for U.S. monthly inflation rates. Journal: Econometric Reviews Pages: 303-336 Issue: 3 Volume: 30 Year: 2011 Keywords: Bias correction, GARCH, Quasi maximum likelihood, X-DOI: 10.1080/07474930903562551 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930903562551 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:30:y:2011:i:3:p:303-336 Template-Type: ReDIF-Article 1.0 Author-Name: Scott Atkinson Author-X-Name-First: Scott Author-X-Name-Last: Atkinson Author-Name: Christopher Cornwell Author-X-Name-First: Christopher Author-X-Name-Last: Cornwell Title: Estimation of Allocative Inefficiency and Productivity Growth with Dynamic Adjustment Costs Abstract: A substantial literature has been generated on the estimation of allocative and technical inefficiency using static production, cost, profit, and distance functions. We develop a dynamic shadow distance system that integrates dynamic adjustment costs into a long-run shadow cost-minimization problem, which allows us to distinguish static allocative distortions from short-run inefficiencies that arise due to period-to-period adjustment costs. The set of estimating equations is comprised of the first-order conditions from the short-run shadow cost-minimization problem for the variable shadow input quantities, a set of Euler equations derived from subsequent shadow cost minimization with respect to the quasi-fixed inputs, and the input distance function, expressed in terms of shadow quantities. This system nests within it the static model with zero adjustment costs. Using panel data on U.S. electric utilities, we contrast the results of static and dynamic shadow distance systems. First, the zero-adjustment-cost restriction is strongly rejected. Second, we find that adjustment costs represent about 0.42% of total cost, and about 1.26% of capital costs. Third, while both models reveal that labor is not utilized efficiently, the dynamic model indicates a longer period of over-use and less variance over time in the degree of inefficiency. With the dynamic model, productivity growth is larger but more stable. Journal: Econometric Reviews Pages: 337-357 Issue: 3 Volume: 30 Year: 2011 Keywords: Allocative inefficiency, Dynamic estimation, Euler equations, Productivity change, Technical change, Technical inefficiency, X-DOI: 10.1080/07474930903451581 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474930903451581 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:30:y:2011:i:3:p:337-357 Template-Type: ReDIF-Article 1.0 Author-Name: Kulan Ranasinghe Author-X-Name-First: Kulan Author-X-Name-Last: Ranasinghe Author-Name: Mervyn J. Silvapulle Author-X-Name-First: Mervyn J. Author-X-Name-Last: Silvapulle Title: Estimation Under Inequality Constraints: Semiparametric Estimation of Conditional Duration Models Abstract: This article proposes a semiparametric estimator of the parameter in a conditional duration model when there are inequality constraints on some parameters and the error distribution may be unknown. We propose to estimate the parameter by a constrained version of an unrestricted semiparametrically efficient estimator. The main requirement for applying this method is that the initial unrestricted estimator converges in distribution. Apart from this, additional regularity conditions on the data generating process or the likelihood function, are not required. Hence the method is applicable to a broad range of models where the parameter space is constrained by inequality constraints, such as the conditional duration models. In a simulation study involving conditional duration models, the overall performance of the constrained estimator was better than its competitors, in terms of mean squared error. A data example is used to illustrate the method. Journal: Econometric Reviews Pages: 359-378 Issue: 4 Volume: 30 Year: 2011 Month: 8 X-DOI: 10.1080/07474938.2011.553537 File-URL: http://hdl.handle.net/10.1080/07474938.2011.553537 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:30:y:2011:i:4:p:359-378 Template-Type: ReDIF-Article 1.0 Author-Name: Nikolay Gospodinov Author-X-Name-First: Nikolay Author-X-Name-Last: Gospodinov Author-Name: Ye Tao Author-X-Name-First: Ye Author-X-Name-Last: Tao Title: Bootstrap Unit Root Tests in Models with GARCH(1,1) Errors Abstract: This article proposes a bootstrap unit root test in models with GARCH(1,1) errors and establishes its asymptotic validity under mild moment and distributional restrictions. While the proposed bootstrap test for a unit root shares the power enhancing properties of its asymptotic counterpart (Ling and Li, 2003), it offers a number of important advantages. In particular, the bootstrap procedure does not require explicit estimation of nuisance parameters that enter the distribution of the test statistic and corrects the substantial size distortions of the asymptotic test that occur for strongly heteroskedastic processes. The simulation results demonstrate the excellent finite-sample properties of the bootstrap unit root test for a wide range of GARCH specifications. Journal: Econometric Reviews Pages: 379-405 Issue: 4 Volume: 30 Year: 2011 Month: 8 X-DOI: 10.1080/07474938.2011.553538 File-URL: http://hdl.handle.net/10.1080/07474938.2011.553538 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:30:y:2011:i:4:p:379-405 Template-Type: ReDIF-Article 1.0 Author-Name: Giuseppe Ragusa Author-X-Name-First: Giuseppe Author-X-Name-Last: Ragusa Title: Minimum Divergence, Generalized Empirical Likelihoods, and Higher Order Expansions Abstract: This article studies the minimum divergence (MD) class of estimators for econometric models specified through moment restrictions. We show that MD estimators can be obtained as solutions to a tractable lower dimensional optimization problem. This problem is similar to the one solved by the generalized empirical likelihood estimators of Newey and Smith (2004), but it is equivalent to it only for a subclass of divergences. The MD framework provides a coherent testing theory: tests for overidentification and parametric restrictions in this framework can be interpreted as semiparametric versions of Pearson-type goodness of fit tests. The higher order properties of MD estimators are also studied and it is shown that MD estimators that have the same higher order bias as the empirical likelihood (EL) estimator also share the same higher order mean square error and are all higher order efficient. We identify members of the MD class that are not only higher order efficient, but also, unlike the EL estimator, well behaved when the moment restrictions are misspecified. Journal: Econometric Reviews Pages: 406-456 Issue: 4 Volume: 30 Year: 2011 Month: 8 X-DOI: 10.1080/07474938.2011.553541 File-URL: http://hdl.handle.net/10.1080/07474938.2011.553541 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:30:y:2011:i:4:p:406-456 Template-Type: ReDIF-Article 1.0 Author-Name: Dale J. Poirier Author-X-Name-First: Dale J. Author-X-Name-Last: Poirier Title: Bayesian Interpretations of Heteroskedastic Consistent Covariance Estimators Using the Informed Bayesian Bootstrap Abstract: This article provides Bayesian interpretations for White's <italic>heteroskedastic consistent</italic> (HC) covariance estimator, and various modifications of it, in linear regression models. An informed Bayesian bootstrap provides a useful framework. Journal: Econometric Reviews Pages: 457-468 Issue: 4 Volume: 30 Year: 2011 Month: 8 X-DOI: 10.1080/07474938.2011.553542 File-URL: http://hdl.handle.net/10.1080/07474938.2011.553542 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:30:y:2011:i:4:p:457-468 Template-Type: ReDIF-Article 1.0 Author-Name: Richard Luger Author-X-Name-First: Richard Author-X-Name-Last: Luger Title: Book Review: Introducing Monte Carlo Methods with R Journal: Econometric Reviews Pages: 469-474 Issue: 4 Volume: 30 Year: 2011 Month: 8 X-DOI: 10.1080/07474938.2011.553548 File-URL: http://hdl.handle.net/10.1080/07474938.2011.553548 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:30:y:2011:i:4:p:469-474 Template-Type: ReDIF-Article 1.0 Author-Name: Tucker McElroy Author-X-Name-First: Tucker Author-X-Name-Last: McElroy Author-Name: Thomas M. Trimbur Author-X-Name-First: Thomas M. Author-X-Name-Last: Trimbur Title: On the Discretization of Continuous-Time Filters for Nonstationary Stock and Flow Time Series Abstract: This article discusses the discretization of continuous-time filters for application to discrete time series sampled at any fixed frequency. In this approach, the filter is first set up directly in continuous-time; since the filter is expressed over a continuous range of lags, we also refer to them as continuous-lag filters. The second step is to discretize the filter itself. This approach applies to different problems in signal extraction, including trend or business cycle analysis, and the method allows for coherent design of discrete filters for observed data sampled as a stock or a flow, for nonstationary data with stochastic trend, and for different sampling frequencies. We derive explicit formulas for the mean squared error (MSE) optimal discretization filters. We also discuss the problem of optimal interpolation for nonstationary processes - namely, how to estimate the values of a process and its components at arbitrary times in-between the sampling times. A number of illustrations of discrete filter coefficient calculations are provided, including the local level model (LLM) trend filter, the smooth trend model (STM) trend filter, and the Band Pass (BP) filter. The essential methodology can be applied to other kinds of trend extraction problems. Finally, we provide an extended demonstration of the method on CPI flow data measured at monthly and annual sampling frequencies. Journal: Econometric Reviews Pages: 475-513 Issue: 5 Volume: 30 Year: 2011 Month: 10 X-DOI: 10.1080/07474938.2011.553554 File-URL: http://hdl.handle.net/10.1080/07474938.2011.553554 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:30:y:2011:i:5:p:475-513 Template-Type: ReDIF-Article 1.0 Author-Name: David I. Harvey Author-X-Name-First: David I. Author-X-Name-Last: Harvey Author-Name: Stephen J. Leybourne Author-X-Name-First: Stephen J. Author-X-Name-Last: Leybourne Author-Name: A. M. Robert Taylor Author-X-Name-First: A. M. Author-X-Name-Last: Robert Taylor Title: Testing for Unit Roots and the Impact of Quadratic Trends, with an Application to Relative Primary Commodity Prices Abstract: In practice a degree of uncertainty will always exist concerning what specification to adopt for the deterministic trend function when running unit root tests. While most macroeconomic time series appear to display an underlying trend, it is often far from clear whether this component is best modeled as a simple linear trend (so that long-run growth rates are constant) or by a more complicated nonlinear trend function which may, for instance, allow the deterministic trend component to evolve gradually over time. In this article, we consider the effects on unit root testing of allowing for a local quadratic trend, a simple yet very flexible example of the latter. Where a local quadratic trend is present but not modeled, we show that the quasi-differenced detrended Dickey-Fuller-type test of Elliott et al. (1996) has both size and power which tend to zero asymptotically. An extension of the Elliott et al. (1996) approach to allow for a quadratic trend resolves this problem but is shown to result in large power losses relative to the standard detrended test when no quadratic trend is present. We consequently propose a simple and practical approach to dealing with this form of uncertainty based on a union of rejections-based decision rule whereby the unit root is rejected whenever either of the detrended or quadratic detrended unit root tests rejects. A modification of this basic strategy is also suggested which further improves on the properties of the procedure. An application to relative primary commodity price data highlights the empirical relevance of the methods outlined in this article. A by-product of our analysis is the development of a test for the presence of a quadratic trend which is robust to whether the data admit a unit root. Journal: Econometric Reviews Pages: 514-547 Issue: 5 Volume: 30 Year: 2011 Month: 10 X-DOI: 10.1080/07474938.2011.553561 File-URL: http://hdl.handle.net/10.1080/07474938.2011.553561 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:30:y:2011:i:5:p:514-547 Template-Type: ReDIF-Article 1.0 Author-Name: Manabu Asai Author-X-Name-First: Manabu Author-X-Name-Last: Asai Author-Name: Michael McAleer Author-X-Name-First: Michael Author-X-Name-Last: McAleer Title: Alternative Asymmetric Stochastic Volatility Models Abstract: The stochastic volatility model usually incorporates asymmetric effects by introducing the negative correlation between the innovations in returns and volatility. In this paper, we propose a new asymmetric stochastic volatility model, based on the leverage and size effects. The model is a generalization of the exponential GARCH (EGARCH) model of Nelson (1991). We consider categories for asymmetric effects, which describes the difference among the asymmetric effect of the EGARCH model, the threshold effects indicator function of Glosten et al. (1992), and the negative correlation between the innovations in returns and volatility. The new model is estimated by the efficient importance sampling method of Liesenfeld and Richard (2003), and the finite sample properties of the estimator are investigated using numerical simulations. Four financial time series are used to estimate the alternative asymmetric stochastic volatility (SV) models, with empirical asymmetric effects found to be statistically significant in each case. The empirical results for S&P 500 and Yen/USD returns indicate that the leverage and size effects are significant, supporting the general model. For Tokyo stock price index (TOPIX) and USD/AUD returns, the size effect is insignificant, favoring the negative correlation between the innovations in returns and volatility. We also consider standardized <italic>t</italic> distribution for capturing the tail behavior. The results for Yen/USD returns show that the model is correctly specified, while the results for three other data sets suggest there is scope for improvement. Journal: Econometric Reviews Pages: 548-564 Issue: 5 Volume: 30 Year: 2011 Month: 10 X-DOI: 10.1080/07474938.2011.553156 File-URL: http://hdl.handle.net/10.1080/07474938.2011.553156 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:30:y:2011:i:5:p:548-564 Template-Type: ReDIF-Article 1.0 Author-Name: Andreas C. Drichoutis Author-X-Name-First: Andreas C. Author-X-Name-Last: Drichoutis Author-Name: Rodolfo M. Nayga Author-X-Name-First: Rodolfo M. Author-X-Name-Last: Nayga Title: Marginal Changes in Random Parameters Ordered Response Models with Interaction Terms Abstract: Marginal changes of interacted variables and interaction terms in random parameters ordered response models are calculated incorrectly in econometric softwares. We derive the correct formulas for calculating these marginal changes. In our empirical example, we observe significant changes not only in the magnitude of the marginal effects but also in their standard errors, suggesting that the incorrect estimation of the marginal effects of these variables as is commonly practiced can render biased inferences on the findings. Journal: Econometric Reviews Pages: 565-576 Issue: 5 Volume: 30 Year: 2011 Month: 10 X-DOI: 10.1080/07474938.2011.553564 File-URL: http://hdl.handle.net/10.1080/07474938.2011.553564 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:30:y:2011:i:5:p:565-576 Template-Type: ReDIF-Article 1.0 Author-Name: Jean-Fran�ois Richard Author-X-Name-First: Jean-Fran�ois Author-X-Name-Last: Richard Title: Book Review: Econometric Modeling and Inference Journal: Econometric Reviews Pages: 577-581 Issue: 5 Volume: 30 Year: 2011 Month: 10 X-DOI: 10.1080/07474938.2011.553565 File-URL: http://hdl.handle.net/10.1080/07474938.2011.553565 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:30:y:2011:i:5:p:577-581 Template-Type: ReDIF-Article 1.0 Author-Name: George Kapetanios Author-X-Name-First: George Author-X-Name-Last: Kapetanios Author-Name: Yongcheol Shin Author-X-Name-First: Yongcheol Author-X-Name-Last: Shin Title: Testing the Null Hypothesis of Nonstationary Long Memory Against the Alternative Hypothesis of a Nonlinear Ergodic Model Abstract: Interest in the interface of nonstationarity and nonlinearity has been increasing in the econometric literature. This paper provides a formal method of testing for nonstationary long memory against the alternative of a particular form of nonlinear ergodic processes; namely, exponential smooth transition autoregressive processes. In this regard, the current paper provides a significant generalization to existing unit root tests by allowing the null hypothesis to encompass a much larger class of nonstationary processes. The asymptotic theory associated with the proposed Wald statistic is derived, and Monte Carlo simulation results confirm that the Wald statistics have reasonably correct size and good power in small samples. In an application to real interest rates and the Yen real exchange rates, we find that the tests are able to distinguish between these competing processes in most cases, supporting the long-run Purchasing Power Parity (PPP) and Fisher hypotheses. But, there are a few cases in which long memory and nonlinear ergodic processes display similar characteristics and are thus confused with each other in small samples. Journal: Econometric Reviews Pages: 620-645 Issue: 6 Volume: 30 Year: 2011 Keywords: Long memory I(d) and ESTAR processes, Monte Carlo simulations, Real exchange rates, Real interest rates, The Wald tests, X-DOI: 10.1080/07474938.2011.553568 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474938.2011.553568 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:30:y:2011:i:6:p:620-645 Template-Type: ReDIF-Article 1.0 Author-Name: Jose Luis Aznarte Author-X-Name-First: Jose Luis Author-X-Name-Last: Aznarte Author-Name: Jesus Alcala-Fdez Author-X-Name-First: Jesus Author-X-Name-Last: Alcala-Fdez Author-Name: Antonio Arauzo Author-X-Name-First: Antonio Author-X-Name-Last: Arauzo Author-Name: Jose Manuel Benitez Author-X-Name-First: Jose Manuel Author-X-Name-Last: Benitez Title: Fuzzy Autoregressive Rules: Towards Linguistic Time Series Modeling Abstract: Fuzzy rule-based models, a key element in soft computing (SC), have arisen as an alternative for time series analysis and modeling. One difference with preexisting models is their interpretability in terms of human language. Their interactions with other components have also contributed to a huge development in their identification and estimation procedures. In this article, we present fuzzy rule-based models, their links with some regime-switching autoregressive models, and how the use of soft computing concepts can help the practitioner to solve and gain a deeper insight into a given problem. An example on a realized volatility series is presented to show the forecasting abilities of a fuzzy rule-based model. Journal: Econometric Reviews Pages: 646-668 Issue: 6 Volume: 30 Year: 2011 Keywords: Fuzzy models, Regime-switching models, Soft computing, Time series, Volatility, X-DOI: 10.1080/07474938.2011.553569 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474938.2011.553569 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:30:y:2011:i:6:p:646-668 Template-Type: ReDIF-Article 1.0 Author-Name: Chia-Lin Chang Author-X-Name-First: Chia-Lin Author-X-Name-Last: Chang Author-Name: Michael McAleer Author-X-Name-First: Michael Author-X-Name-Last: McAleer Author-Name: Les Oxley Author-X-Name-First: Les Author-X-Name-Last: Oxley Title: Great Expectatrics: Great Papers, Great Journals, Great Econometrics Abstract: The article discusses alternative Research Assessment Measures (RAM), with an emphasis on the Thomson Reuters ISI Web of Science database (hereafter ISI). Some analysis and comparisons are also made with data from the SciVerse Scopus database. The various RAM that are calculated annually or updated daily are defined and analyzed, including the classic 2-year impact factor (2YIF), 2YIF without journal self-citations (2YIF*), 5-year impact factor (5YIF), Immediacy (or zero-year impact factor (0YIF)), Impact Factor Inflation (IFI), Self-citation Threshold Approval Rating (STAR), Eigenfactor score, Article Influence, C3PO (Citation Performance Per Paper Online), h-index, Zinfluence, and PI-BETA (Papers Ignored - By Even The Authors). The RAM are analyzed for 10 leading econometrics journals and 4 leading statistics journals. The application to econometrics can be used as a template for other areas in economics, for other scientific disciplines, and as a benchmark for newer journals in a range of disciplines. In addition to evaluating high quality research in leading econometrics journals, the paper also compares econometrics and statistics, alternative RAM, highlights the similarities and differences of the alternative RAM, finds that several RAM capture similar performance characteristics for the leading econometrics and statistics journals, while the new PI-BETA criterion is not highly correlated with any of the other RAM, and hence conveys additional information regarding RAM, highlights major research areas in leading journals in econometrics, and discusses some likely future uses of RAM, and shows that the harmonic mean of 13 RAM provides more robust journal rankings than relying solely on 2YIF. Journal: Econometric Reviews Pages: 583-619 Issue: 6 Volume: 30 Year: 2011 Keywords: Article influence, Cited article influence, C3PO, Eigenfactor, IFI, Immediacy, Impact factors, h-Index, PI-BETA, STAR, Research assessment measures, Zinfluence, X-DOI: 10.1080/07474938.2011.586614 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474938.2011.586614 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:30:y:2011:i:6:p:583-619 Template-Type: ReDIF-Article 1.0 Author-Name: Davide Raggi Author-X-Name-First: Davide Author-X-Name-Last: Raggi Author-Name: Silvano Bordignon Author-X-Name-First: Silvano Author-X-Name-Last: Bordignon Title: Volatility, Jumps, and Predictability of Returns: A Sequential Analysis Abstract: In this article we propose a Monte Carlo algorithm for sequential parameter learning for a stochastic volatility model with leverage, nonconstant conditional mean and jumps. We are interested in estimating the time invariant parameters and the nonobservable dynamics involved in the model. Our simple but effective idea relies on the auxiliary particle filter algorithm mixed together with the Markov Chain Monte Carlo (MCMC) methodology. Adding an MCMC step to the auxiliary particle filter prevents numerical degeneracies in the sequential algorithm and allows sequential evaluation of the fixed parameters and the latent processes. Empirical evaluation on simulated and real data is presented to assess the performance of the algorithm. A numerical comparison with a full MCMC procedure is also provided. We also extend our methodology to superposition models in which volatility is obtained by a linear combination of independent processes. Journal: Econometric Reviews Pages: 669-695 Issue: 6 Volume: 30 Year: 2011 Keywords: Auxiliary particle filters, Bayesian estimation, Leverage, MCMC, Return's predictability, Stochastic volatility with jumps, X-DOI: 10.1080/07474938.2011.553570 File-URL: http://www.tandfonline.com/doi/abs/10.1080/07474938.2011.553570 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:30:y:2011:i:6:p:669-695 Template-Type: ReDIF-Article 1.0 Author-Name: Vasilis Sarafidis Author-X-Name-First: Vasilis Author-X-Name-Last: Sarafidis Author-Name: Tom Wansbeek Author-X-Name-First: Tom Author-X-Name-Last: Wansbeek Title: Cross-Sectional Dependence in Panel Data Analysis Abstract: This article provides an overview of the existing literature on panel data models with error cross-sectional dependence (CSD). We distinguish between weak and strong CSD and link these concepts to the spatial and factor structure approaches. We consider estimation under strong and weak exogeneity of the regressors for both <italic>T</italic> fixed and <italic>T</italic> large cases. Available tests for CSD and methods for determining the number of factors are discussed in detail. The finite-sample properties of some estimators and statistics are investigated using Monte Carlo experiments. Journal: Econometric Reviews Pages: 483-531 Issue: 5 Volume: 31 Year: 2012 Month: 9 X-DOI: 10.1080/07474938.2011.611458 File-URL: http://hdl.handle.net/10.1080/07474938.2011.611458 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:31:y:2012:i:5:p:483-531 Template-Type: ReDIF-Article 1.0 Author-Name: Emma M. Iglesias Author-X-Name-First: Emma M. Author-X-Name-Last: Iglesias Author-Name: Garry D. A. Phillips Author-X-Name-First: Garry D. A. Author-X-Name-Last: Phillips Title: Estimation, Testing, and Finite Sample Properties of Quasi-Maximum Likelihood Estimators in GARCH-M Models Abstract: We provide three new results concerning quasi-maximum likelihood (QML) estimators in generalized autoregressive conditional heteroskedastic in mean (GARCH-M) models. We first show that, depending on the functional form that we impose in the mean equation, the properties of the model may change and the conditional variance parameter space may be restricted, in contrast to the theory of traditional GARCH processes. Second, we also present a new test for GARCH effects in the GARCH-M context which is simpler to implement than alternative procedures such as in Beg et al. (2001). We propose a new way of dealing with parameters that are not identified by creating composites of parameters that are identified. Third, the finite sample properties of QML estimators are explored in a restricted ARCH-M model and bias and variance approximations are found which show that the larger the volatility of the process the better the variance parameters are estimated. The invariance properties that Lumsdaine (1995) proved for the traditional GARCH are shown not to hold in the GARCH-M. For those researchers who choose not to rely on the first order asymptotic approximation of our proposed test statistic, we also show how our bias expressions can be used to bias correct the QML estimates with a view to improving the finite sample performance of the test. Finally, we show how our new proposed test works in practice in an empirical economic application. Journal: Econometric Reviews Pages: 532-557 Issue: 5 Volume: 31 Year: 2012 Month: 9 X-DOI: 10.1080/07474938.2011.608007 File-URL: http://hdl.handle.net/10.1080/07474938.2011.608007 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:31:y:2012:i:5:p:532-557 Template-Type: ReDIF-Article 1.0 Author-Name: Roseline Bilina Author-X-Name-First: Roseline Author-X-Name-Last: Bilina Author-Name: Steve Lawford Author-X-Name-First: Steve Author-X-Name-Last: Lawford Title: Python for Unified Research in Econometrics and Statistics Abstract: Python is a powerful high-level open source programming language that is available for multiple platforms. It supports object-oriented programming and has recently become a serious alternative to low-level compiled languages such as C + +. It is easy to learn and use, and is recognized for very fast development times, which makes it suitable for rapid software prototyping as well as teaching purposes. We motivate the use of Python and its free extension modules for high performance stand-alone applications in econometrics and statistics, and as a tool for gluing different applications together. (It is in this sense that Python forms a “unified” environment for statistical research.) We give details on the core language features, which will enable a user to immediately begin work, and then provide practical examples of advanced uses of Python. Finally, we compare the run-time performance of extended Python against a number of commonly-used statistical packages and programming environments. <roman>Supplemental materials are available for this article. Go to the publisher's online edition of</roman> Econometric Reviews <roman>to view the free supplemental file.</roman> Journal: Econometric Reviews Pages: 558-591 Issue: 5 Volume: 31 Year: 2012 Month: 9 X-DOI: 10.1080/07474938.2011.553573 File-URL: http://hdl.handle.net/10.1080/07474938.2011.553573 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:31:y:2012:i:5:p:558-591 Template-Type: ReDIF-Article 1.0 Author-Name: Theodore Alexandrov Author-X-Name-First: Theodore Author-X-Name-Last: Alexandrov Author-Name: Silvia Bianconcini Author-X-Name-First: Silvia Author-X-Name-Last: Bianconcini Author-Name: Estela Bee Dagum Author-X-Name-First: Estela Bee Author-X-Name-Last: Dagum Author-Name: Peter Maass Author-X-Name-First: Peter Author-X-Name-Last: Maass Author-Name: Tucker S. McElroy Author-X-Name-First: Tucker S. Author-X-Name-Last: McElroy Title: A Review of Some Modern Approaches to the Problem of Trend Extraction Abstract: This article presents a review of some modern approaches to trend extraction for one-dimensional time series, which is one of the major tasks of time series analysis. The trend of a time series is usually defined as a smooth additive component which contains information about the time series global change, and we discuss this and other definitions of the trend. We do not aim to review all the novel approaches, but rather to observe the problem from different viewpoints and from different areas of expertise. The article contributes to understanding the concept of a trend and the problem of its extraction. We present an overview of advantages and disadvantages of the approaches under consideration, which are: the model-based approach (MBA), nonparametric linear filtering, singular spectrum analysis (SSA), and wavelets. The MBA assumes the specification of a stochastic time series model, which is usually either an autoregressive integrated moving average (ARIMA) model or a state space model. The nonparametric filtering methods do not require specification of model and are popular because of their simplicity in application. We discuss the Henderson, LOESS, and Hodrick--Prescott filters and their versions derived by exploiting the Reproducing Kernel Hilbert Space methodology. In addition to these prominent approaches, we consider SSA and wavelet methods. SSA is widespread in the geosciences; its algorithm is similar to that of principal components analysis, but SSA is applied to time series. Wavelet methods are the de facto standard for denoising in signal procession, and recent works revealed their potential in trend analysis. Journal: Econometric Reviews Pages: 593-624 Issue: 6 Volume: 31 Year: 2012 Month: 11 X-DOI: 10.1080/07474938.2011.608032 File-URL: http://hdl.handle.net/10.1080/07474938.2011.608032 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:31:y:2012:i:6:p:593-624 Template-Type: ReDIF-Article 1.0 Author-Name: Yi-Ting Chen Author-X-Name-First: Yi-Ting Author-X-Name-Last: Chen Author-Name: Hung-Jen Wang Author-X-Name-First: Hung-Jen Author-X-Name-Last: Wang Title: Centered-Residuals-Based Moment Estimator and Test for Stochastic Frontier Models Abstract: The composed error of a stochastic frontier (SF) model consists of two random variables, and the identification of the model relies heavily on the distribution assumptions for each of these variables. While the literature has put much effort into applying various SF models to a wide range of empirical problems, little has been done to test the distribution assumptions of these two variables. In this article, by exploiting the specification structures of the SF model, we propose a centered-residuals-based method of moments which can be easily and flexibly applied to testing the distribution assumptions on both of the random variables and to estimating the model parameters. A Monte Carlo simulation is conducted to assess the performance of the proposed method. We also provide two empirical examples to demonstrate the use of the proposed estimator and test using real data. Journal: Econometric Reviews Pages: 625-653 Issue: 6 Volume: 31 Year: 2012 Month: 11 X-DOI: 10.1080/07474938.2011.608037 File-URL: http://hdl.handle.net/10.1080/07474938.2011.608037 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:31:y:2012:i:6:p:625-653 Template-Type: ReDIF-Article 1.0 Author-Name: Hans Manner Author-X-Name-First: Hans Author-X-Name-Last: Manner Author-Name: Olga Reznikova Author-X-Name-First: Olga Author-X-Name-Last: Reznikova Title: A Survey on Time-Varying Copulas: Specification, Simulations, and Application Abstract: The aim of this article is to bring together different specifications for copula models with time-varying dependence structure. Copula models are widely used in financial econometrics and risk management. They are considered to be a competitive alternative to the Gaussian dependence structure. The dynamic structure of the dependence between the data can be modeled by allowing either the copula function or the dependence parameter to be time-varying. First, we give a brief description of eight different models, among which there are fully parametric, semiparametric, and adaptive methods. The purpose of this study is to compare the applicability of each particular model in different cases. We conduct a simulation study to show the performance for model selection, to compare the model fit for different setups and to study the ability of the models to estimate the (latent) time-varying dependence parameter. Finally, we provide an illustration by applying the competing models on the same financial dataset and compare their performance by means of Value-at-Risk. Journal: Econometric Reviews Pages: 654-687 Issue: 6 Volume: 31 Year: 2012 Month: 11 X-DOI: 10.1080/07474938.2011.608042 File-URL: http://hdl.handle.net/10.1080/07474938.2011.608042 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:31:y:2012:i:6:p:654-687 Template-Type: ReDIF-Article 1.0 Author-Name: E. Maasoumi Author-X-Name-First: E. Author-X-Name-Last: Maasoumi Author-Name: G. Yalonetzky Author-X-Name-First: G. Author-X-Name-Last: Yalonetzky Title: Introduction to Robustness in Multidimensional Wellbeing Analysis Journal: Econometric Reviews Pages: 1-6 Issue: 1 Volume: 32 Year: 2013 Month: 1 X-DOI: 10.1080/07474938.2012.690650 File-URL: http://hdl.handle.net/10.1080/07474938.2012.690650 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:32:y:2013:i:1:p:1-6 Template-Type: ReDIF-Article 1.0 Author-Name: Koen Decancq Author-X-Name-First: Koen Author-X-Name-Last: Decancq Author-Name: María Ana Lugo Author-X-Name-First: María Ana Author-X-Name-Last: Lugo Title: Weights in Multidimensional Indices of Wellbeing: An Overview Abstract: Multidimensional indices are becoming increasingly important instruments to assess the wellbeing of societies. They move beyond the focus on a single indicator and yet they are easy to present and communicate. A crucial step in the construction of a multidimensional index of wellbeing is the selection of the relative weights for the different dimensions. The aim of this article is to study the role of these weights and to critically survey eight different approaches to set them. We categorize the approaches in three classes: data-driven, normative, and hybrid weighting, and compare their respective advantages and drawbacks. Journal: Econometric Reviews Pages: 7-34 Issue: 1 Volume: 32 Year: 2013 Month: 1 X-DOI: 10.1080/07474938.2012.690641 File-URL: http://hdl.handle.net/10.1080/07474938.2012.690641 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:32:y:2013:i:1:p:7-34 Template-Type: ReDIF-Article 1.0 Author-Name: James E. Foster Author-X-Name-First: James E. Author-X-Name-Last: Foster Author-Name: Mark McGillivray Author-X-Name-First: Mark Author-X-Name-Last: McGillivray Author-Name: Suman Seth Author-X-Name-First: Suman Author-X-Name-Last: Seth Title: Composite Indices: Rank Robustness, Statistical Association, and Redundancy Abstract: This article evaluates the robustness of rankings obtained from composite indices that combine information from two or more components via a weighted sum. It examines the empirical prevalence of robust comparisons using the method proposed by Foster et al. (2010). Indices examined are the Human Development Index (HDI), the Index of Economic Freedom (IEF), and the Environmental Performance Index (EPI). Key theoretical results demonstrate links between the prevalence of robust comparisons, Kendall's tau rank correlation coefficient, and statistical association across components. Implications for redundancy among index components are also examined. Journal: Econometric Reviews Pages: 35-56 Issue: 1 Volume: 32 Year: 2013 Month: 1 X-DOI: 10.1080/07474938.2012.690647 File-URL: http://hdl.handle.net/10.1080/07474938.2012.690647 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:32:y:2013:i:1:p:35-56 Template-Type: ReDIF-Article 1.0 Author-Name: Christopher J. Bennett Author-X-Name-First: Christopher J. Author-X-Name-Last: Bennett Author-Name: Shabana Mitra Author-X-Name-First: Shabana Author-X-Name-Last: Mitra Title: Multidimensional Poverty: Measurement, Estimation, and Inference Abstract: Multidimensional poverty measures give rise to a host of statistical hypotheses that are of interest to applied economists and policy-makers alike. In the specific context of the generalized Alkire--Foster (Alkire and Foster, 2008) class of measures, we show that many of these hypotheses can be treated in a unified manner and also tested simultaneously using a minimum <italic>p</italic>-value approach. When applied to study the relative state of poverty among Hindus and Muslims in India, these tests reveal novel insights into the plight of the poor which are not otherwise captured by traditional univariate approaches. Journal: Econometric Reviews Pages: 57-83 Issue: 1 Volume: 32 Year: 2013 Month: 1 X-DOI: 10.1080/07474938.2012.690331 File-URL: http://hdl.handle.net/10.1080/07474938.2012.690331 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:32:y:2013:i:1:p:57-83 Template-Type: ReDIF-Article 1.0 Author-Name: Russell Davidson Author-X-Name-First: Russell Author-X-Name-Last: Davidson Author-Name: Jean-Yves Duclos Author-X-Name-First: Jean-Yves Author-X-Name-Last: Duclos Title: Testing for Restricted Stochastic Dominance Abstract: Asymptotic and bootstrap tests are studied for testing whether there is a relation of stochastic dominance between two distributions. These tests have a null hypothesis of nondominance, with the advantage that, if this null is rejected, then all that is left is dominance. This also leads us to define and focus on <italic>restricted</italic> stochastic dominance, the only empirically useful form of dominance relation that we can seek to infer in many settings. One testing procedure that we consider is based on an empirical likelihood ratio. The computations necessary for obtaining a test statistic also provide estimates of the distributions under study that satisfy the null hypothesis, on the frontier between dominance and nondominance. These estimates can be used to perform dominance tests that can turn out to provide much improved reliability of inference compared with the asymptotic tests so far proposed in the literature. Journal: Econometric Reviews Pages: 84-125 Issue: 1 Volume: 32 Year: 2013 Month: 1 X-DOI: 10.1080/07474938.2012.690332 File-URL: http://hdl.handle.net/10.1080/07474938.2012.690332 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:32:y:2013:i:1:p:84-125 Template-Type: ReDIF-Article 1.0 Author-Name: Gaston Yalonetzky Author-X-Name-First: Gaston Author-X-Name-Last: Yalonetzky Title: Stochastic Dominance with Ordinal Variables: Conditions and a Test Abstract: A re-emerging literature on robustness in multidimensional welfare and poverty comparisons has revived interest in multidimensional stochastic dominance. Considering the widespread use of ordinal variables in wellbeing measurement, and particularly in composite indices, I derive multivariate stochastic dominance conditions for ordinal variables. These are the analogues of the conditions for continuous variables (e.g., Bawa, 1975, and Atkinson and Bourguignon, 1982). The article also derives mixed-order-of-dominance conditions for any type of variable. Then I propose an extension of Anderson's nonparametric test in order to test these conditions for ordinal variables. In addition, I propose the use of <italic>vectors and matrices of positions</italic> in order to handle multivariate, multinomial distributions. An empirical application to multidimensional wellbeing in Peru illustrates these tests. Journal: Econometric Reviews Pages: 126-163 Issue: 1 Volume: 32 Year: 2013 Month: 1 X-DOI: 10.1080/07474938.2012.690653 File-URL: http://hdl.handle.net/10.1080/07474938.2012.690653 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:32:y:2013:i:1:p:126-163 Template-Type: ReDIF-Article 1.0 Author-Name: Gordon Anderson Author-X-Name-First: Gordon Author-X-Name-Last: Anderson Author-Name: Kinda Hachem Author-X-Name-First: Kinda Author-X-Name-Last: Hachem Title: Institutions and Economic Outcomes: A Dominance-Based Analysis Abstract: An important issue in both welfare and development economics is the interaction between institutions and economic outcomes. While welfarists are typically concerned with how these variables contribute to overall wellbeing, empirical assessments of their joint contribution are limited. Development economists, on the other hand, have focused extensively on whether institutions cause or are caused by growth yet the relevant literature is still rife with debate. In this article, we use a notion of distributional dominance to tackle both the measurement of multivariate welfare and the evaluation of inter-temporal dependence without hindrance from the mix of discrete (political) and continuous (economic) variables in our data set. On the causality front, our results support the view that institutions promote growth more than growth promotes institutions. On the welfare front, we find that economic growth had a positive impact from 1960 to 2000 but declines in institutional quality over the earlier part of this period were sufficient to produce a decline in overall wellbeing until the mid-1970s. Subsequent improvements in institutions then reversed the trend and, ultimately, wellbeing in 2000 was higher than that in 1960. Journal: Econometric Reviews Pages: 164-182 Issue: 1 Volume: 32 Year: 2013 Month: 1 X-DOI: 10.1080/07474938.2012.690330 File-URL: http://hdl.handle.net/10.1080/07474938.2012.690330 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:32:y:2013:i:1:p:164-182 Template-Type: ReDIF-Article 1.0 Author-Name: Christoph Hanck Author-X-Name-First: Christoph Author-X-Name-Last: Hanck Title: An Intersection Test for Panel Unit Roots Abstract: This article proposes a new panel unit root test based on Simes’ (1986) classical intersection test. The test is robust to general patterns of cross-sectional dependence and yet is straightforward to implement, only requiring <italic>p</italic>-values of time series unit root tests of the series in the panel, and no resampling. Monte Carlo experiments show good size and power properties relative to existing panel unit root tests. Unlike previously suggested tests, the new test allows to identify the units in the panel for which the alternative of stationarity can be said to hold. We provide an empirical application to real exchange rate data. Journal: Econometric Reviews Pages: 183-203 Issue: 2 Volume: 32 Year: 2013 Month: 2 X-DOI: 10.1080/07474938.2011.608058 File-URL: http://hdl.handle.net/10.1080/07474938.2011.608058 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:32:y:2013:i:2:p:183-203 Template-Type: ReDIF-Article 1.0 Author-Name: Giuseppe Cavaliere Author-X-Name-First: Giuseppe Author-X-Name-Last: Cavaliere Author-Name: Iliyan Georgiev Author-X-Name-First: Iliyan Author-X-Name-Last: Georgiev Author-Name: A. M. Robert Taylor Author-X-Name-First: A. M. Author-X-Name-Last: Robert Taylor Title: Wild Bootstrap of the Sample Mean in the Infinite Variance Case Abstract: It is well known that the standard independent, identically distributed (iid) bootstrap of the mean is inconsistent in a location model with infinite variance (α-stable) innovations. This occurs because the bootstrap distribution of a normalised sum of infinite variance random variables tends to a random distribution. Consistent bootstrap algorithms based on subsampling methods have been proposed but have the drawback that they deliver much wider confidence sets than those generated by the iid bootstrap owing to the fact that they eliminate the dependence of the bootstrap distribution on the sample extremes. In this paper we propose sufficient conditions that allow a simple modification of the bootstrap (Wu, 1986) to be consistent (in a conditional sense) yet to also reproduce the narrower confidence sets of the iid bootstrap. Numerical results demonstrate that our proposed bootstrap method works very well in practice delivering coverage rates very close to the nominal level and significantly narrower confidence sets than other consistent methods. Journal: Econometric Reviews Pages: 204-219 Issue: 2 Volume: 32 Year: 2013 Month: 2 X-DOI: 10.1080/07474938.2012.690660 File-URL: http://hdl.handle.net/10.1080/07474938.2012.690660 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:32:y:2013:i:2:p:204-219 Template-Type: ReDIF-Article 1.0 Author-Name: Alan J. Rogers Author-X-Name-First: Alan J. Author-X-Name-Last: Rogers Title: Concentration Ellipsoids, Their Planes of Support, and the Linear Regression Model Abstract: The relationship between the concentration ellipsoid of a random vector and its planes of support is exploited to provide a geometric derivation and interpretation of existing results for a general form of the linear regression model. In particular, the planes of support whose points of tangency to the ellipsoid are contained in the range (or column space) of the design matrix are the source of all linear unbiased minimum variance estimators. The connection between this idea and estimators based on projections is explored, as is also its use in obtaining and interpreting some existing relative efficiency results. Journal: Econometric Reviews Pages: 220-243 Issue: 2 Volume: 32 Year: 2013 Month: 2 X-DOI: 10.1080/07474938.2011.608055 File-URL: http://hdl.handle.net/10.1080/07474938.2011.608055 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:32:y:2013:i:2:p:220-243 Template-Type: ReDIF-Article 1.0 Author-Name: Sarantis Tsiaplias Author-X-Name-First: Sarantis Author-X-Name-Last: Tsiaplias Author-Name: Chew Lian Chua Author-X-Name-First: Chew Lian Author-X-Name-Last: Chua Title: A Multivariate GARCH Model Incorporating the Direct and Indirect Transmission of Shocks Abstract: Theoretical models of contagion and spillovers allow for asset-specific shocks that can be directly transmitted from one asset to another, as well as indirectly transmitted across uncorrelated assets through some intermediary mechanism. Standard multivariate Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models, however, provide estimates of volatilities and correlations based only on the direct transmission of shocks across assets. As such, spillover effects via an intermediary asset or market are not considered. In this article, a multivariate GARCH model is constructed that provides estimates of volatilities and correlations based on both directly and indirectly transmitted shocks. The model is applied to exchange rate and equity returns data. The results suggest that if a spillover component is observed in the data, the spillover augmented models provide significantly different volatility estimates compared to standard multivariate GARCH models. Journal: Econometric Reviews Pages: 244-271 Issue: 2 Volume: 32 Year: 2013 Month: 2 X-DOI: 10.1080/07474938.2011.608045 File-URL: http://hdl.handle.net/10.1080/07474938.2011.608045 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:32:y:2013:i:2:p:244-271 Template-Type: ReDIF-Article 1.0 Author-Name: Halbert White Author-X-Name-First: Halbert Author-X-Name-Last: White Author-Name: Karim Chalak Author-X-Name-First: Karim Author-X-Name-Last: Chalak Title: Identification and Identification Failure for Treatment Effects Using Structural Systems Abstract: We provide necessary and sufficient conditions for effect identification, thereby characterizing the limits to identification. Our results link the nonstructural potential outcome framework for identifying and estimating treatment effects to structural approaches in economics. This permits economic theory to be built into treatment effect methods. We elucidate the sources and consequences of identification failure by examining the biases arising when the necessary conditions fail, and we clarify the relations between unconfoundedness, conditional exogeneity, and the necessary and sufficient identification conditions. A new quantity, the exogeneity score, plays a central role in this analysis, permitting an omitted variable representation for effect biases. This analysis also provides practical guidance for selecting covariates and insight into the price paid for making various identifying assumptions and the benefits gained. Journal: Econometric Reviews Pages: 273-317 Issue: 3 Volume: 32 Year: 2013 Month: 11 X-DOI: 10.1080/07474938.2012.690664 File-URL: http://hdl.handle.net/10.1080/07474938.2012.690664 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:32:y:2013:i:3:p:273-317 Template-Type: ReDIF-Article 1.0 Author-Name: Alex Maynard Author-X-Name-First: Alex Author-X-Name-Last: Maynard Author-Name: Aaron Smallwood Author-X-Name-First: Aaron Author-X-Name-Last: Smallwood Author-Name: Mark E. Wohar Author-X-Name-First: Mark E. Author-X-Name-Last: Wohar Title: Long Memory Regressors and Predictive Testing: A Two-stage Rebalancing Approach Abstract: Predictability tests with long memory regressors may entail both size distortion and incompatibility between the orders of integration of the dependent and independent variables. Addressing both problems simultaneously, this paper proposes a two-step procedure that rebalances the predictive regression by fractionally differencing the predictor based on a first-stage estimation of the memory parameter. Extensive simulations indicate that our procedure has good size, is robust to estimation error in the first stage, and can yield improved power over cases in which an integer order is assumed for the regressor. We also extend our approach beyond the standard predictive regression context to cases in which the dependent variable is also fractionally integrated, but not cointegrated with the regressor. We use our procedure to provide a valid test of forward rate unbiasedness that allows for a long memory forward premium. Journal: Econometric Reviews Pages: 318-360 Issue: 3 Volume: 32 Year: 2013 Month: 11 X-DOI: 10.1080/07474938.2012.690663 File-URL: http://hdl.handle.net/10.1080/07474938.2012.690663 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:32:y:2013:i:3:p:318-360 Template-Type: ReDIF-Article 1.0 Author-Name: Jonathan B. Hill Author-X-Name-First: Jonathan B. Author-X-Name-Last: Hill Title: Consistent GMM Residuals-Based Tests of Functional Form Abstract: This paper presents a consistent Generalized Method of Moments (GMM) residuals-based test of functional form for time series models. By relating two moments we deliver a vector moment condition in which at least one element must be nonzero if the model is misspecified. The test will never fail to detect misspecification of any form for large samples, and is asymptotically chi-squared under the null, allowing for fast and simple inference. A simulation study reveals randomly selecting the nuisance parameter leads to more power than supremum-tests, and can obtain empirical power nearly equivalent to the most powerful test for even relatively small <italic>n</italic>. Journal: Econometric Reviews Pages: 361-383 Issue: 3 Volume: 32 Year: 2013 Month: 11 X-DOI: 10.1080/07474938.2012.690662 File-URL: http://hdl.handle.net/10.1080/07474938.2012.690662 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:32:y:2013:i:3:p:361-383 Template-Type: ReDIF-Article 1.0 Author-Name: Markus Frölich Author-X-Name-First: Markus Author-X-Name-Last: Frölich Author-Name: Blaise Melly Author-X-Name-First: Blaise Author-X-Name-Last: Melly Title: Identification of Treatment Effects on the Treated with One-Sided Non-Compliance Abstract: Traditional instrumental variable estimators do not generally estimate effects for the treated population but for the unobserved population of compliers. On the other hand, when there is one-sided non-compliance, they do identify effects for the treated because the populations of treated and compliers are identical in this case. However, this property is lost when <italic>covariates are included in the model</italic>. In this case, we show that the effects for the treated are still identified but require modified estimators. We consider both average and quantile treatment effects and allow the instrument to be discrete or continuous. Journal: Econometric Reviews Pages: 384-414 Issue: 3 Volume: 32 Year: 2013 Month: 11 X-DOI: 10.1080/07474938.2012.718684 File-URL: http://hdl.handle.net/10.1080/07474938.2012.718684 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:32:y:2013:i:3:p:384-414 Template-Type: ReDIF-Article 1.0 Author-Name: Yong Bao Author-X-Name-First: Yong Author-X-Name-Last: Bao Title: On Sample Skewness and Kurtosis Abstract: It is well documented in the literature that the sample skewness and excess kurtosis can be severely biased in finite samples. In this paper, we derive analytical results for their finite-sample biases up to the second order. In general, the bias results depend on the cumulants (up to the sixth order) as well as the dependency structure of the data. Using an AR(1) process for illustration, we show that a feasible bias-correction procedure based on our analytical results works remarkably well for reducing the bias of the sample skewness. Bias-correction works reasonably well also for the sample kurtosis under some moderate degree of dependency. In terms of hypothesis testing, bias-correction offers power improvement when testing for normality, and bias-correction under the null provides also size improvement. However, for testing nonzero skewness and/or excess kurtosis, there exist nonnegligible size distortions in finite samples and bias-correction may not help. Journal: Econometric Reviews Pages: 415-448 Issue: 4 Volume: 32 Year: 2013 Month: 12 X-DOI: 10.1080/07474938.2012.690665 File-URL: http://hdl.handle.net/10.1080/07474938.2012.690665 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:32:y:2013:i:4:p:415-448 Template-Type: ReDIF-Article 1.0 Author-Name: C. Gourieroux Author-X-Name-First: C. Author-X-Name-Last: Gourieroux Author-Name: A. Monfort Author-X-Name-First: A. Author-X-Name-Last: Monfort Title: Granularity Adjustment for Efficient Portfolios Abstract: This article considers large portfolios of assets submitted to both systematic and unsystematic (or idiosyncratic) risks. The idiosyncratic risks can be fully diversified if the portfolio size is infinite, but only partly diversified otherwise. The granularity adjustment measures the effect of partly diversifying idiosyncratic risks. We derive the granularity adjustments for a portfolio with naive diversification and for the efficient mean-variance portfolio allocation. We consider in particular the Sharpe performances, with and without short-sale restrictions and we highlight the effect of concentration risk. Journal: Econometric Reviews Pages: 449-468 Issue: 4 Volume: 32 Year: 2013 Month: 12 X-DOI: 10.1080/07474938.2012.690667 File-URL: http://hdl.handle.net/10.1080/07474938.2012.690667 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:32:y:2013:i:4:p:449-468 Template-Type: ReDIF-Article 1.0 Author-Name: Sainan Jin Author-X-Name-First: Sainan Author-X-Name-Last: Jin Author-Name: Liangjun Su Author-X-Name-First: Liangjun Author-X-Name-Last: Su Title: A Nonparametric Poolability Test for Panel Data Models with Cross Section Dependence Abstract: In this article we propose a nonparametric test for poolability in large dimensional semiparametric panel data models with cross-section dependence based on the sieve estimation technique. To construct the test statistic, we only need to estimate the model under the alternative. We establish the asymptotic normal distributions of our test statistic under the null hypothesis of poolability and a sequence of local alternatives, and prove the consistency of our test. We also suggest a bootstrap method as an alternative way to obtain the critical values. A small set of Monte Carlo simulations indicate the test performs reasonably well in finite samples. Journal: Econometric Reviews Pages: 469-512 Issue: 4 Volume: 32 Year: 2013 Month: 12 X-DOI: 10.1080/07474938.2012.690669 File-URL: http://hdl.handle.net/10.1080/07474938.2012.690669 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:32:y:2013:i:4:p:469-512 Template-Type: ReDIF-Article 1.0 Author-Name: Brennan S. Thompson Author-X-Name-First: Brennan S. Author-X-Name-Last: Thompson Title: Empirical Likelihood-Based Inference for Poverty Measures with Relative Poverty Lines Abstract: In this article, we propose an empirical likelihood-based method of inference for decomposable poverty measures utilizing poverty lines which are some fraction of the median of the underlying income distribution. Specifically, we focus on making poverty comparisons between two subgroups of the population which share the same poverty line. Our proposed method is assessed using a Monte Carlo simulation and is applied to some Canadian household income data. Journal: Econometric Reviews Pages: 513-523 Issue: 4 Volume: 32 Year: 2013 Month: 12 X-DOI: 10.1080/07474938.2012.690671 File-URL: http://hdl.handle.net/10.1080/07474938.2012.690671 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:32:y:2013:i:4:p:513-523 Template-Type: ReDIF-Article 1.0 Author-Name: M. Ryan Haley Author-X-Name-First: M. Ryan Author-X-Name-Last: Haley Author-Name: M. Kevin McGee Author-X-Name-First: M. Kevin Author-X-Name-Last: McGee Author-Name: Todd B. Walker Author-X-Name-First: Todd B. Author-X-Name-Last: Walker Title: Disparity, Shortfall, and Twice-Endogenous HARA Utility Abstract: We derive a mapping between the shortfall-minimizing portfolio selection based on higher-order entropy measures and expected utility theory. We show that the family of HARA utility functions has a minimum-divergence, shortfall-based representation. This facilitates an interpretation in which the risk aversion parameters and the type of risk aversion arise endogenously. We provide a numerical example illustrating this interpretation. Journal: Econometric Reviews Pages: 524-541 Issue: 4 Volume: 32 Year: 2013 Month: 12 X-DOI: 10.1080/07474938.2012.690672 File-URL: http://hdl.handle.net/10.1080/07474938.2012.690672 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:32:y:2013:i:4:p:524-541 Template-Type: ReDIF-Article 1.0 Author-Name: Badi H. Baltagi Author-X-Name-First: Badi H. Author-X-Name-Last: Baltagi Author-Name: Esfandiar Maasoumi Author-X-Name-First: Esfandiar Author-X-Name-Last: Maasoumi Title: An Overview of Dependence in Cross-Section, Time-Series, and Panel Data Journal: Econometric Reviews Pages: 543-546 Issue: 5-6 Volume: 32 Year: 2013 Month: 8 X-DOI: 10.1080/07474938.2012.740957 File-URL: http://hdl.handle.net/10.1080/07474938.2012.740957 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:32:y:2013:i:5-6:p:543-546 Template-Type: ReDIF-Article 1.0 Author-Name: Joakim Westerlund Author-X-Name-First: Joakim Author-X-Name-Last: Westerlund Author-Name: Jörg Breitung Author-X-Name-First: Jörg Author-X-Name-Last: Breitung Title: Lessons from a Decade of IPS and LLC Abstract: This paper points to some of the facts that have emerged from 20 years of research into the analysis of unit roots in panel data, an area that has been heavily influenced by two studies, IPS (Im, Pesaran, and Shin, 2003) and LLC (Levin et al., 2002). Some of these facts are known, others are not. But they all have in common that, if ignored, the effects can be very serious. This is demonstrated using both simulations and theoretical arguments. Journal: Econometric Reviews Pages: 547-591 Issue: 5-6 Volume: 32 Year: 2013 Month: 8 X-DOI: 10.1080/07474938.2013.741023 File-URL: http://hdl.handle.net/10.1080/07474938.2013.741023 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:32:y:2013:i:5-6:p:547-591 Template-Type: ReDIF-Article 1.0 Author-Name: Alexander Chudik Author-X-Name-First: Alexander Author-X-Name-Last: Chudik Author-Name: M. Hashem Pesaran Author-X-Name-First: M. Hashem Author-X-Name-Last: Pesaran Title: Econometric Analysis of High Dimensional VARs Featuring a Dominant Unit Abstract: This paper extends the analysis of infinite dimensional vector autoregressive (IVAR) models proposed in Chudik and Pesaran (2011) to the case where one of the variables or the cross-section units in the IVAR model is dominant or pervasive. It is an important extension from empirical as well theoretical perspectives. In the theory of networks a dominant unit is the centre node of a star network and arises as an efficient outcome of a distance-based utility model. Empirically, the extension poses a number of technical challenges that goes well beyond the analysis of IVAR models provided in Chudik and Pesaran. This is because the dominant unit influences the rest of the variables in the IVAR model both directly and indirectly, and its effects do not vanish as the dimension of the model (N) tends to infinity. The dominant unit acts as a dynamic factor in the regressions of the non-dominant units and yields an infinite order distributed lag relationship between the two types of units. Despite this it is shown that the effects of the dominant unit as well as those of the neighborhood units can be consistently estimated by running augmented least squares regressions that include distributed lag functions of the dominant unit and its neighbors (if any). The asymptotic distribution of the estimators is derived and their small sample properties investigated by means of Monte Carlo experiments. Journal: Econometric Reviews Pages: 592-649 Issue: 5-6 Volume: 32 Year: 2013 Month: 8 X-DOI: 10.1080/07474938.2012.740374 File-URL: http://hdl.handle.net/10.1080/07474938.2012.740374 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:32:y:2013:i:5-6:p:592-649 Template-Type: ReDIF-Article 1.0 Author-Name: Badi H. Baltagi Author-X-Name-First: Badi H. Author-X-Name-Last: Baltagi Author-Name: Peter Egger Author-X-Name-First: Peter Author-X-Name-Last: Egger Author-Name: Michael Pfaffermayr Author-X-Name-First: Michael Author-X-Name-Last: Pfaffermayr Title: A Generalized Spatial Panel Data Model with Random Effects Abstract: This paper proposes a generalized panel data model with random effects and first-order spatially autocorrelated residuals that encompasses two previously suggested specifications. The first one is described in Anselin's (1988) book and the second one by Kapoor et al. (2007). Our encompassing specification allows us to test for these models as restricted specifications. In particular, we derive three Lagrange multiplier (LM) and likelihood ration (LR) tests that restrict our generalized model to obtain (i) the Anselin model, (ii) the Kapoor, Kelejian, and Prucha model, and (iii) the simple random effects model that ignores the spatial correlation in the residuals. For two of these three tests, we obtain closed form solutions and we derive their large sample distributions. Our Monte Carlo results show that the suggested tests are powerful in testing for these restricted specifications even in small and medium sized samples. Journal: Econometric Reviews Pages: 650-685 Issue: 5-6 Volume: 32 Year: 2013 Month: 8 X-DOI: 10.1080/07474938.2012.742342 File-URL: http://hdl.handle.net/10.1080/07474938.2012.742342 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:32:y:2013:i:5-6:p:650-685 Template-Type: ReDIF-Article 1.0 Author-Name: David M. Drukker Author-X-Name-First: David M. Author-X-Name-Last: Drukker Author-Name: Peter Egger Author-X-Name-First: Peter Author-X-Name-Last: Egger Author-Name: Ingmar R. Prucha Author-X-Name-First: Ingmar R. Author-X-Name-Last: Prucha Title: On Two-Step Estimation of a Spatial Autoregressive Model with Autoregressive Disturbances and Endogenous Regressors Abstract: In this paper, we consider a spatial-autoregressive model with autoregressive disturbances, where we allow for endogenous regressors in addition to a spatial lag of the dependent variable. We suggest a two-step generalized method of moments (GMM) and instrumental variable (IV) estimation approach extending earlier work by, e.g., Kelejian and Prucha (1998, 1999). In contrast to those papers, we not only prove consistency for our GMM estimator for the spatial-autoregressive parameter in the disturbance process, but we also derive the joint limiting distribution for our GMM estimator and the IV estimator for the regression parameters. Thus the theory allows for a joint test of zero spatial interactions in the dependent variable, the exogenous variables and the disturbances. The paper also provides a Monte Carlo study to illustrate the performance of the estimator in small samples. Journal: Econometric Reviews Pages: 686-733 Issue: 5-6 Volume: 32 Year: 2013 Month: 8 X-DOI: 10.1080/07474938.2013.741020 File-URL: http://hdl.handle.net/10.1080/07474938.2013.741020 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:32:y:2013:i:5-6:p:686-733 Template-Type: ReDIF-Article 1.0 Author-Name: Xiaodong Liu Author-X-Name-First: Xiaodong Author-X-Name-Last: Liu Author-Name: Lung-Fei Lee Author-X-Name-First: Lung-Fei Author-X-Name-Last: Lee Title: Two-Stage Least Squares Estimation of Spatial Autoregressive Models with Endogenous Regressors and Many Instruments Abstract: This paper considers the IV estimation of spatial autoregressive models with endogenous regressors in the presence of many instruments. To improve asymptotic efficiency, it may be desirable to use many valid instruments. However, finite sample properties of IV estimators can be sensitive to the number of instruments. For a spatial model with endogenous regressors, this paper derives the asymptotic distribution of the two-stage least squares (2SLS) estimator when the number of instruments grows with the sample size, and suggests a bias-correction procedure based on the leading-order many-instrument bias. The paper also gives the Nagar-type approximate mean square errors (MSEs) of the 2SLS estimator and the bias-corrected 2SLS estimator, which can be minimized to choose instruments as in Donald and Newey (2001). A limited Monte Carlo experiment is carried out to study the finite sample performance of the instrument selection procedure. Journal: Econometric Reviews Pages: 734-753 Issue: 5-6 Volume: 32 Year: 2013 Month: 8 X-DOI: 10.1080/07474938.2013.741018 File-URL: http://hdl.handle.net/10.1080/07474938.2013.741018 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:32:y:2013:i:5-6:p:734-753 Template-Type: ReDIF-Article 1.0 Author-Name: Xiao Huang Author-X-Name-First: Xiao Author-X-Name-Last: Huang Title: Nonparametric Estimation in Large Panels with Cross-Sectional Dependence Abstract: In this paper we consider nonparametric estimation in panel data under cross-sectional dependence. Both the number of cross-sectional units (N) and the time dimension of the panel (T) are assumed to be large, and the cross-sectional dependence has a multifactor structure. Local linear regression is used to filter the unobserved cross-sectional factors and to estimate the nonparametric conditional mean. A Monte Carlo simulation study shows that the proposed estimator yields good finite sample properties. Journal: Econometric Reviews Pages: 754-777 Issue: 5-6 Volume: 32 Year: 2013 Month: 8 X-DOI: 10.1080/07474938.2013.740998 File-URL: http://hdl.handle.net/10.1080/07474938.2013.740998 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:32:y:2013:i:5-6:p:754-777 Template-Type: ReDIF-Article 1.0 Author-Name: Jennie Bai Author-X-Name-First: Jennie Author-X-Name-Last: Bai Author-Name: Eric Ghysels Author-X-Name-First: Eric Author-X-Name-Last: Ghysels Author-Name: Jonathan H. Wright Author-X-Name-First: Jonathan H. Author-X-Name-Last: Wright Title: State Space Models and MIDAS Regressions Abstract: We examine the relationship between Mi(xed) Da(ta) S(ampling) (MIDAS) regressions and the Kalman filter when forecasting with mixed frequency data. In general, state space models involve a system of equations, whereas MIDAS regressions involve a single equation. As a consequence, MIDAS regressions might be less efficient, but could also be less prone to parameter estimation error and/or specification errors. We examine how MIDAS regressions and Kalman filters match up under ideal circumstances, that is in population, and in cases where all the stochastic processes—low and high frequency—are correctly specified. We characterize cases where the MIDAS regression exactly replicates the steady state Kalman filter weights. We compare MIDAS and Kalman filter forecasts in population where the state space model is misspecified. We also compare MIDAS and Kalman filter forecasts in small samples. The paper concludes with an empirical application. Overall we find that the MIDAS and Kalman filter methods give similar forecasts. In most cases, the Kalman filter is a bit more accurate, but it is also computationally much more demanding. Journal: Econometric Reviews Pages: 779-813 Issue: 7 Volume: 32 Year: 2013 Month: 10 X-DOI: 10.1080/07474938.2012.690675 File-URL: http://hdl.handle.net/10.1080/07474938.2012.690675 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:32:y:2013:i:7:p:779-813 Template-Type: ReDIF-Article 1.0 Author-Name: Giuseppe Cavaliere Author-X-Name-First: Giuseppe Author-X-Name-Last: Cavaliere Author-Name: A. M. Robert Taylor Author-X-Name-First: A. M. Robert Author-X-Name-Last: Taylor Author-Name: Carsten Trenkler Author-X-Name-First: Carsten Author-X-Name-Last: Trenkler Title: Bootstrap Cointegration Rank Testing: The Role of Deterministic Variables and Initial Values in the Bootstrap Recursion Abstract: In this paper we investigate the role of deterministic components and initial values in bootstrap likelihood ratio type tests of cointegration rank. A number of bootstrap procedures have been proposed in the recent literature some of which include estimated deterministic components and nonzero initial values in the bootstrap recursion while others do the opposite. To date, however, there has not been a study into the relative performance of these two alternative approaches. In this paper we fill this gap in the literature and consider the impact of these choices on both ordinary least squares (OLS) and generalized least squares (GLS) detrended tests, in the case of the latter proposing a new bootstrap algorithm as part of our analysis. Overall, for OLS detrended tests our findings suggest that it is preferable to take the computationally simpler approach of not including estimated deterministic components in the bootstrap recursion and setting the initial values of the bootstrap recursion to zero. For GLS detrended tests, we find that the approach of Trenkler (2009), who includes a restricted estimate of the deterministic component in the bootstrap recursion, can improve finite sample behavior further. Journal: Econometric Reviews Pages: 814-847 Issue: 7 Volume: 32 Year: 2013 Month: 10 X-DOI: 10.1080/07474938.2012.690677 File-URL: http://hdl.handle.net/10.1080/07474938.2012.690677 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:32:y:2013:i:7:p:814-847 Template-Type: ReDIF-Article 1.0 Author-Name: Estela Bee Dagum Author-X-Name-First: Estela Bee Author-X-Name-Last: Dagum Author-Name: Silvia Bianconcini Author-X-Name-First: Silvia Author-X-Name-Last: Bianconcini Title: A Unified View of Nonparametric Trend-Cycle Predictors Via Reproducing Kernel Hilbert Spaces Abstract: We provide a common approach for studying several nonparametric estimators used for smoothing functional time series data. Linear filters based on different building assumptions are transformed into kernel functions via reproducing kernel Hilbert spaces. For each estimator, we identify a density function or second order kernel, from which a hierarchy of higher order estimators is derived. These are shown to give excellent representations for the currently applied symmetric filters. In particular, we derive equivalent kernels of smoothing splines in Sobolev and polynomial spaces. The asymmetric weights are obtained by adapting the kernel functions to the length of the various filters, and a theoretical and empirical comparison is made with the classical estimators used in real time analysis. The former are shown to be superior in terms of signal passing, noise suppression and speed of convergence to the symmetric filter. Journal: Econometric Reviews Pages: 848-867 Issue: 7 Volume: 32 Year: 2013 Month: 10 X-DOI: 10.1080/07474938.2012.690674 File-URL: http://hdl.handle.net/10.1080/07474938.2012.690674 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:32:y:2013:i:7:p:848-867 Template-Type: ReDIF-Article 1.0 Author-Name: Stephan Smeekes Author-X-Name-First: Stephan Author-X-Name-Last: Smeekes Title: Detrending Bootstrap Unit Root Tests Abstract: The role of detrending in bootstrap unit root tests is investigated. When bootstrapping, detrending must not only be done for the construction of the test statistic, but also in the first step of the bootstrap algorithm. It is argued that the two issues should be treated separately. Asymptotic validity of sieve bootstrap augmented Dickey--Fuller (ADF) unit root tests is shown for test statistics based on full sample and recursive ordinary least squares (OLS) and generalized least squares (GLS) detrending. It is also shown that the detrending method in the first step of the bootstrap may differ from the one used in the construction of the test statistic. A simulation study is conducted to analyze the effects of detrending on finite sample performance of the bootstrap test. It is found that full sample OLS detrending should be preferred based on power in the first step of the bootstrap algorithm, and that the decision about the detrending method used to obtain the test statistic should be based on the power properties of the corresponding asymptotic tests. Journal: Econometric Reviews Pages: 869-891 Issue: 8 Volume: 32 Year: 2013 Month: 11 X-DOI: 10.1080/07474938.2012.690693 File-URL: http://hdl.handle.net/10.1080/07474938.2012.690693 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:32:y:2013:i:8:p:869-891 Template-Type: ReDIF-Article 1.0 Author-Name: Mohitosh Kejriwal Author-X-Name-First: Mohitosh Author-X-Name-Last: Kejriwal Author-Name: Claude Lopez Author-X-Name-First: Claude Author-X-Name-Last: Lopez Title: Unit Roots, Level Shifts, and Trend Breaks in Per Capita Output: A Robust Evaluation Abstract: Determining whether per capita output can be characterized by a stochastic trend is complicated by the fact that infrequent breaks in trend can bias standard unit root tests towards nonrejection of the unit root hypothesis. The bulk of the existing literature has focused on the application of unit root tests allowing for structural breaks in the trend function under the trend stationary alternative but not under the unit root null. These tests, however, provide little information regarding the existence and number of trend breaks. Moreover, these tests suffer from serious power and size distortions due to the asymmetric treatment of breaks under the null and alternative hypotheses. This article estimates the number of breaks in trend employing procedures that are robust to the unit root/stationarity properties of the data. Our analysis of the per capita gross domestic product (GDP) for Organization for Economic Cooperation and Development (OECD) countries thereby permits a robust classification of countries according to the “growth shift,” “level shift,” and “linear trend” hypotheses. In contrast to the extant literature, unit root tests conditional on the presence or absence of breaks do not provide evidence against the unit root hypothesis. Journal: Econometric Reviews Pages: 892-927 Issue: 8 Volume: 32 Year: 2013 Month: 11 X-DOI: 10.1080/07474938.2012.690689 File-URL: http://hdl.handle.net/10.1080/07474938.2012.690689 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:32:y:2013:i:8:p:892-927 Template-Type: ReDIF-Article 1.0 Author-Name: Jia Chen Author-X-Name-First: Jia Author-X-Name-Last: Chen Author-Name: Jiti Gao Author-X-Name-First: Jiti Author-X-Name-Last: Gao Author-Name: Degui Li Author-X-Name-First: Degui Author-X-Name-Last: Li Title: Estimation in Single-Index Panel Data Models with Heterogeneous Link Functions Abstract: In this article, we study semiparametric estimation for a single-index panel data model where the nonlinear link function varies among the individuals. We propose using the refined minimum average variance estimation method to estimate the parameter in the single-index. As the cross-section dimension <italic>N</italic> and the time series dimension <italic>T</italic> tend to infinity simultaneously, we establish asymptotic distributions for the proposed estimator. In addition, we provide a real-data example to illustrate the finite sample behavior of the proposed estimation method. Journal: Econometric Reviews Pages: 928-955 Issue: 8 Volume: 32 Year: 2013 Month: 11 X-DOI: 10.1080/07474938.2012.690687 File-URL: http://hdl.handle.net/10.1080/07474938.2012.690687 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:32:y:2013:i:8:p:928-955 Template-Type: ReDIF-Article 1.0 Author-Name: Esfandiar (Essie) Maasoumi Author-X-Name-First: Esfandiar (Essie) Author-X-Name-Last: Maasoumi Author-Name: Ehsan S. Soofi Author-X-Name-First: Ehsan S. Author-X-Name-Last: Soofi Title: Arnold Zellner: Scientist, Leader, Mentor, and Friend Journal: Econometric Reviews Pages: 1-2 Issue: 1-4 Volume: 33 Year: 2014 Month: 6 X-DOI: 10.1080/07474938.2013.806840 File-URL: http://hdl.handle.net/10.1080/07474938.2013.806840 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:33:y:2014:i:1-4:p:1-2 Template-Type: ReDIF-Article 1.0 Author-Name: Arnold Zellner Author-X-Name-First: Arnold Author-X-Name-Last: Zellner Author-Name: Tomohiro Ando Author-X-Name-First: Tomohiro Author-X-Name-Last: Ando Author-Name: Nalan Baştük Author-X-Name-First: Nalan Author-X-Name-Last: Baştük Author-Name: Lennart Hoogerheide Author-X-Name-First: Lennart Author-X-Name-Last: Hoogerheide Author-Name: Herman K. van Dijk Author-X-Name-First: Herman K. Author-X-Name-Last: van Dijk Title: Bayesian Analysis of Instrumental Variable Models: Acceptance-Rejection within Direct Monte Carlo Abstract: We discuss Bayesian inferential procedures within the family of instrumental variables regression models and focus on two issues: existence conditions for posterior moments of the parameters of interest under a flat prior and the potential of Direct Monte Carlo (DMC) approaches for efficient evaluation of such possibly highly non-elliptical posteriors. We show that, for the general case of m endogenous variables under a flat prior, posterior moments of order r exist for the coefficients reflecting the endogenous regressors' effect on the dependent variable, if the number of instruments is greater than <italic>m +r</italic>, even though there is an issue of local non-identification that causes non-elliptical shapes of the posterior. This stresses the need for efficient Monte Carlo integration methods. We introduce an extension of DMC that incorporates an acceptance-rejection sampling step within DMC. This Acceptance-Rejection within Direct Monte Carlo (ARDMC) method has the attractive property that the generated random drawings are independent, which greatly helps the fast convergence of simulation results, and which facilitates the evaluation of the numerical accuracy. The speed of ARDMC can be easily further improved by making use of parallelized computation using multiple core machines or computer clusters. We note that ARDMC is an analogue to the well-known ";Metropolis-Hastings within Gibbs" sampling in the sense that one 'more difficult' step is used within an 'easier' simulation method. We compare the ARDMC approach with the Gibbs sampler using simulated data and two empirical data sets, involving the settler mortality instrument of Acemoglu et al. (2001) and father's education's instrument used by Hoogerheide et al. (2012a). Even without making use of parallelized computation, an efficiency gain is observed both under strong and weak instruments, where the gain can be enormous in the latter case. Journal: Econometric Reviews Pages: 3-35 Issue: 1-4 Volume: 33 Year: 2014 Month: 6 X-DOI: 10.1080/07474938.2013.807094 File-URL: http://hdl.handle.net/10.1080/07474938.2013.807094 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:33:y:2014:i:1-4:p:3-35 Template-Type: ReDIF-Article 1.0 Author-Name: James J. Heckman Author-X-Name-First: James J. Author-X-Name-Last: Heckman Author-Name: Hedibert F. Lopes Author-X-Name-First: Hedibert F. Author-X-Name-Last: Lopes Author-Name: Rémi Piatek Author-X-Name-First: Rémi Author-X-Name-Last: Piatek Title: Treatment Effects: A Bayesian Perspective Abstract: This paper contributes to the emerging Bayesian literature on treatment effects. It derives treatment parameters in the framework of a potential outcomes model with a treatment choice equation, where the correlation between the unobservable components of the model is driven by a low-dimensional vector of latent factors. The analyst is assumed to have access to a set of measurements generated by the latent factors. This approach has attractive features from both theoretical and practical points of view. Not only does it address the fundamental identification problem arising from the inability to observe the same person in both the treated and untreated states, but it also turns out to be straightforward to implement. Formulae are provided to compute mean treatment effects as well as their distributional versions. A Monte Carlo simulation study is carried out to illustrate how the methodology can easily be applied. Journal: Econometric Reviews Pages: 36-67 Issue: 1-4 Volume: 33 Year: 2014 Month: 6 X-DOI: 10.1080/07474938.2013.807103 File-URL: http://hdl.handle.net/10.1080/07474938.2013.807103 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:33:y:2014:i:1-4:p:36-67 Template-Type: ReDIF-Article 1.0 Author-Name: Tomohiro Ando Author-X-Name-First: Tomohiro Author-X-Name-Last: Ando Author-Name: Ruey S. Tsay Author-X-Name-First: Ruey S. Author-X-Name-Last: Tsay Title: A Predictive Approach for Selection of Diffusion Index Models Abstract: In this article, we propose a predictive mean squared error criterion for selecting diffusion index models, which are useful in forecasting when many predictors are available. A special feature of the proposed criterion is that it takes into account the uncertainty in estimated common factors. The new criterion is based on estimating the predictive mean squared error in forecasting with correction for asymptotic bias. The resulting estimate of bias-corrected forecast-error is shown to be <inline-formula> <inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="lecr_a_807105_o_ilm0001.gif"/> </inline-formula> consistent. The proposed criterion is a natural extension of the traditional Akaike information criterion (AIC), but it does not require the distributional assumptions for the likelihood. Results of real data analysis and Monte Carlo simulations demonstrate that the proposed criterion works well in comparison with the commonly used AIC and Bayesian information criteria. Journal: Econometric Reviews Pages: 68-99 Issue: 1-4 Volume: 33 Year: 2014 Month: 6 X-DOI: 10.1080/07474938.2013.807105 File-URL: http://hdl.handle.net/10.1080/07474938.2013.807105 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:33:y:2014:i:1-4:p:68-99 Template-Type: ReDIF-Article 1.0 Author-Name: Hedibert F. Lopes Author-X-Name-First: Hedibert F. Author-X-Name-Last: Lopes Author-Name: Nicholas G. Polson Author-X-Name-First: Nicholas G. Author-X-Name-Last: Polson Title: Bayesian Instrumental Variables: Priors and Likelihoods Abstract: Instrumental variable (IV) regression provides a number of statistical challenges due to the shape of the likelihood. We review the main Bayesian literature on instrumental variables and highlight these pathologies. We discuss Jeffreys priors, the connection to the errors-in-the-variables problems and more general error distributions. We propose, as an alternative to the inverted Wishart prior, a new Cholesky-based prior for the covariance matrix of the errors in IV regressions. We argue that this prior is more flexible and more robust thanthe inverted Wishart prior since it is not based on only one tightness parameter and therefore can be more informative about certain components of the covariance matrix and less informative about others. We show how prior-posterior inference can be formulated in a Gibbs sampler and compare its performance in the weak instruments case for synthetic as well as two illustrations based on well-known real data. Journal: Econometric Reviews Pages: 100-121 Issue: 1-4 Volume: 33 Year: 2014 Month: 6 X-DOI: 10.1080/07474938.2013.807146 File-URL: http://hdl.handle.net/10.1080/07474938.2013.807146 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:33:y:2014:i:1-4:p:100-121 Template-Type: ReDIF-Article 1.0 Author-Name: Alex Lenkoski Author-X-Name-First: Alex Author-X-Name-Last: Lenkoski Author-Name: Theo S. Eicher Author-X-Name-First: Theo S. Author-X-Name-Last: Eicher Author-Name: Adrian E. Raftery Author-X-Name-First: Adrian E. Author-X-Name-Last: Raftery Title: Two-Stage Bayesian Model Averaging in Endogenous Variable Models Abstract: Economic modeling in the presence of endogeneity is subject to model uncertainty at both the instrument and covariate level. We propose a Two-Stage Bayesian Model Averaging (2SBMA) methodology that extends the Two-Stage Least Squares (2SLS) estimator. By constructing a Two-Stage Unit Information Prior in the endogenous variable model, we are able to efficiently combine established methods for addressing model uncertainty in regression models with the classic technique of 2SLS. To assess the validity of instruments in the 2SBMA context, we develop Bayesian tests of the identification restriction that are based on model averaged posterior predictive p-values. A simulation study showed that 2SBMA has the ability to recover structure in both the instrument and covariate set, and substantially improves the sharpness of resulting coefficient estimates in comparison to 2SLS using the full specification in an automatic fashion. Due to the increased parsimony of the 2SBMA estimate, the Bayesian Sargan test had a power of 50% in detecting a violation of the exogeneity assumption, while the method based on 2SLS using the full specification had negligible power. We apply our approach to the problem of development accounting, and find support not only for institutions, but also for geography and integration as development determinants, once both model uncertainty and endogeneity have been jointly addressed. Journal: Econometric Reviews Pages: 122-151 Issue: 1-4 Volume: 33 Year: 2014 Month: 6 X-DOI: 10.1080/07474938.2013.807150 File-URL: http://hdl.handle.net/10.1080/07474938.2013.807150 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:33:y:2014:i:1-4:p:122-151 Template-Type: ReDIF-Article 1.0 Author-Name: Siddhartha Chib Author-X-Name-First: Siddhartha Author-X-Name-Last: Chib Author-Name: Srikanth Ramamurthy Author-X-Name-First: Srikanth Author-X-Name-Last: Ramamurthy Title: DSGE Models with Student-<italic>t</italic> Errors Abstract: This paper deals with Dynamic Stochastic General Equilibrium (DSGE) models under a multivariate student-<italic>t</italic> distribution for the structural shocks. Based on the solution algorithm of Klein (2000) and the gamma-normal representation of the <italic>t</italic>-distribution, the TaRB-MH algorithm of Chib and Ramamurthy (2010) is used to estimate the model. A technique for estimating the marginal likelihood of the DSGE student-<italic>t</italic> model is also provided. The methodologies are illustrated first with simulated data and then with the DSGE model of Ireland (2004) where the results support the <italic>t</italic>-error model in relation to the Gaussian model. Journal: Econometric Reviews Pages: 152-171 Issue: 1-4 Volume: 33 Year: 2014 Month: 6 X-DOI: 10.1080/07474938.2013.807152 File-URL: http://hdl.handle.net/10.1080/07474938.2013.807152 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:33:y:2014:i:1-4:p:152-171 Template-Type: ReDIF-Article 1.0 Author-Name: Brendan Kline Author-X-Name-First: Brendan Author-X-Name-Last: Kline Author-Name: Justin L. Tobias Author-X-Name-First: Justin L. Author-X-Name-Last: Tobias Title: Explaining Trends in Body Mass Index Using Demographic Counterfactuals Abstract: The United States is experiencing a major public health problem relating to increasing levels of excess body fat. This paper is about the relationship in the United States between trends in the distribution of body mass index (BMI), including trends in overweight and obesity, and demographic change. We provide estimates of the counterfactual distribution of BMI that would have been observed in 2003--2008 had demographics remained fixed at 1980 values, roughly the beginning of the period of increasing overweight and obesity. We find that changes in demographics are partly responsible for the changes in the population distribution of BMI and are capable of explaining about 8.6% of the increase in the combined rate of overweight and obesity among women and about 7.2% of the increase among men. We also use demographic projections to predict a BMI distribution and corresponding rates of overweight and obesity for 2050. Journal: Econometric Reviews Pages: 172-196 Issue: 1-4 Volume: 33 Year: 2014 Month: 6 X-DOI: 10.1080/07474938.2013.807155 File-URL: http://hdl.handle.net/10.1080/07474938.2013.807155 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:33:y:2014:i:1-4:p:172-196 Template-Type: ReDIF-Article 1.0 Author-Name: James Berger Author-X-Name-First: James Author-X-Name-Last: Berger Author-Name: M. J. Bayarri Author-X-Name-First: M. J. Author-X-Name-Last: Bayarri Author-Name: L. R. Pericchi Author-X-Name-First: L. R. Author-X-Name-Last: Pericchi Title: The Effective Sample Size Abstract: Model selection procedures often depend explicitly on the sample size n of the experiment. One example is the Bayesian information criterion (BIC) criterion and another is the use of Zellner--Siow priors in Bayesian model selection. Sample size is well-defined if one has i.i.d real observations, but is not well-defined for vector observations or in non-i.i.d. settings; extensions of critera such as BIC to such settings thus requires a definition of effective sample size that applies also in such cases. A definition of effective sample size that applies to fairly general linear models is proposed and illustrated in a variety of situations. The definition is also used to propose a suitable 'scale' for default proper priors for Bayesian model selection. Journal: Econometric Reviews Pages: 197-217 Issue: 1-4 Volume: 33 Year: 2014 Month: 6 X-DOI: 10.1080/07474938.2013.807157 File-URL: http://hdl.handle.net/10.1080/07474938.2013.807157 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:33:y:2014:i:1-4:p:197-217 Template-Type: ReDIF-Article 1.0 Author-Name: Xiao-Li Meng Author-X-Name-First: Xiao-Li Author-X-Name-Last: Meng Author-Name: Xianchao Xie Author-X-Name-First: Xianchao Author-X-Name-Last: Xie Title: I Got More Data, My Model is More Refined, but My Estimator is Getting Worse! Am I Just Dumb? Abstract: Possibly, but more likely you are merely a victim of conventional wisdom. More data or better models by no means guarantee better estimators (e.g., with a smaller mean squared error), when you are not following probabilistically principled methods such as MLE (for large samples) or Bayesian approaches. Estimating equations are particularly vulnerable in this regard, almost a necessary price for their robustness. These points will be demonstrated via common tasks of estimating regression parameters and correlations, under simple models such as bivariate normal and ARCH(1). Some general strategies for detecting and avoiding such pitfalls are suggested, including checking for self-efficiency (Meng, 1994; <italic>Statistical Science</italic>) and adopting a guiding working model. Using the example of estimating the autocorrelation ρ under a stationary AR(1) model, we also demonstrate the interaction between model assumptions and observation structures in seeking additional information, as the sampling interval <italic>s</italic> increases. Furthermore, for a given sample size, the optimal <italic>s</italic> for minimizing the asymptotic variance of <inline-formula> <inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="lecr_a_808567_o_ilm0001.gif"/> </inline-formula> is s = 1 if and only if ρ-super-2 ≤ 1/3; beyond that region the optimal <italic>s</italic> increases at the rate of log -super- - 1(ρ-super- - 2) as ρ approaches a unit root, as does the gain in efficiency relative to using s = 1. A practical implication of this result is that the so-called "non-informative" Jeffreys prior can be far from non-informative even for stationary time series models, because here it converges rapidly to a point mass at a unit root as <italic>s</italic> increases. Our overall emphasis is that intuition and conventional wisdom need to be examined via critical thinking and theoretical verification before they can be trusted fully. Journal: Econometric Reviews Pages: 218-250 Issue: 1-4 Volume: 33 Year: 2014 Month: 6 X-DOI: 10.1080/07474938.2013.808567 File-URL: http://hdl.handle.net/10.1080/07474938.2013.808567 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:33:y:2014:i:1-4:p:218-250 Template-Type: ReDIF-Article 1.0 Author-Name: Edward I. George Author-X-Name-First: Edward I. Author-X-Name-Last: George Author-Name: Yuzo Maruyama Author-X-Name-First: Yuzo Author-X-Name-Last: Maruyama Title: Posterior Odds with a Generalized Hyper-<italic>g</italic>-Prior Abstract: Averaged orthogonal rotations of Zellner's g-prior yield general, interpretable, closed form Bayes factors for the normal linear model variable selection problem. Coupled with a model space prior that balances the weight between the identifiable and the unidentifiable models, limiting forms for the posterior odds ratios are seen to yield new expressions for high dimensional model choice. Journal: Econometric Reviews Pages: 251-269 Issue: 1-4 Volume: 33 Year: 2014 Month: 6 X-DOI: 10.1080/07474938.2013.807181 File-URL: http://hdl.handle.net/10.1080/07474938.2013.807181 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:33:y:2014:i:1-4:p:251-269 Template-Type: ReDIF-Article 1.0 Author-Name: John Geweke Author-X-Name-First: John Author-X-Name-Last: Geweke Author-Name: Gianni Amisano Author-X-Name-First: Gianni Author-X-Name-Last: Amisano Title: Analysis of Variance for Bayesian Inference Abstract: This paper develops a multiway analysis of variance for non-Gaussian multivariate distributions and provides a practical simulation algorithm to estimate the corresponding components of variance. It specifically addresses variance in Bayesian predictive distributions, showing that it may be decomposed into the sum of extrinsic variance, arising from posterior uncertainty about parameters, and intrinsic variance, which would exist even if parameters were known. Depending on the application at hand, further decomposition of extrinsic or intrinsic variance (or both) may be useful. The paper shows how to produce simulation-consistent estimates of all of these components, and the method demands little additional effort or computing time beyond that already invested in the posterior simulator. It illustrates the methods using a dynamic stochastic general equilibrium model of the US economy, both before and during the global financial crisis. Journal: Econometric Reviews Pages: 270-288 Issue: 1-4 Volume: 33 Year: 2014 Month: 6 X-DOI: 10.1080/07474938.2013.807182 File-URL: http://hdl.handle.net/10.1080/07474938.2013.807182 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:33:y:2014:i:1-4:p:270-288 Template-Type: ReDIF-Article 1.0 Author-Name: Fabrizio Ruggeri Author-X-Name-First: Fabrizio Author-X-Name-Last: Ruggeri Title: On Some Optimal Bayesian Nonparametric Rules for Estimating Distribution Functions Abstract: In this paper, we present a novel approach to estimating distribution functions, which combines ideas from Bayesian nonparametric inference, decision theory and robustness. Given a sample from a Dirichlet process on the space (𝒳, A), with parameter <roman>η</roman> in a class of measures, the sampling distribution function is estimated according to some optimality criteria (mainly minimax and regret), when a quadratic loss function is assumed. Estimates are then compared in two examples: one with simulated data and one with gas escapes data in a city network. Journal: Econometric Reviews Pages: 289-304 Issue: 1-4 Volume: 33 Year: 2014 Month: 6 X-DOI: 10.1080/07474938.2013.807183 File-URL: http://hdl.handle.net/10.1080/07474938.2013.807183 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:33:y:2014:i:1-4:p:289-304 Template-Type: ReDIF-Article 1.0 Author-Name: Minxian Yang Author-X-Name-First: Minxian Author-X-Name-Last: Yang Title: Normality of Posterior Distribution Under Misspecification and Nonsmoothness, and Bayes Factor for Davies' Problem Abstract: We examine the large sample properties of Bayes procedures in a general framework, where data may be dependent and models may be misspecified and nonsmooth. The posterior distribution of parameters is shown to be asymptotically normal, centered at the quasi maximum likelihood estimator, under mild conditions. In this framework, the Bayes factor for the test problem of Davies (1997, 1987), where a parameter is unidentified under the null hypothesis, is analyzed. The probability that the Bayes factor leads to a correct conclusion about the hypotheses in Davies’ problem is shown to approach to one. Journal: Econometric Reviews Pages: 305-336 Issue: 1-4 Volume: 33 Year: 2014 Month: 6 X-DOI: 10.1080/07474938.2013.807185 File-URL: http://hdl.handle.net/10.1080/07474938.2013.807185 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:33:y:2014:i:1-4:p:305-336 Template-Type: ReDIF-Article 1.0 Author-Name: Bertrand Clarke Author-X-Name-First: Bertrand Author-X-Name-Last: Clarke Author-Name: Jennifer Clarke Author-X-Name-First: Jennifer Author-X-Name-Last: Clarke Author-Name: Chi Wai Yu Author-X-Name-First: Chi Wai Author-X-Name-Last: Yu Title: Statistical Problem Classes and Their Links to Information Theory Abstract: We begin by recalling the tripartite division of statistical problems into three classes, M-closed, M-complete, and M-open and then reviewing the key ideas of introductory Shannon theory. Focusing on the related but distinct goals of model selection and prediction, we argue that different techniques for these two goals are appropriate for the three different problem classes. For M-closed problems we give relative entropy justification that the Bayes information criterion (BIC) is appropriate for model selection and that the Bayes model average is information optimal for prediction. For M-complete problems, we discuss the principle of maximum entropy and a way to use the rate distortion function to bypass the inaccessibility of the true distribution. For prediction in the M-complete class, there is little work done on information based model averaging so we discuss the Akaike information criterion (AIC) and its properties and variants. For the M-open class, we argue that essentially only predictive criteria are suitable. Thus, as an analog to model selection, we present the key ideas of prediction along a string under a codelength criterion and propose a general form of this criterion. Since little work appears to have been done on information methods for general prediction in the M-open class of problems, we mention the field of information theoretic learning in certain general function spaces. Journal: Econometric Reviews Pages: 337-371 Issue: 1-4 Volume: 33 Year: 2014 Month: 6 X-DOI: 10.1080/07474938.2013.807190 File-URL: http://hdl.handle.net/10.1080/07474938.2013.807190 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:33:y:2014:i:1-4:p:337-371 Template-Type: ReDIF-Article 1.0 Author-Name: Joseph B. Kadane Author-X-Name-First: Joseph B. Author-X-Name-Last: Kadane Author-Name: Jiashun Jin Author-X-Name-First: Jiashun Author-X-Name-Last: Jin Title: Uniform Distributions on the Integers: A connection to the Bernouilli Random Walk Abstract: Associate to each subset of the integers its almost sure limiting relative frequency under the Bernouilli random walk, if it has one. The resulting probability space is purely finitely additive, and uniform in the sense of residue classes and shift-invariance. However, it is not uniform in the sense of limiting relative frequency. Journal: Econometric Reviews Pages: 372-378 Issue: 1-4 Volume: 33 Year: 2014 Month: 6 X-DOI: 10.1080/07474938.2013.807193 File-URL: http://hdl.handle.net/10.1080/07474938.2013.807193 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:33:y:2014:i:1-4:p:372-378 Template-Type: ReDIF-Article 1.0 Author-Name: Nozer D. Singpurwalla Author-X-Name-First: Nozer D. Author-X-Name-Last: Singpurwalla Title: Adaptive Percolation Using Subjective Likelihoods Abstract: A phenomenon that I call "adaptive percolation" commonly arises in biology, business, economics, defense, finance, manufacturing, and the social sciences. Here one wishes to select a handful of entities from a large pool of entities via a process of screening through a hierarchy of sieves. The process is not unlike the percolation of a liquid through a porous medium. The probability model developed here is based on a nested and adaptive Bayesian approach that results in the product of beta-binomial distributions with common parameters. The common parameters happen to be the observed data. I call this the <bold> <italic>percolated beta-binomial distribution</italic> </bold>. The model turns out to be a slight generalization of the probabilistic model used in percolation theory. The generalization is a consequence of using a subjectively specified likelihood function to construct a probability model. The notion of using likelihoods for constructing probability models is not a part of the conventional toolkit of applied probabilists. To the best of my knowledge, a use of the product of beta-binomial distributions as a probability model for Bernoulli trials appears to be new. The development of the material of this article is illustrated via data from the 2009 astronaut selection program, which motivated this work. Journal: Econometric Reviews Pages: 379-394 Issue: 1-4 Volume: 33 Year: 2014 Month: 6 X-DOI: 10.1080/07474938.2013.807195 File-URL: http://hdl.handle.net/10.1080/07474938.2013.807195 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:33:y:2014:i:1-4:p:379-394 Template-Type: ReDIF-Article 1.0 Author-Name: Nader Ebrahimi Author-X-Name-First: Nader Author-X-Name-Last: Ebrahimi Author-Name: Nima Y. Jalali Author-X-Name-First: Nima Y. Author-X-Name-Last: Jalali Author-Name: Ehsan S. Soofi Author-X-Name-First: Ehsan S. Author-X-Name-Last: Soofi Author-Name: Refik Soyer Author-X-Name-First: Refik Author-X-Name-Last: Soyer Title: Importance of Components for a System Abstract: Which component is most important for a system's survival? We answer this question by ranking the information relationship between a system and its components. The mutual information (M) measures dependence between the operational states of the system and a component for a mission time as well as between their life lengths. This measure ranks each component in terms of its expected utility for predicting the system's survival. We explore some relationships between the ordering of importance of components by M and by Zellner's Maximal Data Information (MDIP) criterion. For many systems the bivariate distribution of the component and system lifetimes does not have a density with respect to the two-dimensional Lebesgue measure. For these systems, <italic>M</italic> is not defined, so we use a modification of a mutual information index to cover such situations. Our results for ordering dependence are general in terms of binary structures, sum of random variables, and order statistics. Journal: Econometric Reviews Pages: 395-420 Issue: 1-4 Volume: 33 Year: 2014 Month: 6 X-DOI: 10.1080/07474938.2013.807652 File-URL: http://hdl.handle.net/10.1080/07474938.2013.807652 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:33:y:2014:i:1-4:p:395-420 Template-Type: ReDIF-Article 1.0 Author-Name: Peter Rossi Author-X-Name-First: Peter Author-X-Name-Last: Rossi Title: All Roads Lead to Arnold Journal: Econometric Reviews Pages: 421-423 Issue: 1-4 Volume: 33 Year: 2014 Month: 6 X-DOI: 10.1080/07474938.2013.807654 File-URL: http://hdl.handle.net/10.1080/07474938.2013.807654 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:33:y:2014:i:1-4:p:421-423 Template-Type: ReDIF-Article 1.0 Author-Name: Ehsan S. Soofi Author-X-Name-First: Ehsan S. Author-X-Name-Last: Soofi Title: Memorial Statements by Anderson, Judge, Press, Aigner, Allenby, and Palm Abstract: This collection presents memorial statements by Theodore W. Anderson, George G. Judge, S. James Press, Dennis J. Aigner, Greg M. Allenby, and Franz C. Palm. Journal: Econometric Reviews Pages: 424-427 Issue: 1-4 Volume: 33 Year: 2014 Month: 6 X-DOI: 10.1080/07474938.2013.807657 File-URL: http://hdl.handle.net/10.1080/07474938.2013.807657 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:33:y:2014:i:1-4:p:424-427 Template-Type: ReDIF-Article 1.0 Author-Name: Karim M. Abadir Author-X-Name-First: Karim M. Author-X-Name-Last: Abadir Author-Name: Esfandiar Maasoumi Author-X-Name-First: Esfandiar Author-X-Name-Last: Maasoumi Title: Overview Journal: Econometric Reviews Pages: 429-430 Issue: 5-6 Volume: 33 Year: 2014 Month: 8 X-DOI: 10.1080/07474938.2013.824766 File-URL: http://hdl.handle.net/10.1080/07474938.2013.824766 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:33:y:2014:i:5-6:p:429-430 Template-Type: ReDIF-Article 1.0 Author-Name: Chris D. Orme Author-X-Name-First: Chris D. Author-X-Name-Last: Orme Author-Name: Takashi Yamagata Author-X-Name-First: Takashi Author-X-Name-Last: Yamagata Title: A Heteroskedasticity-Robust <italic>F</italic>-Test Statistic for Individual Effects Abstract: We derive the asymptotic distribution of the standard F-test statistic for fixed effects, in static linear panel data models, under both non-normality and heteroskedasticity of the error terms, when the cross-section dimension is large but the time series dimension is fixed. It is shown that a simple linear transformation of the F-test statistic yields asymptotically valid inferences and under local fixed (or correlated) individual effects, this heteroskedasticity-robust F-test enjoys higher asymptotic power than a suitably robustified Random Effects test. Wild bootstrap versions of these tests are considered which, in a Monte Carlo study, provide more reliable inference in finite samples. Journal: Econometric Reviews Pages: 431-471 Issue: 5-6 Volume: 33 Year: 2014 Month: 8 X-DOI: 10.1080/07474938.2013.824792 File-URL: http://hdl.handle.net/10.1080/07474938.2013.824792 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:33:y:2014:i:5-6:p:431-471 Template-Type: ReDIF-Article 1.0 Author-Name: Jerry Hausman Author-X-Name-First: Jerry Author-X-Name-Last: Hausman Author-Name: Tiemen Woutersen Author-X-Name-First: Tiemen Author-X-Name-Last: Woutersen Title: Estimating the Derivative Function and Counterfactuals in Duration Models with Heterogeneity Abstract: This paper presents a new estimator for counterfactuals in duration models. The counterfactual in a duration model is the length of the spell in case the regressor would have been different. We introduce the structural duration function, which gives these counterfactuals. The advantage of focusing on counterfactuals is that one does not need to identify the mixed proportional hazard model. In particular, we present examples in which the mixed proportional hazard model is unidentified or has a singular information matrix but our estimator for counterfactuals still converges at rate <italic>N</italic> -super-1/2, where <italic>N</italic> is the number of observations. We apply the structural duration function to simulate important policy effects, including a change in welfare benefits. Journal: Econometric Reviews Pages: 472-496 Issue: 5-6 Volume: 33 Year: 2014 Month: 8 X-DOI: 10.1080/07474938.2013.825120 File-URL: http://hdl.handle.net/10.1080/07474938.2013.825120 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:33:y:2014:i:5-6:p:472-496 Template-Type: ReDIF-Article 1.0 Author-Name: Christine Amsler Author-X-Name-First: Christine Author-X-Name-Last: Amsler Author-Name: Artem Prokhorov Author-X-Name-First: Artem Author-X-Name-Last: Prokhorov Author-Name: Peter Schmidt Author-X-Name-First: Peter Author-X-Name-Last: Schmidt Title: Using Copulas to Model Time Dependence in Stochastic Frontier Models Abstract: We consider stochastic frontier models in a panel data setting where there is dependence over time. Current methods of modeling time dependence in this setting are either unduly restrictive or computationally infeasible. Some impose restrictive assumptions on the nature of dependence such as the "scaling" property. Others involve <italic>T</italic>-dimensional integration, where <italic>T</italic> is the number of cross-sections, which may be large. Moreover, no known multivariate distribution has the property of having commonly used, convenient marginals such as normal/half-normal. We show how to use copulas to resolve these issues. The range of dependence we allow for is unrestricted and the computational task involved is easy compared to the alternatives. Also, the resulting estimators are more efficient than those that assume independence over time. We propose two alternative specifications. One applies a copula function to the distribution of the composed error term. This permits the use of maximum likelyhood estimate (MLE) and generalized method moments (GMM). The other applies a copula to the distribution of the one-sided error term. This allows for a simulated MLE and improved estimation of inefficiencies. An application demonstrates the usefulness of our approach. Journal: Econometric Reviews Pages: 497-522 Issue: 5-6 Volume: 33 Year: 2014 Month: 8 X-DOI: 10.1080/07474938.2013.825126 File-URL: http://hdl.handle.net/10.1080/07474938.2013.825126 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:33:y:2014:i:5-6:p:497-522 Template-Type: ReDIF-Article 1.0 Author-Name: Oliver Linton Author-X-Name-First: Oliver Author-X-Name-Last: Linton Author-Name: Pedro Gozalo Author-X-Name-First: Pedro Author-X-Name-Last: Gozalo Title: Testing Conditional Independence Restrictions Abstract: We propose a nonparametric test of the hypothesis of conditional independence between variables of interest based on a generalization of the empirical distribution function. This hypothesis is of interest both for model specification purposes, parametric and semiparametric, and for nonmodel-based testing of economic hypotheses. We allow for both discrete variables and estimated parameters. The asymptotic null distribution of the test statistic is a functional of a Gaussian process. A bootstrap procedure is proposed for calculating the critical values. Our test has power against alternatives at distance <italic>n</italic> -super-&minus1/2 from the null; this result holding independently of dimension. Monte Carlo simulations provide evidence on size and power. Journal: Econometric Reviews Pages: 523-552 Issue: 5-6 Volume: 33 Year: 2014 Month: 8 X-DOI: 10.1080/07474938.2013.825135 File-URL: http://hdl.handle.net/10.1080/07474938.2013.825135 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:33:y:2014:i:5-6:p:523-552 Template-Type: ReDIF-Article 1.0 Author-Name: Jennifer L. Castle Author-X-Name-First: Jennifer L. Author-X-Name-Last: Castle Author-Name: Jurgen A. Doornik Author-X-Name-First: Jurgen A. Author-X-Name-Last: Doornik Author-Name: David F. Hendry Author-X-Name-First: David F. Author-X-Name-Last: Hendry Author-Name: Ragnar Nymoen Author-X-Name-First: Ragnar Author-X-Name-Last: Nymoen Title: Misspecification Testing: Non-Invariance of Expectations Models of Inflation Abstract: Many economic models (such as the new-Keynesian Phillips curve, NKPC) include expected future values, often estimated after replacing the expected value by the actual future outcome, using Instrumental Variables (IV) or Generalized Method of Moments (GMM). Although crises, breaks, and regime shifts are relatively common, the underlying theory does not allow for their occurrence. We show the consequences for such models of breaks in data processes, and propose an impulse-indicator saturation test of such specifications, applied to USA and Euro-area NKPCs. Journal: Econometric Reviews Pages: 553-574 Issue: 5-6 Volume: 33 Year: 2014 Month: 8 X-DOI: 10.1080/07474938.2013.825137 File-URL: http://hdl.handle.net/10.1080/07474938.2013.825137 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:33:y:2014:i:5-6:p:553-574 Template-Type: ReDIF-Article 1.0 Author-Name: Sainan Jin Author-X-Name-First: Sainan Author-X-Name-Last: Jin Author-Name: Liangjun Su Author-X-Name-First: Liangjun Author-X-Name-Last: Su Author-Name: Aman Ullah Author-X-Name-First: Aman Author-X-Name-Last: Ullah Title: Robustify Financial Time Series Forecasting with Bagging Abstract: In this paper we propose a revised version of (bagging) <bold>b</bold>ootstrap <bold>aggr</bold>egat<bold>ing</bold> as a forecast combination method for the out-of-sample forecasts in time series models. The revised version explicitly takes into account the dependence in time series data and can be used to justify the validity of bagging in the reduction of mean squared forecast error when compared with the unbagged forecasts. Monte Carlo simulations show that the new method works quite well and outperforms the traditional one-step-ahead linear forecast as well as the nonparametric forecast in general, especially when the in-sample estimation period is small. We also find that the bagging forecasts based on misspecified linear models may work as effectively as those based on nonparametric models, suggesting the robustification property of bagging method in terms of out-of-sample forecasts. We then reexamine forecasting powers of predictive variables suggested in the literature to forecast the excess returns or equity premium. We find that, consistent with Goyal and Welch (2008), the historical average excess stock return forecasts may beat other predictor variables in the literature when we apply traditional one-step linear forecast and the nonparametric forecasting methods. However, when using the bagging method or its revised version, which help to improve the mean squared forecast error for "unstable" predictors, the predictive variables have a better forecasting power than the historical mean. Journal: Econometric Reviews Pages: 575-605 Issue: 5-6 Volume: 33 Year: 2014 Month: 8 X-DOI: 10.1080/07474938.2013.825142 File-URL: http://hdl.handle.net/10.1080/07474938.2013.825142 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:33:y:2014:i:5-6:p:575-605 Template-Type: ReDIF-Article 1.0 Author-Name: Giuseppe Cavaliere Author-X-Name-First: Giuseppe Author-X-Name-Last: Cavaliere Author-Name: Anders Rahbek Author-X-Name-First: Anders Author-X-Name-Last: Rahbek Author-Name: A. M. Robert Taylor Author-X-Name-First: A. M. Author-X-Name-Last: Robert Taylor Title: Bootstrap Determination of the Co-Integration Rank in Heteroskedastic VAR Models Abstract: In a recent paper Cavaliere et al. (2012) develop bootstrap implementations of the (pseudo-) likelihood ratio (PLR) co-integration rank test and associated sequential rank determination procedure of Johansen (1996). The bootstrap samples are constructed using the restricted parameter estimates of the underlying vector autoregressive (VAR) model which obtain under the reduced rank null hypothesis. They propose methods based on an independent and individual distributed (i.i.d.) bootstrap resampling scheme and establish the validity of their proposed bootstrap procedures in the context of a co-integrated VAR model with i.i.d. innovations. In this paper we investigate the properties of their bootstrap procedures, together with analogous procedures based on a wild bootstrap resampling scheme, when time-varying behavior is present in either the conditional or unconditional variance of the innovations. We show that the bootstrap PLR tests are asymptotically correctly sized and, moreover, that the probability that the associated bootstrap sequential procedures select a rank smaller than the true rank converges to zero. This result is shown to hold for both the i.i.d. and wild bootstrap variants under conditional heteroskedasticity but only for the latter under unconditional heteroskedasticity. Monte Carlo evidence is reported which suggests that the bootstrap approach of Cavaliere et al. (2012) significantly improves upon the finite sample performance of corresponding procedures based on either the asymptotic PLR test or an alternative bootstrap method (where the short run dynamics in the VAR model are estimated unrestrictedly) for a variety of conditionally and unconditionally heteroskedastic innovation processes. Journal: Econometric Reviews Pages: 606-650 Issue: 5-6 Volume: 33 Year: 2014 Month: 8 X-DOI: 10.1080/07474938.2013.825175 File-URL: http://hdl.handle.net/10.1080/07474938.2013.825175 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:33:y:2014:i:5-6:p:606-650 Template-Type: ReDIF-Article 1.0 Author-Name: Russell Davidson Author-X-Name-First: Russell Author-X-Name-Last: Davidson Author-Name: James G. MacKinnon Author-X-Name-First: James G. Author-X-Name-Last: MacKinnon Title: Bootstrap Confidence Sets with Weak Instruments Abstract: We study several methods of constructing confidence sets for the coefficient of the single right-hand-side endogenous variable in a linear equation with weak instruments. Two of these are based on conditional likelihood ratio (CLR) tests, and the others are based on inverting <italic>t</italic> statistics or the bootstrap <italic>P</italic> values associated with them. We propose a new method for constructing bootstrap confidence sets based on <italic>t</italic> statistics. In large samples, the procedures that generally work best are CLR confidence sets using asymptotic critical values and bootstrap confidence sets based on limited-information maximum likelihood (LIML) estimates. Journal: Econometric Reviews Pages: 651-675 Issue: 5-6 Volume: 33 Year: 2014 Month: 8 X-DOI: 10.1080/07474938.2013.825177 File-URL: http://hdl.handle.net/10.1080/07474938.2013.825177 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:33:y:2014:i:5-6:p:651-675 Template-Type: ReDIF-Article 1.0 Author-Name: Ioannis Kasparis Author-X-Name-First: Ioannis Author-X-Name-Last: Kasparis Author-Name: Peter C. B. Phillips Author-X-Name-First: Peter C. B. Author-X-Name-Last: Phillips Author-Name: Tassos Magdalinos Author-X-Name-First: Tassos Author-X-Name-Last: Magdalinos Title: Nonlinearity Induced Weak Instrumentation Abstract: In regressions involving integrable functions we examine the limit properties of instrumental variable (IV) estimators that utilise integrable transformations of lagged regressors as instruments. The regressors can be either <italic>I</italic>(0) or nearly integrated (<italic>NI</italic>) processes. We show that this kind of nonlinearity in the regression function can significantly affect the relevance of the instruments. In particular, such instruments become weak when the signal of the regressor is strong, as it is in the <italic>NI</italic> case. Instruments based on integrable functions of lagged <italic>NI</italic> regressors display long range dependence and so remain relevant even at long lags, continuing to contribute to variance reduction in IV estimation. However, simulations show that ordinary least square (OLS) is generally superior to IV estimation in terms of mean squared error (MSE), even in the presence of endogeneity. Estimation precision is also reduced when the regressor is nonstationary. Journal: Econometric Reviews Pages: 676-712 Issue: 5-6 Volume: 33 Year: 2014 Month: 8 X-DOI: 10.1080/07474938.2013.825181 File-URL: http://hdl.handle.net/10.1080/07474938.2013.825181 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:33:y:2014:i:5-6:p:676-712 Template-Type: ReDIF-Article 1.0 Author-Name: Marcelo C. Medeiros Author-X-Name-First: Marcelo C. Author-X-Name-Last: Medeiros Author-Name: Eduardo Mendes Author-X-Name-First: Eduardo Author-X-Name-Last: Mendes Author-Name: Les Oxley Author-X-Name-First: Les Author-X-Name-Last: Oxley Title: A Note on Nonlinear Cointegration, Misspecification, and Bimodality Abstract: We derive the asymptotic distribution of the ordinary least squares estimator in a regression with cointegrated variables under misspecification and/or nonlinearity in the regressors. We show that, under some circumstances, the order of convergence of the estimator changes and the asymptotic distribution is non-standard. The <italic>t</italic>-statistic might also diverge. A simple case arises when the intercept is erroneously omitted from the estimated model or in nonlinear-in-variables models with endogenous regressors. In the latter case, a solution is to use an instrumental variable estimator. The core results in this paper also generalise to more complicated nonlinear models involving integrated time series. Journal: Econometric Reviews Pages: 713-731 Issue: 7 Volume: 33 Year: 2014 Month: 10 X-DOI: 10.1080/07474938.2012.690676 File-URL: http://hdl.handle.net/10.1080/07474938.2012.690676 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:33:y:2014:i:7:p:713-731 Template-Type: ReDIF-Article 1.0 Author-Name: Randall A. Lewis Author-X-Name-First: Randall A. Author-X-Name-Last: Lewis Author-Name: James B. McDonald Author-X-Name-First: James B. Author-X-Name-Last: McDonald Title: Partially Adaptive Estimation of the Censored Regression Model Abstract: Data censoring causes ordinary least squares estimates of linear models to be biased and inconsistent. Tobit, semiparametric, and partially adaptive estimators have been considered as possible solutions. This paper proposes several new partially adaptive estimators that cover a wide range of distributional characteristics. A simulation study is used to investigate the estimators' relative efficiency in these settings. The partially adaptive censored regression estimators have little efficiency loss for censored normal errors and may outperform Tobit and semiparametric estimators considered for non-normal distributions. An empirical example of out-of-pocket expenditures for a health insurance plan provides an example, which supports these results. Journal: Econometric Reviews Pages: 732-750 Issue: 7 Volume: 33 Year: 2014 Month: 10 X-DOI: 10.1080/07474938.2012.690691 File-URL: http://hdl.handle.net/10.1080/07474938.2012.690691 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:33:y:2014:i:7:p:732-750 Template-Type: ReDIF-Article 1.0 Author-Name: Wanling Huang Author-X-Name-First: Wanling Author-X-Name-Last: Huang Author-Name: Artem Prokhorov Author-X-Name-First: Artem Author-X-Name-Last: Prokhorov Title: A Goodness-of-fit Test for Copulas Abstract: We propose a new rank-based goodness-of-fit test for copulas. It uses the information matrix equality and so relates to the White (1982) specification test. The test avoids parametric specification of marginal distributions, it does not involve kernel weighting, bandwidth selection, or any other strategic choices, it is asymptotically pivotal with a standard distribution, and it is simple to compute compared to available alternatives. The finite-sample size of this type of tests is known to deviate from their nominal size based on asymptotic critical values, and bootstrapping critical values could be a preferred alternative. A power study shows that, in a bivariate setting, the test has reasonable properties compared to its competitors. We conclude with an application in which we apply the test to two stock indices. Journal: Econometric Reviews Pages: 751-771 Issue: 7 Volume: 33 Year: 2014 Month: 10 X-DOI: 10.1080/07474938.2012.690692 File-URL: http://hdl.handle.net/10.1080/07474938.2012.690692 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:33:y:2014:i:7:p:751-771 Template-Type: ReDIF-Article 1.0 Author-Name: Clément Bosquet Author-X-Name-First: Clément Author-X-Name-Last: Bosquet Author-Name: Hervé Boulhol Author-X-Name-First: Hervé Author-X-Name-Last: Boulhol Title: Applying the GLM Variance Assumption to Overcome the Scale-Dependence of the Negative Binomial QGPML Estimator Abstract: Recently, various studies have used the Poisson Pseudo-Maximal Likehood (PML) to estimate gravity specifications of trade flows and non-count data models more generally. Some papers also report results based on the Negative Binomial Quasi-Generalised Pseudo-Maximum Likelihood (NB QGPML) estimator, which encompasses the Poisson assumption as a special case. This note shows that the NB QGPML estimators that have been used so far are unappealing when applied to a continuous dependent variable which unit choice is arbitrary, because estimates artificially depend on that choice. A new NB QGPML estimator is introduced to overcome this shortcoming. Journal: Econometric Reviews Pages: 772-784 Issue: 7 Volume: 33 Year: 2014 Month: 10 X-DOI: 10.1080/07474938.2013.806102 File-URL: http://hdl.handle.net/10.1080/07474938.2013.806102 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:33:y:2014:i:7:p:772-784 Template-Type: ReDIF-Article 1.0 Author-Name: Eduardo Rossi Author-X-Name-First: Eduardo Author-X-Name-Last: Rossi Author-Name: Paolo Santucci de Magistris Author-X-Name-First: Paolo Author-X-Name-Last: Santucci de Magistris Title: Estimation of Long Memory in Integrated Variance Abstract: A stylized fact is that realized variance has long memory. We show that, when the instantaneous volatility is a long memory process of order <italic>d</italic>, the integrated variance is characterized by the same long-range dependence. We prove that the spectral density of realized variance is given by the sum of the spectral density of the integrated variance plus that of a measurement error, due to the sparse sampling and market microstructure noise. Hence, the realized volatility has the same degree of long memory as the integrated variance. The additional term in the spectral density induces a finite-sample bias in the semiparametric estimates of the long memory. A Monte Carlo simulation provides evidence that the corrected local Whittle estimator of Hurvich et al. (2005) is much less biased than the standard local Whittle estimator and the empirical application shows that it is robust to the choice of the sampling frequency used to compute the realized variance. Finally, the empirical results suggest that the volatility series are more likely to be generated by a nonstationary fractional process. Journal: Econometric Reviews Pages: 785-814 Issue: 7 Volume: 33 Year: 2014 Month: 10 X-DOI: 10.1080/07474938.2013.806131 File-URL: http://hdl.handle.net/10.1080/07474938.2013.806131 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:33:y:2014:i:7:p:785-814 Template-Type: ReDIF-Article 1.0 Author-Name: Carlos A. Flores Author-X-Name-First: Carlos A. Author-X-Name-Last: Flores Author-Name: Alfonso Flores-Lagunes Author-X-Name-First: Alfonso Author-X-Name-Last: Flores-Lagunes Author-Name: Dimitrios Kapetanakis Author-X-Name-First: Dimitrios Author-X-Name-Last: Kapetanakis Title: Lessons From Quantile Panel Estimation of the Environmental Kuznets Curve Abstract: We employ quantile regression fixed effects models to estimate the income-pollution relationship on <italic>NO</italic> <sub> <italic>x</italic> </sub> (nitrogen oxide) and <italic>SO</italic> <sub>2</sub> (sulfur dioxide) using U.S. data. Conditional median results suggest that conditional mean methods provide too optimistic estimates about emissions reduction for <italic>NO</italic> <sub> <italic>x</italic> </sub>, while the opposite is found for <italic>SO</italic> <sub>2</sub>. Deleting outlier states reverses the absence of a turning point for <italic>SO</italic> <sub>2</sub> in the conditional mean model, while the conditional median model is robust to them. We also document the relationship's sensitivity to including additional covariates for <italic>NO</italic> <sub> <italic>x</italic> </sub>, and undertake simulations to shed light on some estimation issues of the methods employed. Journal: Econometric Reviews Pages: 815-853 Issue: 8 Volume: 33 Year: 2014 Month: 11 X-DOI: 10.1080/07474938.2013.806148 File-URL: http://hdl.handle.net/10.1080/07474938.2013.806148 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:33:y:2014:i:8:p:815-853 Template-Type: ReDIF-Article 1.0 Author-Name: Andrew Hodge Author-X-Name-First: Andrew Author-X-Name-Last: Hodge Author-Name: Sriram Shankar Author-X-Name-First: Sriram Author-X-Name-Last: Shankar Title: Partial Effects in Ordered Response Models with Factor Variables Abstract: Interpretation in nonlinear regression models that include sets of dummy variables representing categories of underlying categorical variables is not straightforward. Partial effects giving the differences between each category and the reference category are routinely computed in the empirical economics literature. Yet, partial effects yielding the differences between each category and all other categories are not calculated, despite having great interpretative value. We derive the correct formulae for calculating these partial effects for an ordered probit model. The results of an application using data on subjective well-being illustrate the usefulness of the alternative partial effects. Journal: Econometric Reviews Pages: 854-868 Issue: 8 Volume: 33 Year: 2014 Month: 11 X-DOI: 10.1080/07474938.2013.806157 File-URL: http://hdl.handle.net/10.1080/07474938.2013.806157 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:33:y:2014:i:8:p:854-868 Template-Type: ReDIF-Article 1.0 Author-Name: Martin Huber Author-X-Name-First: Martin Author-X-Name-Last: Huber Title: Treatment Evaluation in the Presence of Sample Selection Abstract: Sample selection and attrition are inherent in a range of treatment evaluation problems such as the estimation of the returns to schooling or training. Conventional estimators tackling selection bias typically rely on restrictive functional form assumptions that are unlikely to hold in reality. This paper shows identification of average and quantile treatment effects in the presence of the double selection problem into (i) a selective subpopulation (e.g., working-selection on unobservables) and (ii) a binary treatment (e.g., training-selection on observables) based on weighting observations by the inverse of a nested propensity score that characterizes either selection probability. Weighting estimators based on parametric propensity score models are applied to female labor market data to estimate the returns to education. Journal: Econometric Reviews Pages: 869-905 Issue: 8 Volume: 33 Year: 2014 Month: 11 X-DOI: 10.1080/07474938.2013.806197 File-URL: http://hdl.handle.net/10.1080/07474938.2013.806197 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:33:y:2014:i:8:p:869-905 Template-Type: ReDIF-Article 1.0 Author-Name: Ted Juhl Author-X-Name-First: Ted Author-X-Name-Last: Juhl Author-Name: Oleksandr Lugovskyy Author-X-Name-First: Oleksandr Author-X-Name-Last: Lugovskyy Title: A Test for Slope Heterogeneity in Fixed Effects Models Abstract: Typical panel data models make use of the assumption that the regression parameters are the same for each individual cross-sectional unit. We propose tests for slope heterogeneity in panel data models. Our tests are based on the conditional Gaussian likelihood function in order to avoid the incidental parameters problem induced by the inclusion of individual fixed effects for each cross-sectional unit. We derive the Conditional Lagrange Multiplier test that is valid in cases where <italic>N</italic> → ∞ and <italic>T</italic> is fixed. The test applies to both balanced and unbalanced panels. We expand the test to account for general heteroskedasticity where each cross-sectional unit has its own form of heteroskedasticity. The modification is possible if <italic>T</italic> is large enough to estimate regression coefficients for each cross-sectional unit by using the MINQUE unbiased estimator for regression variances under heteroskedasticity. All versions of the test have a standard Normal distribution under general assumptions on the error distribution as <italic>N</italic> → ∞. A Monte Carlo experiment shows that the test has very good size properties under all specifications considered, including heteroskedastic errors. In addition, power of our test is very good relative to existing tests, particularly when <italic>T</italic> is not large. Journal: Econometric Reviews Pages: 906-935 Issue: 8 Volume: 33 Year: 2014 Month: 11 X-DOI: 10.1080/07474938.2013.806708 File-URL: http://hdl.handle.net/10.1080/07474938.2013.806708 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:33:y:2014:i:8:p:906-935 Template-Type: ReDIF-Article 1.0 Author-Name: Hiroshi Yamada Author-X-Name-First: Hiroshi Author-X-Name-Last: Yamada Author-Name: Wei Yanfeng Author-X-Name-First: Wei Author-X-Name-Last: Yanfeng Title: Some Theoretical and Simulation Results on the Frequency Domain Causality Test Abstract: Breitung and Candelon (2006) in <italic>Journal of Econometrics</italic> proposed a simple statistical testing procedure for the noncausality hypothesis at a given frequency. In their paper, however, they reported some theoretical results indicating that their test severely suffers from quite low power when the noncausality hypothesis is tested at a frequency close to 0 or pi. This paper examines whether or not these results indicate their procedure is useless at such frequencies. Journal: Econometric Reviews Pages: 936-947 Issue: 8 Volume: 33 Year: 2014 Month: 11 X-DOI: 10.1080/07474938.2013.808488 File-URL: http://hdl.handle.net/10.1080/07474938.2013.808488 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:33:y:2014:i:8:p:936-947 Template-Type: ReDIF-Article 1.0 Author-Name: James J. Heckman Author-X-Name-First: James J. Author-X-Name-Last: Heckman Author-Name: Apostolos Serletis Author-X-Name-First: Apostolos Author-X-Name-Last: Serletis Title: Introduction to Econometrics with Theory: A Special Issue Honoring William A. Barnett Abstract: This special issue of <italic>Econometric Reviews</italic> honors William A. Barnett's exceptional contributions in the field of economics. It follows and complements a recent <italic>Journal of Econometrics</italic> special issue also in honor of William A. Barnett, Internally Consistent Modeling, Aggregation, Inference, and Policy, and is devoted to papers with emphasis on research in the time domain both at the individual and aggregate level. Journal: Econometric Reviews Pages: 1-5 Issue: 1-2 Volume: 34 Year: 2015 Month: 2 X-DOI: 10.1080/07474938.2014.944465 File-URL: http://hdl.handle.net/10.1080/07474938.2014.944465 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:34:y:2015:i:1-2:p:1-5 Template-Type: ReDIF-Article 1.0 Author-Name: James J. Heckman Author-X-Name-First: James J. Author-X-Name-Last: Heckman Author-Name: Rodrigo Pinto Author-X-Name-First: Rodrigo Author-X-Name-Last: Pinto Title: Econometric Mediation Analyses: Identifying the Sources of Treatment Effects from Experimentally Estimated Production Technologies with Unmeasured and Mismeasured Inputs Abstract: This paper presents an econometric mediation analysis. It considers identification of production functions and the sources of output effects (treatment effects) from experimental interventions when some inputs are mismeasured and others are entirely omitted. Journal: Econometric Reviews Pages: 6-31 Issue: 1-2 Volume: 34 Year: 2015 Month: 2 X-DOI: 10.1080/07474938.2014.944466 File-URL: http://hdl.handle.net/10.1080/07474938.2014.944466 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:34:y:2015:i:1-2:p:6-31 Template-Type: ReDIF-Article 1.0 Author-Name: Charles Engel Author-X-Name-First: Charles Author-X-Name-Last: Engel Author-Name: Nelson C. Mark Author-X-Name-First: Nelson C. Author-X-Name-Last: Mark Author-Name: Kenneth D. West Author-X-Name-First: Kenneth D. Author-X-Name-Last: West Title: Factor Model Forecasts of Exchange Rates Abstract: We construct factors from a cross-section of exchange rates and use the idiosyncratic deviations from the factors to forecast. In a stylized data generating process, we show that such forecasts can be effective even if there is essentially no serial correlation in the univariate exchange rate processes. We apply the technique to a panel of bilateral U.S. dollar rates against 17 Organisation for Economic Co-operation and Development countries. We forecast using factors, and using factors combined with any of fundamentals suggested by Taylor rule, monetary and purchasing power parity models. For long horizon (8 and 12 quarter) forecasts, we tend to improve on the forecast of a "no change" benchmark in the late (1999-2007) but not early (1987-1998) parts of our sample. Journal: Econometric Reviews Pages: 32-55 Issue: 1-2 Volume: 34 Year: 2015 Month: 2 X-DOI: 10.1080/07474938.2014.944467 File-URL: http://hdl.handle.net/10.1080/07474938.2014.944467 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:34:y:2015:i:1-2:p:32-55 Template-Type: ReDIF-Article 1.0 Author-Name: Arnold Zellner Author-X-Name-First: Arnold Author-X-Name-Last: Zellner Author-Name: Jacques Kibambe Ngoie Author-X-Name-First: Jacques Kibambe Author-X-Name-Last: Ngoie Title: Evaluation of the Effects of Reduced Personal and Corporate Tax Rates on the Growth Rates of the U.S. Economy Abstract: Using several variants of a Marshallian Macroeconomic Model (MMM), see Zellner and Israilevich (2005) and Ngoie and Zellner (2010), this paper investigates how various tax rate reductions may help stimulate the U.S. economy while not adversely affecting aggregate U.S. debt. Variants of our MMM that are shown to fit past data and to perform well in forecasting experiments are employed to evaluate the effects of alternative tax policies. Using quarterly data, our one-sector MMM has been able to predict the 2008 downturn and the 2009Q3 upturn of the U.S. economy. Among other results, this study, using transfer and impulse response functions associated with our MMM, finds that permanent 5 percentage points cut in the personal income and corporate profits tax rates will cause the U.S. real gross domestic product (GDP) growth rate to rise by 3.0 percentage points with a standard error of 0.6 percentage points. Also, while this policy change leads to positive growth of the government sector, its share of total real GDP is slightly reduced. This is understandable since short run effects of tax cuts include the transfer of tax revenue from the government to the private sector. The private sector is allowed to manage a larger portion of its revenue, while government is forced to cut public spending on social programs with little growth enhancing effects. This broadens private economic activities overall. Further, these tax rate policy changes stimulate the growth of the federal tax base considerably, which helps to reduce annual budget deficits and the federal debt. Journal: Econometric Reviews Pages: 56-81 Issue: 1-2 Volume: 34 Year: 2015 Month: 2 X-DOI: 10.1080/07474938.2014.944468 File-URL: http://hdl.handle.net/10.1080/07474938.2014.944468 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:34:y:2015:i:1-2:p:56-81 Template-Type: ReDIF-Article 1.0 Author-Name: Yingying Dong Author-X-Name-First: Yingying Author-X-Name-Last: Dong Author-Name: Arthur Lewbel Author-X-Name-First: Arthur Author-X-Name-Last: Lewbel Title: A Simple Estimator for Binary Choice Models with Endogenous Regressors Abstract: This paper provides a few variants of a simple estimator for binary choice models with endogenous or mismeasured regressors, or with heteroskedastic errors, or with panel fixed effects. Unlike control function methods, which are generally only valid when endogenous regressors are continuous, the estimators proposed here can be used with limited, censored, continuous, or discrete endogenous regressors, and they allow for latent errors having heteroskedasticity of unknown form, including random coefficients. The variants of special regressor based estimators we provide are numerically trivial to implement. We illustrate these methods with an empirical application estimating migration probabilities within the US. Journal: Econometric Reviews Pages: 82-105 Issue: 1-2 Volume: 34 Year: 2015 Month: 2 X-DOI: 10.1080/07474938.2014.944470 File-URL: http://hdl.handle.net/10.1080/07474938.2014.944470 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:34:y:2015:i:1-2:p:82-105 Template-Type: ReDIF-Article 1.0 Author-Name: W. Erwin Diewert Author-X-Name-First: W. Erwin Author-X-Name-Last: Diewert Author-Name: Jan de Haan Author-X-Name-First: Jan de Author-X-Name-Last: Haan Author-Name: Rens Hendriks Author-X-Name-First: Rens Author-X-Name-Last: Hendriks Title: Hedonic Regressions and the Decomposition of a House Price Index into Land and Structure Components Abstract: The paper uses hedonic regression techniques in order to decompose the price of a house into land and structure components using readily available real estate sales data for a small Dutch city. To get sensible results, it was useful to estimate a nonlinear model on data that cover multiple time periods. It also proved necessary to incorporate exogenous information on the rate of growth of construction costs in the Netherlands in order to obtain meaningful constant quality indexes for the price of land and structures separately. Journal: Econometric Reviews Pages: 106-126 Issue: 1-2 Volume: 34 Year: 2015 Month: 2 X-DOI: 10.1080/07474938.2014.944791 File-URL: http://hdl.handle.net/10.1080/07474938.2014.944791 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:34:y:2015:i:1-2:p:106-126 Template-Type: ReDIF-Article 1.0 Author-Name: Yiguo Sun Author-X-Name-First: Yiguo Author-X-Name-Last: Sun Author-Name: Cheng Hsiao Author-X-Name-First: Cheng Author-X-Name-Last: Hsiao Author-Name: Qi Li Author-X-Name-First: Qi Author-X-Name-Last: Li Title: Volatility Spillover Effect: A Semiparametric Analysis of Non-Cointegrated Process Abstract: Stock market volatility is highly persistent and exhibits large fluctuations so that it is likely to be an integrated or a near integrated process. Stock markets' volatilities from different countries are intercorrelated, but are generally not cointegrated as many other (domestic) factors also affect volatility. In this paper, we use a semiparametric varying coefficient model to examine stock market volatility spillover effects. Using the estimation method proposed by Sun et al. (2011), we study the U.S./U.K. and U.S./Canadian stock market volatility spillover effects. We find striking similar patterns in both the U.S./U.K. and the U.S./Canadian markets. The stock market volatility spillover effects are strengthened when the currency markets experience high movement, and the spillover effects are asymmetric depending on whether a foreign currency is appreciating or depreciating. Journal: Econometric Reviews Pages: 127-145 Issue: 1-2 Volume: 34 Year: 2015 Month: 2 X-DOI: 10.1080/07474938.2014.944793 File-URL: http://hdl.handle.net/10.1080/07474938.2014.944793 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:34:y:2015:i:1-2:p:127-145 Template-Type: ReDIF-Article 1.0 Author-Name: Shigeru Iwata Author-X-Name-First: Shigeru Author-X-Name-Last: Iwata Author-Name: Han Li Author-X-Name-First: Han Author-X-Name-Last: Li Title: What are the Differences in Trend Cycle Decompositions by Beveridge and Nelson and by Unobserved Component Models? Abstract: When a certain procedure is applied to extract two component processes from a single observed process, it is necessary to impose a set of restrictions that defines two components. One popular restriction is the assumption that the shocks to the trend and cycle are orthogonal. Another is the assumption that the trend is a pure random walk process. The unobserved components (UC) model (Harvey, 1985) assumes both of the above, whereas the BN decomposition (Beveridge and Nelson, 1981) assumes only the latter. Quah (1992) investigates a broad class of decompositions by making the former assumption only. This paper develops a convenient general framework in which alternative trend-cycle decompositions are regarded as special cases, and examines alternative decomposition schemes from the perspective of the frequency domain. We find that, although the conventional UC model is not necessarily a misspecification for describing the postwar U.S. GDP, choosing a univariate model among alternatives on the purely statistical grounds is difficult. Journal: Econometric Reviews Pages: 146-173 Issue: 1-2 Volume: 34 Year: 2015 Month: 2 X-DOI: 10.1080/07474938.2014.945335 File-URL: http://hdl.handle.net/10.1080/07474938.2014.945335 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:34:y:2015:i:1-2:p:146-173 Template-Type: ReDIF-Article 1.0 Author-Name: Annastiina Silvennoinen Author-X-Name-First: Annastiina Author-X-Name-Last: Silvennoinen Author-Name: Timo Ter�svirta Author-X-Name-First: Timo Author-X-Name-Last: Ter�svirta Title: Modeling Conditional Correlations of Asset Returns: A Smooth Transition Approach Abstract: In this paper we propose a new multivariate GARCH model with time-varying conditional correlation structure. The time-varying conditional correlations change smoothly between two extreme states of constant correlations according to a predetermined or exogenous transition variable. An LM-test is derived to test the constancy of correlations and LM- and Wald tests to test the hypothesis of partially constant correlations. Analytical expressions for the test statistics and the required derivatives are provided to make computations feasible. An empirical example based on daily return series of five frequently traded stocks in the S&P 500 stock index completes the paper. Journal: Econometric Reviews Pages: 174-197 Issue: 1-2 Volume: 34 Year: 2015 Month: 2 X-DOI: 10.1080/07474938.2014.945336 File-URL: http://hdl.handle.net/10.1080/07474938.2014.945336 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:34:y:2015:i:1-2:p:174-197 Template-Type: ReDIF-Article 1.0 Author-Name: Apostolos Serletis Author-X-Name-First: Apostolos Author-X-Name-Last: Serletis Author-Name: Guohua Feng Author-X-Name-First: Guohua Author-X-Name-Last: Feng Title: Imposing Theoretical Regularity on Flexible Functional Forms Abstract: In this paper we build on work by Gallant and Golub (1984), Diewert and Wales (1987), and Barnett (2002) and provide a comparison among three different methods of imposing theoretical regularity on flexible functional forms-reparameterization using Cholesky factorization, constrained optimization, and Bayesian methodology. We apply the methodology to a translog cost and share equation system and make a distinction between local, regional, pointwise, and global regularity. We find that the imposition of curvature at a single point does not always assure regularity. We also find that the imposition of global concavity (at all possible, positive input prices), irrespective of the method used, exaggerates the elasticity estimates and rules out the possibility of a complementarity relationship among the inputs. Finally, we find that constrained optimization and the Bayesian methodology with regional (over a neighborhood of data points in the sample) or pointwise (at every data point in the sample) concavity imposed can guarantee inference consistent with neoclassical microeconomic theory, without compromising much of the flexibility of the functional form. Journal: Econometric Reviews Pages: 198-227 Issue: 1-2 Volume: 34 Year: 2015 Month: 2 X-DOI: 10.1080/07474938.2014.945385 File-URL: http://hdl.handle.net/10.1080/07474938.2014.945385 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:34:y:2015:i:1-2:p:198-227 Template-Type: ReDIF-Article 1.0 Author-Name: Richard G. Anderson Author-X-Name-First: Richard G. Author-X-Name-Last: Anderson Author-Name: Marcelle Chauvet Author-X-Name-First: Marcelle Author-X-Name-Last: Chauvet Author-Name: Barry Jones Author-X-Name-First: Barry Author-X-Name-Last: Jones Title: Nonlinear Relationship Between Permanent and Transitory Components of Monetary Aggregates and the Economy Abstract: This paper uses several methods to study the interrelationship among Divisia monetary aggregates, prices, and income, allowing for nonstationary, nonlinearities, asymmetries, and time-varying relationships among the series. We propose a multivariate regime switching unobserved components model to obtain transitory and permanent components for each series, allowing for potential recurrent and structural changes in their dynamics. Each component follows distinct two-state Markov processes representing low or high phases. Since the lead-lag relationship between the phases can vary over time, rather than pre-imposing a structure to their linkages, the proposed flexible framework enables us to study their specific lead-lag relationship over each one of their cycles and over each U.S. recession in the last 40 years. The decomposition of the series into permanent and transitory components reveals striking results. First, we find a strong nonlinear association between the components of money and prices-all low phases of the transitory component of prices were preceded by tight transitory and permanent money phases. We also find that most recessions were preceded by tight money phases (its cyclical and permanent components) and high transitory price phases (with the exception of the 2001 and 2009-2010 recessions). In addition, all recessions were associated with a decrease in transitory and permanent income. Journal: Econometric Reviews Pages: 228-254 Issue: 1-2 Volume: 34 Year: 2015 Month: 2 X-DOI: 10.1080/07474938.2014.945386 File-URL: http://hdl.handle.net/10.1080/07474938.2014.945386 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:34:y:2015:i:1-2:p:228-254 Template-Type: ReDIF-Article 1.0 Author-Name: Amos Golan Author-X-Name-First: Amos Author-X-Name-Last: Golan Author-Name: Esfandiar Maasoumi Author-X-Name-First: Esfandiar Author-X-Name-Last: Maasoumi Title: Editorial Note Journal: Econometric Reviews Pages: 255-255 Issue: 3 Volume: 34 Year: 2015 Month: 3 X-DOI: 10.1080/07474938.2014.944472 File-URL: http://hdl.handle.net/10.1080/07474938.2014.944472 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:34:y:2015:i:3:p:255-255 Template-Type: ReDIF-Article 1.0 Author-Name: Joshua C. C. Chan Author-X-Name-First: Joshua C. C. Author-X-Name-Last: Chan Author-Name: Eric Eisenstat Author-X-Name-First: Eric Author-X-Name-Last: Eisenstat Title: Marginal Likelihood Estimation with the Cross-Entropy Method Abstract: We consider an adaptive importance sampling approach to estimating the marginal likelihood, a quantity that is fundamental in Bayesian model comparison and Bayesian model averaging. This approach is motivated by the difficulty of obtaining an accurate estimate through existing algorithms that use Markov chain Monte Carlo (MCMC) draws, where the draws are typically costly to obtain and highly correlated in high-dimensional settings. In contrast, we use the cross-entropy (CE) method, a versatile adaptive Monte Carlo algorithm originally developed for rare-event simulation. The main advantage of the importance sampling approach is that random samples can be obtained from some convenient density with little additional costs. As we are generating <italic>independent</italic> draws instead of <italic>correlated</italic> MCMC draws, the increase in simulation effort is much smaller should one wish to reduce the numerical standard error of the estimator. Moreover, the importance density derived via the CE method is grounded in information theory, and therefore, is in a well-defined sense optimal. We demonstrate the utility of the proposed approach by two empirical applications involving women's labor market participation and U.S. macroeconomic time series. In both applications, the proposed CE method compares favorably to existing estimators. Journal: Econometric Reviews Pages: 256-285 Issue: 3 Volume: 34 Year: 2015 Month: 3 X-DOI: 10.1080/07474938.2014.944474 File-URL: http://hdl.handle.net/10.1080/07474938.2014.944474 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:34:y:2015:i:3:p:256-285 Template-Type: ReDIF-Article 1.0 Author-Name: Alastair R. Hall Author-X-Name-First: Alastair R. Author-X-Name-Last: Hall Author-Name: Yuyi Li Author-X-Name-First: Yuyi Author-X-Name-Last: Li Author-Name: Chris D. Orme Author-X-Name-First: Chris D. Author-X-Name-Last: Orme Author-Name: Arthur Sinko Author-X-Name-First: Arthur Author-X-Name-Last: Sinko Title: Testing for Structural Instability in Moment Restriction Models: An Info-Metric Approach Abstract: In this paper, we develop an info-metric framework for testing hypotheses about structural instability in nonlinear, dynamic models estimated from the information in population moment conditions. Our methods are designed to distinguish between three states of the world: (i) the model is structurally stable in the sense that the population moment condition holds at the same parameter value throughout the sample; (ii) the model parameters change at some point in the sample but otherwise the model is correctly specified; and (iii) the model exhibits more general forms of instability than a single shift in the parameters. An advantage of the info-metric approach is that the null hypotheses concerned are formulated in terms of distances between various choices of probability measures constrained to satisfy (i) and (ii), and the empirical measure of the sample. Under the alternative hypotheses considered, the model is assumed to exhibit structural instability at a single point in the sample, referred to as the break point; our analysis allows for the break point to be either fixed <italic>a priori</italic> or treated as occuring at some unknown point within a certain fraction of the sample. We propose various test statistics that can be thought of as sample analogs of the distances described above, and derive their limiting distributions under the appropriate null hypothesis. The limiting distributions of our statistics are nonstandard but coincide with various distributions that arise in the literature on structural instability testing within the Generalized Method of Moments framework. A small simulation study illustrates the finite sample performance of our test statistics. Journal: Econometric Reviews Pages: 286-327 Issue: 3 Volume: 34 Year: 2015 Month: 3 X-DOI: 10.1080/07474938.2014.944477 File-URL: http://hdl.handle.net/10.1080/07474938.2014.944477 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:34:y:2015:i:3:p:286-327 Template-Type: ReDIF-Article 1.0 Author-Name: Saraswata Chaudhuri Author-X-Name-First: Saraswata Author-X-Name-Last: Chaudhuri Author-Name: Eric Renault Author-X-Name-First: Eric Author-X-Name-Last: Renault Title: Shrinkage of Variance for Minimum Distance Based Tests Abstract: This paper promotes information theoretic inference in the context of minimum distance estimation. Various score test statistics differ only through the embedded estimator of the variance of estimating functions. We resort to implied probabilities provided by the constrained maximization of generalized entropy to get a more accurate variance estimator under the null. We document, both by theoretical higher order expansions and by Monte-Carlo evidence, that our improved score tests have better finite-sample size properties. The competitiveness of our non-simulation based method with respect to bootstrap is confirmed in the example of inference on covariance structures previously studied by Horowitz (1998). Journal: Econometric Reviews Pages: 328-351 Issue: 3 Volume: 34 Year: 2015 Month: 3 X-DOI: 10.1080/07474938.2014.944794 File-URL: http://hdl.handle.net/10.1080/07474938.2014.944794 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:34:y:2015:i:3:p:328-351 Template-Type: ReDIF-Article 1.0 Author-Name: Lorenzo Camponovo Author-X-Name-First: Lorenzo Author-X-Name-Last: Camponovo Author-Name: Taisuke Otsu Author-X-Name-First: Taisuke Author-X-Name-Last: Otsu Title: Robustness of Bootstrap in Instrumental Variable Regression Abstract: This paper studies robustness of bootstrap inference methods for instrumental variable (IV) regression models. We consider test statistics for parameter hypotheses based on the IV estimator and generalized method of trimmed moments (GMTM) estimator introduced by Č�žek (2008, 2009), and compare the pairs and implied probability bootstrap approximations for these statistics by applying the finite sample breakdown point theory. In particular, we study limiting behaviors of the bootstrap quantiles when the values of outliers diverge to infinity but the sample size is held fixed. The outliers are defined as anomalous observations that can arbitrarily change the value of the statistic of interest. We analyze both just- and overidentified cases and discuss implications of the breakdown point analysis to the size and power properties of bootstrap tests. We conclude that the implied probability bootstrap test using the statistic based on the GMTM estimator shows desirable robustness properties. Simulation studies endorse this conclusion. An empirical example based on Romer's (1993) study on the effect of openness of countries to inflation rates is presented. Several extensions including the analysis for the residual bootstrap are provided. Journal: Econometric Reviews Pages: 352-393 Issue: 3 Volume: 34 Year: 2015 Month: 3 X-DOI: 10.1080/07474938.2014.944803 File-URL: http://hdl.handle.net/10.1080/07474938.2014.944803 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:34:y:2015:i:3:p:352-393 Template-Type: ReDIF-Article 1.0 Author-Name: Song Li Author-X-Name-First: Song Author-X-Name-Last: Li Author-Name: Mervyn J. Silvapulle Author-X-Name-First: Mervyn J. Author-X-Name-Last: Silvapulle Author-Name: Param Silvapulle Author-X-Name-First: Param Author-X-Name-Last: Silvapulle Author-Name: Xibin Zhang Author-X-Name-First: Xibin Author-X-Name-Last: Zhang Title: Bayesian Approaches to Nonparametric Estimation of Densities on the Unit Interval Abstract: This paper investigates nonparametric estimation of density on [0, 1]. The kernel estimator of density on [0, 1] has been found to be sensitive to both bandwidth and kernel. This paper proposes a unified Bayesian framework for choosing both the bandwidth and kernel function. In a simulation study, the Bayesian bandwidth estimator performed better than others, and kernel estimators were sensitive to the choice of the kernel and the shapes of the population densities on [0, 1]. The simulation and empirical results demonstrate that the methods proposed in this paper can improve the way the probability densities on [0, 1] are presently estimated. Journal: Econometric Reviews Pages: 394-412 Issue: 3 Volume: 34 Year: 2015 Month: 3 X-DOI: 10.1080/07474938.2013.807130 File-URL: http://hdl.handle.net/10.1080/07474938.2013.807130 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:34:y:2015:i:3:p:394-412 Template-Type: ReDIF-Article 1.0 Author-Name: Carlos Martins-Filho Author-X-Name-First: Carlos Author-X-Name-Last: Martins-Filho Author-Name: Feng Yao Author-X-Name-First: Feng Author-X-Name-Last: Yao Title: Semiparametric Stochastic Frontier Estimation via Profile Likelihood Abstract: We consider the estimation of a nonparametric stochastic frontier model with composite error density which is known up to a finite parameter vector. Our primary interest is on the estimation of the parameter vector, as it provides the basis for estimation of firm specific (in)efficiency. Our frontier model is similar to that of Fan et al. (1996), but here we extend their work in that: a) we establish the asymptotic properties of their estimation procedure, and b) propose and establish the asymptotic properties of an alternative estimator based on the maximization of a conditional profile likelihood function. The estimator proposed in Fan et al. (1996) is asymptotically normally distributed but has bias which does not vanish as the sample size <italic>n</italic> → ∞. In contrast, our proposed estimator is asymptotically normally distributed and correctly centered at the true value of the parameter vector. In addition, our estimator is shown to be efficient in a broad class of semiparametric estimators. Our estimation procedure provides a fast converging alternative to the recently proposed estimator in Kumbhakar et al. (2007). A Monte Carlo study is performed to shed light on the finite sample properties of these competing estimators. Journal: Econometric Reviews Pages: 413-451 Issue: 4 Volume: 34 Year: 2015 Month: 4 X-DOI: 10.1080/07474938.2013.806729 File-URL: http://hdl.handle.net/10.1080/07474938.2013.806729 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:34:y:2015:i:4:p:413-451 Template-Type: ReDIF-Article 1.0 Author-Name: Arturo Leccadito Author-X-Name-First: Arturo Author-X-Name-Last: Leccadito Author-Name: Omar Rachedi Author-X-Name-First: Omar Author-X-Name-Last: Rachedi Author-Name: Giovanni Urga Author-X-Name-First: Giovanni Author-X-Name-Last: Urga Title: True Versus Spurious Long Memory: Some Theoretical Results and a Monte Carlo Comparison Abstract: A common feature of financial time series is their strong persistence. Yet, long memory may just be the spurious effect of either structural breaks or slow switching regimes. We explore the effects of spurious long memory on the elasticity of the stock market price with respect to volatility and show how cross-sectional aggregation may generate spurious persistence in the data. We undertake an extensive Monte Carlo study to compare the performance of five tests, constructed under the null of true long memory versus the alternative of spurious long memory due to level shifts or breaks. Journal: Econometric Reviews Pages: 452-479 Issue: 4 Volume: 34 Year: 2015 Month: 4 X-DOI: 10.1080/07474938.2013.808462 File-URL: http://hdl.handle.net/10.1080/07474938.2013.808462 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:34:y:2015:i:4:p:452-479 Template-Type: ReDIF-Article 1.0 Author-Name: Dingan Feng Author-X-Name-First: Dingan Author-X-Name-Last: Feng Author-Name: Peter X.-K. Song Author-X-Name-First: Peter X.-K. Author-X-Name-Last: Song Author-Name: Tony S. Wirjanto Author-X-Name-First: Tony S. Author-X-Name-Last: Wirjanto Title: Time-Deformation Modeling of Stock Returns Directed by Duration Processes Abstract: This paper proposes a new time-deformation model for stock returns sampled in transaction time and directed by a generalized duration process. Stochastic volatility in this model is driven by an observed duration process and a latent autoregressive process. Parameter estimation in the model is carried out by using a method of simulated moments (MSM) due to its analytical tractability and numerical stability for the proposed model. Simulations are conducted to validate the choice of moments used in the formulation of MSM. Both simulation and empirical results indicate that the proposed MSM works well for the model. The main empirical findings from the analysis of IBM transaction return data include: (i) the return distribution conditional on the duration process is not Gaussian, even though the duration process itself can marginally serve as a directing process; (ii) the return process is highly leveraged; (iii) longer trade duration tends to be associated with higher return volatility; and (iv) the proposed model is capable of reproducing a return process whose marginal density function is close to that of the empirical return process. Journal: Econometric Reviews Pages: 480-511 Issue: 4 Volume: 34 Year: 2015 Month: 4 X-DOI: 10.1080/07474938.2013.808478 File-URL: http://hdl.handle.net/10.1080/07474938.2013.808478 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:34:y:2015:i:4:p:480-511 Template-Type: ReDIF-Article 1.0 Author-Name: Giuseppe Cavaliere Author-X-Name-First: Giuseppe Author-X-Name-Last: Cavaliere Author-Name: Peter C. B. Phillips Author-X-Name-First: Peter C. B. Author-X-Name-Last: Phillips Author-Name: Stephan Smeekes Author-X-Name-First: Stephan Author-X-Name-Last: Smeekes Author-Name: A. M. Robert Taylor Author-X-Name-First: A. M. Robert Author-X-Name-Last: Taylor Title: Lag Length Selection for Unit Root Tests in the Presence of Nonstationary Volatility Abstract: A number of recent papers have focused on the problem of testing for a unit root in the case where the driving shocks may be unconditionally heteroskedastic. These papers have, however, taken the lag length in the unit root test regression to be a deterministic function of the sample size, rather than data-determined, the latter being standard empirical practice. We investigate the finite sample impact of unconditional heteroskedasticity on conventional data-dependent lag selection methods in augmented Dickey-Fuller type regressions and propose new lag selection criteria which allow for unconditional heteroskedasticity. Standard lag selection methods are shown to have a tendency to over-fit the lag order under heteroskedasticity, resulting in significant power losses in the (wild bootstrap implementation of the) augmented Dickey-Fuller tests under the alternative. The proposed new lag selection criteria are shown to avoid this problem yet deliver unit root tests with almost identical finite sample properties as the corresponding tests based on conventional lag selection when the shocks are homoskedastic. Journal: Econometric Reviews Pages: 512-536 Issue: 4 Volume: 34 Year: 2015 Month: 4 X-DOI: 10.1080/07474938.2013.808065 File-URL: http://hdl.handle.net/10.1080/07474938.2013.808065 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:34:y:2015:i:4:p:512-536 Template-Type: ReDIF-Article 1.0 Author-Name: Markus Jochmann Author-X-Name-First: Markus Author-X-Name-Last: Jochmann Title: Modeling U.S. Inflation Dynamics: A Bayesian Nonparametric Approach Abstract: The properties of the inflation process and especially possible changes in its persistence have received much attention in the literature. However, empirical evidence is ambiguous. Some studies find that inflation persistence varied over time, others conclude it was constant. This article contributes further evidence to this ongoing debate by modeling U.S. inflation dynamics using a <italic>sticky infinite hidden Markov model</italic> (sticky IHMM). The sticky IHMM is a Bayesian nonparametric approach to modeling structural breaks. It allows for an unknown number of breakpoints and is a flexible and attractive alternative to existing methods. We found that inflation persistence was highest in 1973-74 and then again around 1980. However, credible intervals for our estimates of inflation persistence were very wide. Thus, a substantial amount of uncertainty about this aspect of inflation dynamics remained. Journal: Econometric Reviews Pages: 537-558 Issue: 5 Volume: 34 Year: 2015 Month: 5 X-DOI: 10.1080/07474938.2013.806199 File-URL: http://hdl.handle.net/10.1080/07474938.2013.806199 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:34:y:2015:i:5:p:537-558 Template-Type: ReDIF-Article 1.0 Author-Name: Massimiliano Caporin Author-X-Name-First: Massimiliano Author-X-Name-Last: Caporin Author-Name: Paolo Paruolo Author-X-Name-First: Paolo Author-X-Name-Last: Paruolo Title: Proximity-Structured Multivariate Volatility Models Abstract: In many multivariate volatility models, the number of parameters increases faster than the cross-section dimension, hence creating a curse of dimensionality problem. This paper discusses specification and identification of structured parameterizations based on weight matrices induced by economic proximity. It is shown that structured specifications can mitigate or even solve the curse of dimensionality problem. Identification and estimation of structured specifications are analyzed, rank and order conditions for identification are given and the specification of weight matrices is discussed. Several structured specifications compare well with alternatives in modelling conditional covariances of six returns from the New York Stock Exchange. Journal: Econometric Reviews Pages: 559-593 Issue: 5 Volume: 34 Year: 2015 Month: 5 X-DOI: 10.1080/07474938.2013.807102 File-URL: http://hdl.handle.net/10.1080/07474938.2013.807102 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:34:y:2015:i:5:p:559-593 Template-Type: ReDIF-Article 1.0 Author-Name: Alexios Ghalanos Author-X-Name-First: Alexios Author-X-Name-Last: Ghalanos Author-Name: Eduardo Rossi Author-X-Name-First: Eduardo Author-X-Name-Last: Rossi Author-Name: Giovanni Urga Author-X-Name-First: Giovanni Author-X-Name-Last: Urga Title: Independent Factor Autoregressive Conditional Density Model Abstract: In this article, we propose a novel Independent Factor Autoregressive Conditional Density (IFACD) model able to generate time-varying higher moments using an independent factor setup. Our proposed framework incorporates dynamic estimation of higher comovements and feasible portfolio representation within a non-elliptical multivariate distribution. We report an empirical application, using returns data from 14 MSCI equity index iShares for the period 1996 to 2010, and we show that the IFACD model provides superior VaR forecasts and portfolio allocations with respect to the Conditionally Heteroskedastic Independent Component Analysis of Generalized Orthogonal (CHICAGO) and DCC models. Journal: Econometric Reviews Pages: 594-616 Issue: 5 Volume: 34 Year: 2015 Month: 5 X-DOI: 10.1080/07474938.2013.808561 File-URL: http://hdl.handle.net/10.1080/07474938.2013.808561 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:34:y:2015:i:5:p:594-616 Template-Type: ReDIF-Article 1.0 Author-Name: Yi-Ting Chen Author-X-Name-First: Yi-Ting Author-X-Name-Last: Chen Author-Name: Zhongjun Qu Author-X-Name-First: Zhongjun Author-X-Name-Last: Qu Title: <italic>M</italic> Tests with a New Normalization Matrix Abstract: This paper proposes a new family of <italic>M</italic> tests building on the work of Kuan and Lee (2006) and Kiefer et al. (2000). The idea is to replace the asymptotic covariance matrix in conventional <italic>M</italic> tests with an alternative normalization matrix, constructed using moment functions estimated from (<italic>K</italic> + 1) recursive subsamples. The new tests are simple to implement. They automatically account for the effect of parameter estimation and allow for conditional heteroskedasticity and serial correlation of general forms. They converge to central <italic>F</italic> distributions under the fixed-<italic>K</italic> asymptotics and to chi-square distributions if <italic>K</italic> is allowed to approach infinity. We illustrate their applications using three simulation examples: (1) specification testing for conditional heteroskedastic models, (2) non-nested testing with serially correlated errors, and (3) testing for serial correlation with unknown heteroskedasticity. The results show that the new tests exhibit good size properties with power often comparable to the conventional <italic>M</italic> tests while being substantially higher than that of Kuan and Lee (2006). Journal: Econometric Reviews Pages: 617-652 Issue: 5 Volume: 34 Year: 2015 Month: 5 X-DOI: 10.1080/07474938.2013.833822 File-URL: http://hdl.handle.net/10.1080/07474938.2013.833822 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:34:y:2015:i:5:p:617-652 Template-Type: ReDIF-Article 1.0 Author-Name: Esfandiar Maasoumi Author-X-Name-First: Esfandiar Author-X-Name-Last: Maasoumi Author-Name: Qi Li Author-X-Name-First: Qi Author-X-Name-Last: Li Title: The Special Issue in Honor of Aman Ullah: An Overview Journal: Econometric Reviews Pages: 653-658 Issue: 6-10 Volume: 34 Year: 2015 Month: 12 X-DOI: 10.1080/07474938.2014.956028 File-URL: http://hdl.handle.net/10.1080/07474938.2014.956028 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:34:y:2015:i:6-10:p:653-658 Template-Type: ReDIF-Article 1.0 Author-Name: Badi H. Baltagi Author-X-Name-First: Badi H. Author-X-Name-Last: Baltagi Author-Name: Ying Deng Author-X-Name-First: Ying Author-X-Name-Last: Deng Title: EC3SLS Estimator for a Simultaneous System of Spatial Autoregressive Equations with Random Effects Abstract: This article derives a 3SLS estimator for a simultaneous system of spatial autoregressive equations with random effects which can therefore handle endoegeneity, spatial lag dependence, heterogeneity as well as cross equation correlation. This is done by utilizing the Kelejian and Prucha (1998) and Lee (2003) type instruments from the cross-section spatial autoregressive literature and marrying them to the error components 3SLS estimator derived by Baltagi (1981) for a system of simultaneous panel data equations. Our Monte Carlo experiments indicate that, for the single equation spatial error components 2SLS estimators, there is a slight gain in efficiency when Lee (2003) type rather than Kelejian and Prucha (1998) instruments are used. However, there is not much difference in efficiency between these instruments for spatial error components 3SLS estimators. Journal: Econometric Reviews Pages: 659-694 Issue: 6-10 Volume: 34 Year: 2015 Month: 12 X-DOI: 10.1080/07474938.2014.956030 File-URL: http://hdl.handle.net/10.1080/07474938.2014.956030 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:34:y:2015:i:6-10:p:659-694 Template-Type: ReDIF-Article 1.0 Author-Name: Zongwu Cai Author-X-Name-First: Zongwu Author-X-Name-Last: Cai Author-Name: Linna Chen Author-X-Name-First: Linna Author-X-Name-Last: Chen Author-Name: Ying Fang Author-X-Name-First: Ying Author-X-Name-Last: Fang Title: Semiparametric Estimation of Partially Varying-Coefficient Dynamic Panel Data Models Abstract: This paper studies a new class of semiparametric dynamic panel data models, in which some of coefficients are allowed to depend on other informative variables and some of the regressors can be endogenous. To estimate both parametric and nonparametric coefficients, a three-stage estimation method is proposed. A nonparametric generalized method of moments (GMM) is adopted to estimate all coefficients firstly and an average method is used to obtain the root-N consistent estimator of parametric coefficients. At the last stage, the estimator of varying coefficients is obtained by the partial residuals. The consistency and asymptotic normality of both estimators are derived. Monte Carlo simulations are conducted to verify the theoretical results and to demonstrate that the proposed estimators perform well in a finite sample. Journal: Econometric Reviews Pages: 695-719 Issue: 6-10 Volume: 34 Year: 2015 Month: 12 X-DOI: 10.1080/07474938.2014.956569 File-URL: http://hdl.handle.net/10.1080/07474938.2014.956569 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:34:y:2015:i:6-10:p:695-719 Template-Type: ReDIF-Article 1.0 Author-Name: Keisuke Hirano Author-X-Name-First: Keisuke Author-X-Name-Last: Hirano Author-Name: Jack R. Porter Author-X-Name-First: Jack R. Author-X-Name-Last: Porter Title: Location Properties of Point Estimators in Linear Instrumental Variables and Related Models Abstract: We examine statistical models, including the workhorse linear instrumental variables model, in which the mapping from the reduced form distribution to the structural parameters of interest is singular. The singularity of this mapping implies certain fundamental restrictions on the finite sample properties of point estimators: they cannot be unbiased, quantile-unbiased, or translation equivariant. The nonexistence of unbiased estimators does not rule out bias reduction of standard estimators, but implies that the bias-variance tradeoff cannot be avoided and needs to be considered carefully. The results can also be extended to weak instrument asymptotics by using the limits of experiments framework. Journal: Econometric Reviews Pages: 720-733 Issue: 6-10 Volume: 34 Year: 2015 Month: 12 X-DOI: 10.1080/07474938.2014.956573 File-URL: http://hdl.handle.net/10.1080/07474938.2014.956573 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:34:y:2015:i:6-10:p:720-733 Template-Type: ReDIF-Article 1.0 Author-Name: Juan Carlos Escanciano Author-X-Name-First: Juan Carlos Author-X-Name-Last: Escanciano Author-Name: Lin Zhu Author-X-Name-First: Lin Author-X-Name-Last: Zhu Title: A Simple Data-Driven Estimator for the Semiparametric Sample Selection Model Abstract: This paper proposes a simple fully data-driven version of Powell's (2001) two-step semiparametric estimator for the sample selection model. The main feature of the proposal is that the bandwidth used to estimate the infinite-dimensional nuisance parameter is chosen by minimizing the mean squared error of the fitted semiparametric model. We formally justify data-driven inference. We introduce the concept of asymptotic normality, uniform in the bandwidth, and show that the proposed estimator achieves this property for a wide range of bandwidths. The method of proof is different from that in Powell (2001) and permits straightforward extensions to other semiparametric or even fully nonparametric specifications of the selection equation. The results of a small Monte Carlo suggest that our estimator has excellent finite sample performance, comparing well with other competing estimators based on alternative choices of smoothing parameters. Journal: Econometric Reviews Pages: 734-762 Issue: 6-10 Volume: 34 Year: 2015 Month: 12 X-DOI: 10.1080/07474938.2014.956577 File-URL: http://hdl.handle.net/10.1080/07474938.2014.956577 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:34:y:2015:i:6-10:p:734-762 Template-Type: ReDIF-Article 1.0 Author-Name: Yan Dong Author-X-Name-First: Yan Author-X-Name-Last: Dong Author-Name: Li Gan Author-X-Name-First: Li Author-X-Name-Last: Gan Author-Name: Yingning Wang Author-X-Name-First: Yingning Author-X-Name-Last: Wang Title: Residential Mobility, Neighborhood Effects, and Educational Attainment of Blacks and Whites Abstract: This paper proposes a new model to identify if and how much the educational attainment gap between blacks and whites is due to the difference in their neighborhoods. In this model, individuals belong to two unobserved types: the endogenous type, which may move in response to the neighborhood effect on their education; or the exogenous type, which may move for reasons unrelated to education. The Heckman sample selection model becomes a special case of the current model in which the probability of one type of individuals is zero. Although we cannot find any significant neighborhood effect in the usual Heckman sample selection model, we do find heterogeneous effects in our two-type model. In particular, there is a substantial neighborhood effect for the movers who belong to the endogenous type. No significant effects exist for other groups. We also find that the endogenous type has more education and moves more often than the exogenous type. On average, we find that the neighborhood variable, the percentage of high school graduates in the neighborhood, accounts for about 28.96% of the education gap between blacks and whites. Journal: Econometric Reviews Pages: 763-798 Issue: 6-10 Volume: 34 Year: 2015 Month: 12 X-DOI: 10.1080/07474938.2014.956586 File-URL: http://hdl.handle.net/10.1080/07474938.2014.956586 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:34:y:2015:i:6-10:p:763-798 Template-Type: ReDIF-Article 1.0 Author-Name: Chunrong Ai Author-X-Name-First: Chunrong Author-X-Name-Last: Ai Author-Name: Meixia Meng Author-X-Name-First: Meixia Author-X-Name-Last: Meng Title: Endogeneity in Semiparametric Panel Binary Choice Model Abstract: In this paper, we study estimation of a semiparametric panel binary choice model with fixed-effects and continuous endogenous regressors. The proposed procedure combines the smoothed maximum score approach with the control function approach and allows for a fixed effect nonparametric first stage regression. Under some sufficient conditions, we show that the proposed estimator for the finite dimensional parameter is consistent and asymptotically normally distributed. A small scale simulation study demonstrates that the proposed procedure has some practical value. Journal: Econometric Reviews Pages: 799-827 Issue: 6-10 Volume: 34 Year: 2015 Month: 12 X-DOI: 10.1080/07474938.2014.956589 File-URL: http://hdl.handle.net/10.1080/07474938.2014.956589 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:34:y:2015:i:6-10:p:799-827 Template-Type: ReDIF-Article 1.0 Author-Name: Yanqin Fan Author-X-Name-First: Yanqin Author-X-Name-Last: Fan Author-Name: Ruixuan Liu Author-X-Name-First: Ruixuan Author-X-Name-Last: Liu Title: Symmetrized Multivariate <italic>k</italic>-NN Estimators Abstract: In this article, we propose a symmetrized multivariate <italic>k</italic>-NN estimator for the conditional mean and for the conditional distribution function. We establish consistency and asymptotic normality of each estimator. For the estimator of the conditional distribution function, we also establish the weak convergence of the conditional empirical process to a Gaussian process. Compared with the corresponding kernel estimators, the asymptotic distributions of our <italic>k</italic>-NN estimators do not depend on the existence of the marginal probability density functions of the covariate vector. A small simulation study compares the finite sample performance of our symmetrized multivariate <italic>k</italic>-NN estimator with the Nadaraya-Watson kernel estimator for the conditional mean. Journal: Econometric Reviews Pages: 828-848 Issue: 6-10 Volume: 34 Year: 2015 Month: 12 X-DOI: 10.1080/07474938.2014.956590 File-URL: http://hdl.handle.net/10.1080/07474938.2014.956590 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:34:y:2015:i:6-10:p:828-848 Template-Type: ReDIF-Article 1.0 Author-Name: Patrick W. Saart Author-X-Name-First: Patrick W. Author-X-Name-Last: Saart Author-Name: Jiti Gao Author-X-Name-First: Jiti Author-X-Name-Last: Gao Author-Name: David E. Allen Author-X-Name-First: David E. Author-X-Name-Last: Allen Title: Semiparametric Autoregressive Conditional Duration Model: Theory and Practice Abstract: Many existing extensions of the Engle and Russell's (1998) Autoregressive Conditional Duration (ACD) model in the literature are aimed at providing additional flexibility either on the dynamics of the conditional duration model or the allowed shape of the hazard function, i.e., its two most essential components. This article introduces an alternative <italic>semiparametric regression approach</italic> to a nonlinear ACD model; the use of a semiparametric functional form on the dynamics of the duration process suggests the model being called the Semiparametric ACD (SEMI-ACD) model. Unlike existing alternatives, the SEMI-ACD model allows simultaneous generalizations on both of the above-mentioned components of the ACD framework. To estimate the model, we establish an alternative use of the existing B�hlmann and McNeil's (2002) iterative estimation algorithm in the semiparametric setting and provide the mathematical proof of its statistical consistency in our context. Furthermore, we investigate the asymptotic properties of the semiparametric estimators employed in order to ensure the statistical rigor of the SEMI-ACD estimation procedure. These asymptotic results are presented in conjunction with simulated examples, which provide an empirical evidence of the SEMI-ACD model's robust finite-sample performance. Finally, we apply the proposed model to study price duration process in the foreign exchange market to illustrate its usefulness in practice. Journal: Econometric Reviews Pages: 849-881 Issue: 6-10 Volume: 34 Year: 2015 Month: 12 X-DOI: 10.1080/07474938.2014.956594 File-URL: http://hdl.handle.net/10.1080/07474938.2014.956594 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:34:y:2015:i:6-10:p:849-881 Template-Type: ReDIF-Article 1.0 Author-Name: Zhongwen Liang Author-X-Name-First: Zhongwen Author-X-Name-Last: Liang Author-Name: Zhongjian Lin Author-X-Name-First: Zhongjian Author-X-Name-Last: Lin Author-Name: Cheng Hsiao Author-X-Name-First: Cheng Author-X-Name-Last: Hsiao Title: Local Linear Estimation of a Nonparametric Cointegration Model Abstract: The nonparametric local linear method has superior properties compared with the local constant method in the independent and weak dependent data setting, see e.g. Fan and Gijbels (1996). Recently, much attention has been drawn to the nonparametric models with nonstationary data. Wang and Phillips (2009a) studied the asymptotic property of a local constant estimator of a nonparametric regression model with a nonstationary I(1) regressor. Sun and Li (2011) show a surprising result that for a semiparamtric varying coefficient model with nonstationary I(1) regressors, the local linear estimator has a faster rate of convergence than the local constant estimator. In this article, we study the asymptotic behavior of the local linear estimator for the same nonparametric regression model as considered by Wang and Phillips (2009a). We focus on the derivation of the joint asymptotic result of both the unknown regression function and its derivative function. We also examine the performance of the local linear estimator with the bandwidth selected by the data driven least squares cross validation (LS-CV) method. Simulation results show that the local linear estimator, coupled with the LS-CV selected bandwidth, enjoys substantial efficiency gains over the local constant estimator. Journal: Econometric Reviews Pages: 882-906 Issue: 6-10 Volume: 34 Year: 2015 Month: 12 X-DOI: 10.1080/07474938.2014.956610 File-URL: http://hdl.handle.net/10.1080/07474938.2014.956610 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:34:y:2015:i:6-10:p:882-906 Template-Type: ReDIF-Article 1.0 Author-Name: Carlos Martins-Filho Author-X-Name-First: Carlos Author-X-Name-Last: Martins-Filho Author-Name: Feng Yao Author-X-Name-First: Feng Author-X-Name-Last: Yao Author-Name: Maximo Torero Author-X-Name-First: Maximo Author-X-Name-Last: Torero Title: High-Order Conditional Quantile Estimation Based on Nonparametric Models of Regression Abstract: We consider the estimation of a high order quantile associated with the conditional distribution of a regressand in a nonparametric regression model. Our estimator is inspired by Pickands (1975) where it is shown that arbitrary distributions which lie in the domain of attraction of an extreme value type have tails that, in the limit, behave as generalized Pareto distributions (GPD). Smith (1987) has studied the asymptotic properties of maximum likelihood (ML) estimators for the parameters of the GPD in this context, but in our paper the relevant random variables used in estimation are standardized residuals from a first stage kernel based nonparametric estimation. We obtain convergence in probability and distribution of the residual based ML estimator for the parameters of the GPD as well as the asymptotic distribution for a suitably defined quantile estimator. A Monte Carlo study provides evidence that our estimator behaves well in finite samples and is easily implementable. Our results have direct application in finance, particularly in the estimation of conditional Value-at-Risk, but other researchers in applied fields such as insurance will also find the results useful. Journal: Econometric Reviews Pages: 907-958 Issue: 6-10 Volume: 34 Year: 2015 Month: 12 X-DOI: 10.1080/07474938.2014.956612 File-URL: http://hdl.handle.net/10.1080/07474938.2014.956612 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:34:y:2015:i:6-10:p:907-958 Template-Type: ReDIF-Article 1.0 Author-Name: Qi Gao Author-X-Name-First: Qi Author-X-Name-Last: Gao Author-Name: Long Liu Author-X-Name-First: Long Author-X-Name-Last: Liu Author-Name: Jeffrey S. Racine Author-X-Name-First: Jeffrey S. Author-X-Name-Last: Racine Title: A Partially Linear Kernel Estimator for Categorical Data Abstract: We extend Robinson's (1988) partially linear estimator to admit the mix of datatypes typically encountered by applied researchers, namely, categorical (nominal and ordinal) and continuous. We also relax the independence assumption that is prevalent in this literature and allow for β-mixing time-series data. We employ Li, Ouyang, and Racine's (2009) categorical and continuous data kernel method, and extend this so that a mix of continuous and/or categorical variables can appear in the nonparametric part of a partially linear time-series model. The estimator appearing in the linear part is shown to be <inline-formula> <inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="lecr_a_956613_o_ilm0001.gif"/> </inline-formula>-consistent, which is of course the case for Robinson's (1988) estimator. Asymptotic normality of the nonparametric component is also established. A modest Monte Carlo simulation demonstrates that the proposed estimator can outperform existing nonparametric, semiparametric, and popular parametric specifications that appear in the literature. An application using Survey of Income and Program Participation (SIPP) data to model a dynamic labor supply function is undertaken that provides a robustness check and demonstrates that the proposed method is capable of outperforming popular parametric specifications that have been used to model this dataset. Journal: Econometric Reviews Pages: 959-978 Issue: 6-10 Volume: 34 Year: 2015 Month: 12 X-DOI: 10.1080/07474938.2014.956613 File-URL: http://hdl.handle.net/10.1080/07474938.2014.956613 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:34:y:2015:i:6-10:p:959-978 Template-Type: ReDIF-Article 1.0 Author-Name: Jingping Gu Author-X-Name-First: Jingping Author-X-Name-Last: Gu Author-Name: Qi Li Author-X-Name-First: Qi Author-X-Name-Last: Li Author-Name: Jui-Chung Yang Author-X-Name-First: Jui-Chung Author-X-Name-Last: Yang Title: Multivariate Local Polynomial Kernel Estimators: Leading Bias and Asymptotic Distribution Abstract: Masry (1996b) provides estimation bias and variance expression for a general local polynomial kernel estimator in a general multivariate regression framework. Under smoother conditions on the unknown regression function and by including more refined approximation terms than that in Masry (1996b), we extend the result of Masry (1996b) to obtain explicit leading bias terms for the whole vector of the local polynomial estimator. Specifically, we derive the leading bias and leading variance terms of nonparametric local polynomial kernel estimator in a general nonparametric multivariate regression model framework. The results can be used to obtain optimal smoothing parameters in local polynomial estimation of the unknown conditional mean function and its derivative functions. Journal: Econometric Reviews Pages: 979-1010 Issue: 6-10 Volume: 34 Year: 2015 Month: 12 X-DOI: 10.1080/07474938.2014.956615 File-URL: http://hdl.handle.net/10.1080/07474938.2014.956615 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:34:y:2015:i:6-10:p:979-1010 Template-Type: ReDIF-Article 1.0 Author-Name: Zaichao Du Author-X-Name-First: Zaichao Author-X-Name-Last: Du Author-Name: Juan Carlos Escanciano Author-X-Name-First: Juan Carlos Author-X-Name-Last: Escanciano Title: A Nonparametric Distribution-Free Test for Serial Independence of Errors Abstract: In this article, we propose a test for the serial independence of unobservable errors in location-scale models. We consider a Hoeffding-Blum-Kiefer-Rosenblat type empirical process applied to residuals, and show that under certain conditions it converges weakly to the same limit as the process based on true errors. We then consider a generalized spectral test applied to estimated residuals, and get a test that is asymptotically distribution-free and powerful against any type of pairwise dependence at all lags. Some Monte Carlo simulations validate our theoretical findings. Journal: Econometric Reviews Pages: 1011-1034 Issue: 6-10 Volume: 34 Year: 2015 Month: 12 X-DOI: 10.1080/07474938.2014.956616 File-URL: http://hdl.handle.net/10.1080/07474938.2014.956616 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:34:y:2015:i:6-10:p:1011-1034 Template-Type: ReDIF-Article 1.0 Author-Name: Peter C. B. Phillips Author-X-Name-First: Peter C. B. Author-X-Name-Last: Phillips Author-Name: Ji Hyung Lee Author-X-Name-First: Ji Hyung Author-X-Name-Last: Lee Title: Limit Theory for VARs with Mixed Roots Near Unity Abstract: Limit theory is developed for nonstationary vector autoregression (VAR) with mixed roots in the vicinity of unity involving persistent and explosive components. Statistical tests for common roots are examined and model selection approaches for discriminating roots are explored. The results are useful in empirical testing for multiple manifestations of nonstationarity - in particular for distinguishing mildly explosive roots from roots that are local to unity and for testing commonality in persistence. Journal: Econometric Reviews Pages: 1035-1056 Issue: 6-10 Volume: 34 Year: 2015 Month: 12 X-DOI: 10.1080/07474938.2014.956617 File-URL: http://hdl.handle.net/10.1080/07474938.2014.956617 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:34:y:2015:i:6-10:p:1035-1056 Template-Type: ReDIF-Article 1.0 Author-Name: Liangjun Su Author-X-Name-First: Liangjun Author-X-Name-Last: Su Author-Name: Yundong Tu Author-X-Name-First: Yundong Author-X-Name-Last: Tu Author-Name: Aman Ullah Author-X-Name-First: Aman Author-X-Name-Last: Ullah Title: Testing Additive Separability of Error Term in Nonparametric Structural Models Abstract: This article considers testing additive error structure in nonparametric structural models, against the alternative hypothesis that the random error term enters the nonparametric model nonadditively. We propose a test statistic under a set of identification conditions considered by Hoderlein et al. (2012), which require the existence of a control variable such that the regressor is independent of the error term given the control variable. The test statistic is motivated from the observation that, under the additive error structure, the partial derivative of the nonparametric structural function with respect to the error term is one under identification. The asymptotic distribution of the test is established, and a bootstrap version is proposed to enhance its finite sample performance. Monte Carlo simulations show that the test has proper size and reasonable power in finite samples. Journal: Econometric Reviews Pages: 1057-1088 Issue: 6-10 Volume: 34 Year: 2015 Month: 12 X-DOI: 10.1080/07474938.2014.956621 File-URL: http://hdl.handle.net/10.1080/07474938.2014.956621 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:34:y:2015:i:6-10:p:1057-1088 Template-Type: ReDIF-Article 1.0 Author-Name: M. Hashem Pesaran Author-X-Name-First: M. Hashem Author-X-Name-Last: Pesaran Title: Testing Weak Cross-Sectional Dependence in Large Panels Abstract: This article considers testing the hypothesis that errors in a panel data model are weakly cross-sectionally dependent, using the exponent of cross-sectional dependence α, introduced recently in Bailey, Kapetanios, and Pesaran (2012). It is shown that the implicit null of the cross-sectional dependence (CD) test depends on the relative expansion rates of <italic>N</italic> and <italic>T</italic>. When <italic>T</italic> = <italic>O</italic>(<italic>N</italic> -super-ε), for some 0 > ε ≤1, then the implicit null of the <italic>CD</italic> test is given by 0 ≤ α > (2  -  ε)/4, which gives 0 ≤ α >1/4, when <italic>N</italic> and <italic>T</italic> tend to infinity at the same rate such that <italic>T</italic>/<italic>N</italic> → κ, with κ being a finite positive constant. It is argued that in the case of large <italic>N</italic> panels, the null of weak dependence is more appropriate than the null of independence which could be quite restrictive for large panels. Using Monte Carlo experiments, it is shown that the <italic>CD</italic> test has the correct size for values of α in the range [0, 1/4], for all combinations of <italic>N</italic> and <italic>T</italic>, and irrespective of whether the panel contains lagged values of the dependent variables, so long as there are no major asymmetries in the error distribution. Journal: Econometric Reviews Pages: 1089-1117 Issue: 6-10 Volume: 34 Year: 2015 Month: 12 X-DOI: 10.1080/07474938.2014.956623 File-URL: http://hdl.handle.net/10.1080/07474938.2014.956623 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:34:y:2015:i:6-10:p:1089-1117 Template-Type: ReDIF-Article 1.0 Author-Name: Dayong Zhang Author-X-Name-First: Dayong Author-X-Name-Last: Zhang Author-Name: Marco R. Barassi Author-X-Name-First: Marco R. Author-X-Name-Last: Barassi Author-Name: Jijun Tan Author-X-Name-First: Jijun Author-X-Name-Last: Tan Title: Residual-Based Tests for Fractional Cointegration: Testing the Term Structure of Interest Rates Abstract: Campbell and Shiller (1987) and Hall et al. (1992) suggest that the term spread of long-term and short-term interest rates should be a stationary I(0) process. However, an empirically nonstationary term spread or rejection of cointegration between long and short term interest rates need not to be considered an empirical rejection of this theoretical relationship. It is likely that the dichotomy between I(1) or I(0) and/or integer values of cointegration are environments which are too restrictive to model the term structure. To overcome this problem, we propose a residual-based approach to test for the null of no cointegration against a fractional alternative which relies on the Exact Local Whittle Estimator (Shimotsu and Philllips, 2005, 2006). We compare its performance to other residual-based tests for fractional cointegration, and then we use it to investigate the term structure in the U.K and the U.S. Journal: Econometric Reviews Pages: 1118-1140 Issue: 6-10 Volume: 34 Year: 2015 Month: 12 X-DOI: 10.1080/07474938.2014.956624 File-URL: http://hdl.handle.net/10.1080/07474938.2014.956624 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:34:y:2015:i:6-10:p:1118-1140 Template-Type: ReDIF-Article 1.0 Author-Name: Serena Ng Author-X-Name-First: Serena Author-X-Name-Last: Ng Title: Constructing Common Factors from Continuous and Categorical Data Abstract: The method of principal components is widely used to estimate common factors in large panels of continuous data. This article first reviews alternative methods that obtain the common factors by solving a Procrustes problem. While these matrix decomposition methods do not specify the probabilistic structure of the data and hence do not permit statistical evaluations of the estimates, they can be extended to analyze categorical data. This involves the additional step of quantifying the ordinal and nominal variables. The article then reviews and explores the numerical properties of these methods. An interesting finding is that the factor space can be quite precisely estimated directly from categorical data without quantification. This may require using a larger number of estimated factors to compensate for the information loss in categorical variables. Separate treatment of categorical and continuous variables may not be necessary if structural interpretation of the factors is not required, such as in forecasting exercises. Journal: Econometric Reviews Pages: 1141-1171 Issue: 6-10 Volume: 34 Year: 2015 Month: 12 X-DOI: 10.1080/07474938.2014.956625 File-URL: http://hdl.handle.net/10.1080/07474938.2014.956625 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:34:y:2015:i:6-10:p:1141-1171 Template-Type: ReDIF-Article 1.0 Author-Name: John W. Galbraith Author-X-Name-First: John W. Author-X-Name-Last: Galbraith Author-Name: Victoria Zinde-Walsh Author-X-Name-First: Victoria Author-X-Name-Last: Zinde-Walsh Author-Name: Jingmei Zhu Author-X-Name-First: Jingmei Author-X-Name-Last: Zhu Title: GARCH Model Estimation Using Estimated Quadratic Variation Abstract: We consider estimates of the parameters of Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models obtained using auxiliary information on latent variance which may be available from higher-frequency data, for example from an estimate of the daily quadratic variation such as the realized variance. We obtain consistent estimators of the parameters of the infinite Autoregressive Conditional Heteroskedasticity (ARCH) representation via a regression using the estimated quadratic variation, without requiring that it be a consistent estimate; that is, variance information containing measurement error can be used for consistent estimation. We obtain GARCH parameters using a minimum distance estimator based on the estimated ARCH parameters. With Least Absolute Deviations (LAD) estimation of the truncated ARCH approximation, we show that consistency and asymptotic normality can be obtained using a general result on LAD estimation in truncated models of infinite-order processes. We provide simulation evidence on small-sample performance for varying numbers of intra-day observations. Journal: Econometric Reviews Pages: 1172-1192 Issue: 6-10 Volume: 34 Year: 2015 Month: 12 X-DOI: 10.1080/07474938.2014.956629 File-URL: http://hdl.handle.net/10.1080/07474938.2014.956629 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:34:y:2015:i:6-10:p:1172-1192 Template-Type: ReDIF-Article 1.0 Author-Name: Esfandiar Maasoumi Author-X-Name-First: Esfandiar Author-X-Name-Last: Maasoumi Title: Special Section on Meritocracy and Assessment of Scholarly Outcomes Journal: Econometric Reviews Pages: 1-1 Issue: 1 Volume: 35 Year: 2016 Month: 1 X-DOI: 10.1080/07474938.2015.1078626 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1078626 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:1:p:1-1 Template-Type: ReDIF-Article 1.0 Author-Name: Peter C. B. Phillips Author-X-Name-First: Peter C. B. Author-X-Name-Last: Phillips Title: Meritocracy Voting: Measuring the Unmeasurable Abstract: Learned societies commonly carry out selection processes to add new fellows to an existing fellowship. Criteria vary across societies but are typically based on subjective judgments concerning the merit of individuals who are nominated for fellowships. These subjective assessments may be made by existing fellows as they vote in elections to determine the new fellows or they may be decided by a selection committee of fellows and officers of the society who determine merit after reviewing nominations and written assessments. Human judgment inevitably plays a central role in these determinations and, notwithstanding its limitations, is usually regarded as being a necessary ingredient in making an overall assessment of qualifications for fellowship. The present article suggests a mechanism by which these merit assessments may be complemented with a quantitative rule that incorporates both subjective and objective elements. The goal of "measuring merit" may be elusive, but quantitative assessment rules can help to widen the effective electorate (for instance, by including the decisions of editors, the judgments of independent referees, and received opinion about research) and mitigate distortions that can arise from cluster effects, invisible college coalition voting, and inner sanctum bias. The rule considered here is designed to assist the selection process by explicitly taking into account subjective assessments of individual candidates for election as well as direct quantitative measures of quality obtained from bibliometric data. Audit methods are suggested to mitigate possible gaming effects by electors in the peer review process. The methodology has application to a wide arena of quality assessment and professional ranking exercises. Some specific issues of implementation are discussed in the context of the Econometric Society fellowship elections. Journal: Econometric Reviews Pages: 2-40 Issue: 1 Volume: 35 Year: 2016 Month: 1 X-DOI: 10.1080/07474938.2014.956633 File-URL: http://hdl.handle.net/10.1080/07474938.2014.956633 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:1:p:2-40 Template-Type: ReDIF-Article 1.0 Author-Name: Peter Schmidt Author-X-Name-First: Peter Author-X-Name-Last: Schmidt Title: Meritocracy Voting: Measuring the Unmeasurable Abstract: This article is a set of comments on "Meritocracy Voting: Measuring the Unmeasurable" by Peter C. B. Phillips. Journal: Econometric Reviews Pages: 41-43 Issue: 1 Volume: 35 Year: 2016 Month: 1 X-DOI: 10.1080/07474938.2015.1078624 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1078624 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:1:p:41-43 Template-Type: ReDIF-Article 1.0 Author-Name: Les Oxley Author-X-Name-First: Les Author-X-Name-Last: Oxley Title: Elites and Secret Handshakes Versus Metrics and Rule-Based Acclamation: A Comment on "Measuring the Unmeasurable" Abstract: In this issue of <italic>Econometric Reviews</italic>, Peter Phillips proposes a quantitative (<italic>objective</italic>) rule that might be used as part of the exercise of measuring merit. In this short comment, I will try and place the need for such a rule (lack of trust and pluralism), potential for adoption (negotiation and power), pros (transparency), and cons (metric failure and loss of institutional memory), within both an historical context and a broader strategic management literature. Ultimately, the adoption of such a rule will depend on its ability to convince the relevant community, via negotiation, that subjective assessments can be appropriately summarized numerically. Rather than argue for objectivity or suggest that numbers are somehow neutral transformations of the real world, it may be advantageous to consider some of the lessons from the critical accounting literature that has focused on the "socially constructed nature" of their numerical systems and techniques. Journal: Econometric Reviews Pages: 44-49 Issue: 1 Volume: 35 Year: 2016 Month: 1 X-DOI: 10.1080/07474938.2014.956638 File-URL: http://hdl.handle.net/10.1080/07474938.2014.956638 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:1:p:44-49 Template-Type: ReDIF-Article 1.0 Author-Name: Chia-Lin Chang Author-X-Name-First: Chia-Lin Author-X-Name-Last: Chang Author-Name: Esfandiar Maasoumi Author-X-Name-First: Esfandiar Author-X-Name-Last: Maasoumi Author-Name: Michael McAleer Author-X-Name-First: Michael Author-X-Name-Last: McAleer Title: Robust Ranking of Journal Quality: An Application to Economics Abstract: The article focuses on the robustness of rankings of academic journal quality and research impact in general, and in economics, in particular, based on the widely-used Thomson Reuters ISI Web of Science citations database (ISI). The article analyzes 299 leading international journals in economics using quantifiable Research Assessment Measures (RAMs), and highlights the similarities and differences in various RAMs, which are based on alternative transformations of citations and influence. All existing RAMs to date have been static, so two new dynamic RAMs are developed to capture changes in impact factor over time and escalating journal self-citations. Alternative RAMs may be calculated annually or updated daily to determine When, Where, and How (frequently) published articles are cited (see Chang et al., 2011a-c). The RAMs are grouped in four distinct classes that include impact factor, mean citations, and non-citations, journal policy, number of high quality articles, journal influence, and article influence. These classes include the most widely used RAMs, namely, the classic 2-year impact factor including journal self-citations (2YIF), 2-year impact factor excluding journal self citations (2YIF*), 5-year impact factor including journal self citations (5YIF), Eigenfactor (or Journal Influence), Article Influence, h-index, and Papers Ignored-By Even The Authors (PI-BETA). As all existing RAMs to date have been static, two new dynamic RAMs are developed to capture changes in impact factor over time (5YD2 = 5YIF/2YIF) and Escalating Self-Citations (ESC). We highlight robust rankings based on the harmonic mean of the ranks of RAMs across the four classes. It is shown that emphasizing the 2YIF of a journal, which partly answers the question as to When published articles are cited, to the exclusion of other informative RAMs, which answer Where and How (frequently) published articles are cited, can lead to a distorted evaluation of journal quality, impact, and influence relative to the harmonic mean of the ranks. Journal: Econometric Reviews Pages: 50-97 Issue: 1 Volume: 35 Year: 2016 Month: 1 X-DOI: 10.1080/07474938.2014.956639 File-URL: http://hdl.handle.net/10.1080/07474938.2014.956639 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:1:p:50-97 Template-Type: ReDIF-Article 1.0 Author-Name: Xiaodong Liu Author-X-Name-First: Xiaodong Author-X-Name-Last: Liu Title: Nonparametric Estimation of Large Auctions with Risk Averse Bidders Abstract: This article studies the robustness of Guerre et al.'s (2000) two-step nonparametric estimation procedure in a first-price, sealed-bid auction with <italic>n</italic> (<italic>n</italic> >> 1) risk averse bidders. Based on an asymptotic approximation with precision of order <italic>O</italic>(<italic>n</italic> -super- - 2) of the intractable equilibrium bidding function, we establish the uniform consistency with rates of convergence of Guerre et al.'s (2000) two-step nonparametric estimator in the presence of risk aversion. Monte Carlo experiments show that the two-step nonparametric estimator performs reasonably well with a moderate number of bidders such as six. Journal: Econometric Reviews Pages: 98-121 Issue: 1 Volume: 35 Year: 2016 Month: 1 X-DOI: 10.1080/07474938.2013.806719 File-URL: http://hdl.handle.net/10.1080/07474938.2013.806719 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:1:p:98-121 Template-Type: ReDIF-Article 1.0 Author-Name: Tom�s del Barrio Castro Author-X-Name-First: Tom�s Author-X-Name-Last: del Barrio Castro Author-Name: Denise R. Osborn Author-X-Name-First: Denise R. Author-X-Name-Last: Osborn Author-Name: A.M. Robert Taylor Author-X-Name-First: A.M. Robert Author-X-Name-Last: Taylor Title: The Performance of Lag Selection and Detrending Methods for HEGY Seasonal Unit Root Tests Abstract: This paper analyzes two key issues for the empirical implementation of parametric seasonal unit root tests, namely generalized least squares (GLS) versus ordinary least squares (OLS) detrending and the selection of the lag augmentation polynomial. Through an extensive Monte Carlo analysis, the performance of a battery of lag selection techniques is analyzed, including a new extension of modified information criteria for the seasonal unit root context. All procedures are applied for both OLS and GLS detrending for a range of data generating processes, also including an examination of hybrid OLS-GLS detrending in conjunction with (seasonal) modified AIC lag selection. An application to quarterly U.S. industrial production indices illustrates the practical implications of choices made. Journal: Econometric Reviews Pages: 122-168 Issue: 1 Volume: 35 Year: 2016 Month: 1 X-DOI: 10.1080/07474938.2013.807710 File-URL: http://hdl.handle.net/10.1080/07474938.2013.807710 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:1:p:122-168 Template-Type: ReDIF-Article 1.0 Author-Name: Heino Bohn Nielsen Author-X-Name-First: Heino Bohn Author-X-Name-Last: Nielsen Title: The Co-Integrated Vector Autoregression with Errors-in-Variables Abstract: The co-integrated vector autoregression is extended to allow variables to be observed with classical measurement errors (ME). For estimation, the model is parametrized as a time invariant state-space form, and an <italic>accelerated</italic> expectation-maximization algorithm is derived. A simulation study shows that <italic>(i)</italic> the finite-sample properties of the maximum likelihood (ML) estimates and reduced rank test statistics are excellent <italic>(ii)</italic> neglected measurement errors will generally distort unit root inference due to a moving average component in the residuals, and <italic>(iii)</italic> the moving average component may-in principle-be approximated by a long autoregression, but a pure autoregression cannot identify the autoregressive structure of the latent process, and the adjustment coefficients are estimated with a substantial asymptotic bias. An application to the zero-coupon yield-curve is given. Journal: Econometric Reviews Pages: 169-200 Issue: 2 Volume: 35 Year: 2016 Month: 2 X-DOI: 10.1080/07474938.2013.806853 File-URL: http://hdl.handle.net/10.1080/07474938.2013.806853 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:2:p:169-200 Template-Type: ReDIF-Article 1.0 Author-Name: Biao Zhang Author-X-Name-First: Biao Author-X-Name-Last: Zhang Title: Empirical Likelihood in Causal Inference Abstract: This paper discusses the estimation of average treatment effects in observational causal inferences. By employing a working propensity score and two working regression models for treatment and control groups, Robins et al. (1994, 1995) introduced the augmented inverse probability weighting (AIPW) method for estimation of average treatment effects, which extends the inverse probability weighting (IPW) method of Horvitz and Thompson (1952); the AIPW estimators are locally efficient and doubly robust. In this paper, we study a hybrid of the empirical likelihood method and the method of moments by employing three estimating functions, which can generate estimators for average treatment effects that are locally efficient and doubly robust. The proposed estimators of average treatment effects are efficient for the given choice of three estimating functions when the working propensity score is correctly specified, and thus are more efficient than the AIPW estimators. In addition, we consider a regression method for estimation of the average treatment effects when working regression models for both the treatment and control groups are correctly specified; the asymptotic variance of the resulting estimator is no greater than the semiparametric variance bound characterized by the theory of Robins et al. (1994, 1995). Finally, we present a simulation study to compare the finite-sample performance of various methods with respect to bias, efficiency, and robustness to model misspecification. Journal: Econometric Reviews Pages: 201-231 Issue: 2 Volume: 35 Year: 2016 Month: 2 X-DOI: 10.1080/07474938.2013.808490 File-URL: http://hdl.handle.net/10.1080/07474938.2013.808490 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:2:p:201-231 Template-Type: ReDIF-Article 1.0 Author-Name: Francesco Audrino Author-X-Name-First: Francesco Author-X-Name-Last: Audrino Author-Name: Fulvio Corsi Author-X-Name-First: Fulvio Author-X-Name-Last: Corsi Author-Name: Kameliya Filipova Author-X-Name-First: Kameliya Author-X-Name-Last: Filipova Title: Bond Risk Premia Forecasting: A Simple Approach for Extracting Macroeconomic Information from a Panel of Indicators Abstract: We propose a simple but effective estimation procedure to extract the level and the volatility dynamics of a latent macroeconomic factor from a panel of observable indicators. Our approach is based on a multivariate conditionally heteroskedastic exact factor model that can take into account the heteroskedasticity feature shown by most macroeconomic variables and relies on an iterated Kalman filter procedure. In simulations we show the unbiasedness of the proposed estimator and its superiority to different approaches introduced in the literature. Simulation results are confirmed in applications to real inflation data with the goal of forecasting long-term bond risk premia. Moreover, we find that the extracted level and conditional variance of the latent factor for inflation are strongly related to NBER business cycles. Journal: Econometric Reviews Pages: 232-256 Issue: 2 Volume: 35 Year: 2016 Month: 2 X-DOI: 10.1080/07474938.2013.833809 File-URL: http://hdl.handle.net/10.1080/07474938.2013.833809 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:2:p:232-256 Template-Type: ReDIF-Article 1.0 Author-Name: Moawia Alghalith Author-X-Name-First: Moawia Author-X-Name-Last: Alghalith Title: Estimating the Stock/Portfolio Volatility and the Volatility of Volatility: A New Simple Method Abstract: We devise a convenient way to estimate stochastic volatility and its volatility. Our method is applicable to both cross-sectional and time series data, and both high-frequency and low-frequency data. Moreover, this method, when applied to cross-sectional data (a collection of risky assets, portfolio), provides a great simplification in the sense that estimating the volatility of the portfolio does not require an estimation of a volatility <italic>matrix</italic> (the volatilities of the individual assets in the portfolio and their correlations). Furthermore, there is no need to generate volatility data. Journal: Econometric Reviews Pages: 257-262 Issue: 2 Volume: 35 Year: 2016 Month: 2 X-DOI: 10.1080/07474938.2014.932144 File-URL: http://hdl.handle.net/10.1080/07474938.2014.932144 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:2:p:257-262 Template-Type: ReDIF-Article 1.0 Author-Name: Frédéric Ferraty Author-X-Name-First: Frédéric Author-X-Name-Last: Ferraty Author-Name: Alejandro Quintela-Del-Río Author-X-Name-First: Alejandro Author-X-Name-Last: Quintela-Del-Río Title: Conditional VAR and Expected Shortfall: A New Functional Approach Abstract: We estimate two well-known risk measures, the value-at-risk (VAR) and the expected shortfall, conditionally to a functional variable (i.e., a random variable valued in some semi(pseudo)-metric space). We use nonparametric kernel estimation for constructing estimators of these quantities, under general dependence conditions. Theoretical properties are stated whereas practical aspects are illustrated on simulated data: nonlinear functional and GARCH(1,1) models. Some ideas on bandwidth selection using bootstrap are introduced. Finally, an empirical example is given through data of the S&P 500 time series. Journal: Econometric Reviews Pages: 263-292 Issue: 2 Volume: 35 Year: 2016 Month: 2 X-DOI: 10.1080/07474938.2013.807107 File-URL: http://hdl.handle.net/10.1080/07474938.2013.807107 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:2:p:263-292 Template-Type: ReDIF-Article 1.0 Author-Name: Sofia Anyfantaki Author-X-Name-First: Sofia Author-X-Name-Last: Anyfantaki Author-Name: Antonis Demos Author-X-Name-First: Antonis Author-X-Name-Last: Demos Title: Estimation and Properties of a Time-Varying EGARCH(1,1) in Mean Model Abstract: Time-varying GARCH-M models are commonly employed in econometrics and financial economics. Yet the recursive nature of the conditional variance makes likelihood analysis of these models computationally infeasible. This article outlines the issues and suggests to employ a Markov chain Monte Carlo algorithm which allows the calculation of a classical estimator via the simulated EM algorithm or a simulated Bayesian solution in only <italic>O</italic>(<italic>T</italic>) computational operations, where <italic>T</italic> is the sample size. Furthermore, the theoretical dynamic properties of a time-varying-parameter EGARCH(1,1)-M are derived. We discuss them and apply the suggested Bayesian estimation to three major stock markets. Journal: Econometric Reviews Pages: 293-310 Issue: 2 Volume: 35 Year: 2016 Month: 2 X-DOI: 10.1080/07474938.2014.966639 File-URL: http://hdl.handle.net/10.1080/07474938.2014.966639 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:2:p:293-310 Template-Type: ReDIF-Article 1.0 Author-Name: Koji Miyawaki Author-X-Name-First: Koji Author-X-Name-Last: Miyawaki Author-Name: Yasuhiro Omori Author-X-Name-First: Yasuhiro Author-X-Name-Last: Omori Author-Name: Akira Hibiki Author-X-Name-First: Akira Author-X-Name-Last: Hibiki Title: Exact Estimation of Demand Functions under Block-Rate Pricing Abstract: This article proposes an exact estimation of demand functions under block-rate pricing by focusing on increasing block-rate pricing. This is the first study that explicitly considers the separability condition which has been ignored in previous literature. Under this pricing structure, the price changes when consumption exceeds a certain threshold and the consumer faces a utility maximization problem subject to a piecewise-linear budget constraint. Solving this maximization problem leads to a statistical model in which model parameters are strongly restricted by the separability condition. In this article, by taking a hierarchical Bayesian approach, we implement a Markov chain Monte Carlo simulation to properly estimate the demand function. We find, however, that the convergence of the distribution of simulated samples to the posterior distribution is slow, requiring an additional scale transformation step for parameters to the Gibbs sampler. These proposed methods are then applied to estimate the Japanese residential water demand function. Journal: Econometric Reviews Pages: 311-343 Issue: 3 Volume: 35 Year: 2016 Month: 3 X-DOI: 10.1080/07474938.2013.806857 File-URL: http://hdl.handle.net/10.1080/07474938.2013.806857 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:3:p:311-343 Template-Type: ReDIF-Article 1.0 Author-Name: Alain Guay Author-X-Name-First: Alain Author-X-Name-Last: Guay Author-Name: Florian Pelgrin Author-X-Name-First: Florian Author-X-Name-Last: Pelgrin Title: Using Implied Probabilities to Improve the Estimation of Unconditional Moment Restrictions for Weakly Dependent Data Abstract: In this article, we investigate the use of implied probabilities (Back and Brown, 1993) to improve estimation in unconditional moment conditions models. Using the seminal contributions of Bonnal and Renault (2001) and Antoine et al. (2007), we propose two three-step Euclidian empirical likelihood (3S-EEL) estimators for weakly dependent data. Both estimators make use of a control variates principle that can be interpreted in terms of implied probabilities in order to achieve higher-order improvements relative to the traditional two-step GMM estimator. A Monte Carlo study reveals that the finite and large sample properties of the three-step estimators compare favorably to the existing approaches: the two-step GMM and the continuous updating estimator. Journal: Econometric Reviews Pages: 344-372 Issue: 3 Volume: 35 Year: 2016 Month: 3 X-DOI: 10.1080/07474938.2014.966630 File-URL: http://hdl.handle.net/10.1080/07474938.2014.966630 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:3:p:344-372 Template-Type: ReDIF-Article 1.0 Author-Name: Tommaso Proietti Author-X-Name-First: Tommaso Author-X-Name-Last: Proietti Title: The Multistep Beveridge--Nelson Decomposition Abstract: The Beveridge--Nelson decomposition defines the trend component in terms of the eventual forecast function, as the value the series would take if it were on its long-run path. The article introduces the multistep Beveridge--Nelson decomposition, which arises when the forecast function is obtained by the direct autoregressive approach, which optimizes the predictive ability of the AR model at forecast horizons greater than one. We compare our proposal with the standard Beveridge--Nelson decomposition, for which the forecast function is obtained by iterating the one-step-ahead predictions via the chain rule. We illustrate that the multistep Beveridge--Nelson trend is more efficient than the standard one in the presence of model misspecification, and we subsequently assess the predictive validity of the extracted transitory component with respect to future growth. Journal: Econometric Reviews Pages: 373-395 Issue: 3 Volume: 35 Year: 2016 Month: 3 X-DOI: 10.1080/07474938.2014.966631 File-URL: http://hdl.handle.net/10.1080/07474938.2014.966631 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:3:p:373-395 Template-Type: ReDIF-Article 1.0 Author-Name: Joakim Westerlund Author-X-Name-First: Joakim Author-X-Name-Last: Westerlund Title: Pooled Panel Unit Root Tests and the Effect of Past Initialization Abstract: This paper analyzes the role of initialization when testing for a unit root in panel data, an issue that has received surprisingly little attention in the literature. In fact, most studies assume that the initial value is either zero or bounded. As a response to this, the current paper considers a model in which the initialization is in the past, which is shown to have several distinctive features that makes it attractive, even in comparison to the common time series practice of making the initial value a draw from its unconditional distribution under the stationary alternative. The results have implications not only for theory, but also for applied work. In particular, and in contrast to the time series case, in panels the effect of the initialization need not be negative but can actually lead to improved test performance. Journal: Econometric Reviews Pages: 396-427 Issue: 3 Volume: 35 Year: 2016 Month: 3 X-DOI: 10.1080/07474938.2013.833829 File-URL: http://hdl.handle.net/10.1080/07474938.2013.833829 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:3:p:396-427 Template-Type: ReDIF-Article 1.0 Author-Name: Gerdie Everaert Author-X-Name-First: Gerdie Author-X-Name-Last: Everaert Author-Name: Tom De Groote Author-X-Name-First: Tom Author-X-Name-Last: De Groote Title: Common Correlated Effects Estimation of Dynamic Panels with Cross-Sectional Dependence Abstract: We derive inconsistency expressions for dynamic panel data estimators under error cross-sectional dependence generated by an unobserved common factor in both the fixed effect and the incidental trends case. We show that for a temporally dependent factor, the standard within groups (WG) estimator is inconsistent even as both <italic>N</italic> and <italic>T</italic> tend to infinity. Next we investigate the properties of the common correlated effects pooled (CCEP) estimator of Pesaran (2006) which eliminates the error cross-sectional dependence using cross-sectional averages of the data. In contrast to the static case, the CCEP estimator is only consistent when next to <italic>N</italic> also <italic>T</italic> tends to infinity. It is shown that for the most relevant parameter settings, the inconsistency of the CCEP estimator is larger than that of the infeasible WG estimator, which includes the common factors as regressors. Restricting the CCEP estimator results in a somewhat smaller inconsistency. The small sample properties of the various estimators are analyzed using Monte Carlo experiments. The simulation results suggest that the CCEP estimator can be used to estimate dynamic panel data models provided <italic>T</italic> is not too small. The size of <italic>N</italic> is of less importance. Journal: Econometric Reviews Pages: 428-463 Issue: 3 Volume: 35 Year: 2016 Month: 3 X-DOI: 10.1080/07474938.2014.966635 File-URL: http://hdl.handle.net/10.1080/07474938.2014.966635 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:3:p:428-463 Template-Type: ReDIF-Article 1.0 Author-Name: Prosper Dovonon Author-X-Name-First: Prosper Author-X-Name-Last: Dovonon Title: Large Sample Properties of the Three-Step Euclidean Likelihood Estimators under Model Misspecification Abstract: This article studies the three-step Euclidean likelihood (3S) estimator and its corrected version as proposed by Antoine et al. (2007) in globally misspecified models. We establish that the 3S estimator stays <inline-formula><inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="lecr_a_966634_ilm0001.gif"/></inline-formula>-convergent and asymptotically Gaussian. The discontinuity in the shrinkage factor makes the analysis of the corrected-3S estimator harder to carry out in misspecified models. We propose a slight modification to this factor to control its rate of divergence in case of misspecification. We show that the resulting modified-3S estimator is also higher order equivalent to the maximum empirical likelihood (EL) estimator in well-specified models and <inline-formula><inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="lecr_a_966634_ilm0001.gif"/></inline-formula>-convergent and asymptotically Gaussian in misspecified models. Its asymptotic distribution robust to misspecification is also provided. Because of these properties, both the 3S and the modified-3S estimators could be considered as computationally attractive alternatives to the exponentially tilted empirical likelihood estimator proposed by Schennach (2007) which also is higher order equivalent to EL in well-specified models and <inline-formula><inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="lecr_a_966634_ilm0001.gif"/></inline-formula>-convergent in misspecified models. Journal: Econometric Reviews Pages: 465-514 Issue: 4 Volume: 35 Year: 2016 Month: 4 X-DOI: 10.1080/07474938.2014.966634 File-URL: http://hdl.handle.net/10.1080/07474938.2014.966634 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:4:p:465-514 Template-Type: ReDIF-Article 1.0 Author-Name: José M. R. Murteira Author-X-Name-First: José M. R. Author-X-Name-Last: Murteira Author-Name: Joaquim J. S. Ramalho Author-X-Name-First: Joaquim J. S. Author-X-Name-Last: Ramalho Title: Regression Analysis of Multivariate Fractional Data Abstract: The present article discusses alternative regression models and estimation methods for dealing with multivariate fractional response variables. Both conditional mean models, estimable by quasi-maximum likelihood, and fully parametric models (Dirichlet and Dirichlet-multinomial), estimable by maximum likelihood, are considered. A new parameterization is proposed for the parametric models, which accommodates the most common specifications for the conditional mean (e.g., multinomial logit, nested logit, random parameters logit, dogit). The text also discusses at some length the specification analysis of fractional regression models, proposing several tests that can be performed through artificial regressions. Finally, an extensive Monte Carlo study evaluates the finite sample properties of most of the estimators and tests considered. Journal: Econometric Reviews Pages: 515-552 Issue: 4 Volume: 35 Year: 2016 Month: 4 X-DOI: 10.1080/07474938.2013.806849 File-URL: http://hdl.handle.net/10.1080/07474938.2013.806849 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:4:p:515-552 Template-Type: ReDIF-Article 1.0 Author-Name: Stephen G. Donald Author-X-Name-First: Stephen G. Author-X-Name-Last: Donald Author-Name: Yu-Chin Hsu Author-X-Name-First: Yu-Chin Author-X-Name-Last: Hsu Title: Improving the Power of Tests of Stochastic Dominance Abstract: We extend Hansen's (2005) recentering method to a continuum of inequality constraints to construct new Kolmogorov--Smirnov tests for stochastic dominance of any pre-specified order. We show that our tests have correct size asymptotically, are consistent against fixed alternatives and are unbiased against some <italic>N</italic>-super-−1/2 local alternatives. It is shown that by avoiding the use of the least favorable configuration, our tests are less conservative and more powerful than Barrett and Donald's (2003) and in some simulation examples we consider, we find that our tests can be more powerful than the subsampling test of Linton et al. (2005). We apply our method to test stochastic dominance relations between Canadian income distributions in 1978 and 1986 as considered in Barrett and Donald (2003) and find that some of the hypothesis testing results are different using the new method. Journal: Econometric Reviews Pages: 553-585 Issue: 4 Volume: 35 Year: 2016 Month: 4 X-DOI: 10.1080/07474938.2013.833813 File-URL: http://hdl.handle.net/10.1080/07474938.2013.833813 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:4:p:553-585 Template-Type: ReDIF-Article 1.0 Author-Name: Ping Yu Author-X-Name-First: Ping Author-X-Name-Last: Yu Title: Understanding Estimators of Treatment Effects in Regression Discontinuity Designs Abstract: In this paper, we propose two new estimators of treatment effects in regression discontinuity designs. These estimators can aid understanding of the existing estimators such as the local polynomial estimator and the partially linear estimator. The first estimator is the partially polynomial estimator which extends the partially linear estimator by further incorporating derivative differences of the conditional mean of the outcome on the two sides of the discontinuity point. This estimator is related to the local polynomial estimator by a relocalization effect. Unlike the partially linear estimator, this estimator can achieve the optimal rate of convergence even under broader regularity conditions. The second estimator is an instrumental variable estimator in the fuzzy design. This estimator will reduce to the local polynomial estimator if higher order endogeneities are neglected. We study the asymptotic properties of these two estimators and conduct simulation studies to confirm the theoretical analysis. Journal: Econometric Reviews Pages: 586-637 Issue: 4 Volume: 35 Year: 2016 Month: 4 X-DOI: 10.1080/07474938.2013.833831 File-URL: http://hdl.handle.net/10.1080/07474938.2013.833831 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:4:p:586-637 Template-Type: ReDIF-Article 1.0 Author-Name: Badi H. Baltagi Author-X-Name-First: Badi H. Author-X-Name-Last: Baltagi Author-Name: Long Liu Author-X-Name-First: Long Author-X-Name-Last: Liu Title: Random Effects, Fixed Effects and Hausman's Test for the Generalized Mixed Regressive Spatial Autoregressive Panel Data Model Abstract: This article suggests random and fixed effects spatial two-stage least squares estimators for the generalized mixed regressive spatial autoregressive panel data model. This extends the generalized spatial panel model of Baltagi et al. (2013) by the inclusion of a spatial lag term. The estimation method utilizes the Generalized Moments method suggested by Kapoor et al. (2007) for a spatial autoregressive panel data model. We derive the asymptotic distributions of these estimators and suggest a Hausman test a la Mutl and Pfaffermayr (2011) based on the difference between these estimators. Monte Carlo experiments are performed to investigate the performance of these estimators as well as the corresponding Hausman test. Journal: Econometric Reviews Pages: 638-658 Issue: 4 Volume: 35 Year: 2016 Month: 4 X-DOI: 10.1080/07474938.2014.998148 File-URL: http://hdl.handle.net/10.1080/07474938.2014.998148 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:4:p:638-658 Template-Type: ReDIF-Article 1.0 Author-Name: G. Mesters Author-X-Name-First: G. Author-X-Name-Last: Mesters Author-Name: S. J. Koopman Author-X-Name-First: S. J. Author-X-Name-Last: Koopman Author-Name: M. Ooms Author-X-Name-First: M. Author-X-Name-Last: Ooms Title: Monte Carlo Maximum Likelihood Estimation for Generalized Long-Memory Time Series Models Abstract: An exact maximum likelihood method is developed for the estimation of parameters in a non-Gaussian nonlinear density function that depends on a latent Gaussian dynamic process with long-memory properties. Our method relies on the method of importance sampling and on a linear Gaussian approximating model from which the latent process can be simulated. Given the presence of a latent long-memory process, we require a modification of the importance sampling technique. In particular, the long-memory process needs to be approximated by a finite dynamic linear process. Two possible approximations are discussed and are compared with each other. We show that an autoregression obtained from minimizing mean squared prediction errors leads to an effective and feasible method. In our empirical study, we analyze ten daily log-return series from the S&P 500 stock index by univariate and multivariate long-memory stochastic volatility models. We compare the in-sample and out-of-sample performance of a number of models within the class of long-memory stochastic volatility models. Journal: Econometric Reviews Pages: 659-687 Issue: 4 Volume: 35 Year: 2016 Month: 4 X-DOI: 10.1080/07474938.2015.1031014 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1031014 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:4:p:659-687 Template-Type: ReDIF-Article 1.0 Author-Name: Florian Heiss Author-X-Name-First: Florian Author-X-Name-Last: Heiss Title: Discrete Choice Methods with Simulation Journal: Econometric Reviews Pages: 688-692 Issue: 4 Volume: 35 Year: 2016 Month: 4 X-DOI: 10.1080/07474938.2014.975634 File-URL: http://hdl.handle.net/10.1080/07474938.2014.975634 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:4:p:688-692 Template-Type: ReDIF-Article 1.0 Author-Name: Sadat Reza Author-X-Name-First: Sadat Author-X-Name-Last: Reza Author-Name: Paul Rilstone Author-X-Name-First: Paul Author-X-Name-Last: Rilstone Title: Semiparametric Efficiency Bounds and Efficient Estimation of Discrete Duration Models with Unspecified Hazard Rate Abstract: We consider semiparametric estimation of discrete duration models whose hazard rate can be characterized as an unknown transformation of a parametric index of the observable covariates and elapsed spell length. The information matrix is derived. In the case of separable duration dependence the information matrix for the parameters of the index is singular. In that situation, the information matrix for the regression component of the hazard function is derived. The information matrix is also singular when individual--specific/time--invariant unobserved errors are introduced. We develop <inline-formula><inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="lecr_a_966637_ilm0001.gif"/></inline-formula>--consistent estimators for those instances when the information matrix is nonsingular. Less--than--<inline-formula><inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="lecr_a_966637_ilm0001.gif"/></inline-formula>--consistent estimators of the duration dependence component of the hazard rate of the separable model are developed. Simulations and an application to strike durations illustrate the viability of the approach. Journal: Econometric Reviews Pages: 693-726 Issue: 5 Volume: 35 Year: 2016 Month: 5 X-DOI: 10.1080/07474938.2014.966637 File-URL: http://hdl.handle.net/10.1080/07474938.2014.966637 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:5:p:693-726 Template-Type: ReDIF-Article 1.0 Author-Name: Helmut Herwartz Author-X-Name-First: Helmut Author-X-Name-Last: Herwartz Author-Name: Florian Siedenburg Author-X-Name-First: Florian Author-X-Name-Last: Siedenburg Author-Name: Yabibal M. Walle Author-X-Name-First: Yabibal M. Author-X-Name-Last: Walle Title: Heteroskedasticity Robust Panel Unit Root Testing Under Variance Breaks in Pooled Regressions Abstract: Noting that many economic variables display occasional shifts in their second order moments, we investigate the performance of homogenous panel unit root tests in the presence of permanent volatility shifts. It is shown that in this case the test statistic proposed by Herwartz and Siedenburg (2008) is asymptotically standard Gaussian. By means of a simulation study we illustrate the performance of first and second generation panel unit root tests and undertake a more detailed comparison of the test in Herwartz and Siedenburg (2008) and its heteroskedasticity consistent Cauchy counterpart introduced in Demetrescu and Hanck (2012a). As an empirical illustration, we reassess evidence on the Fisher hypothesis with data from nine countries over the period 1961Q2--2011Q2. Empirical evidence supports panel stationarity of the real interest rate for the entire subperiod. With regard to the most recent two decades, the test results cast doubts on market integration, since the real interest rate is diagnosed nonstationary. Journal: Econometric Reviews Pages: 727-750 Issue: 5 Volume: 35 Year: 2016 Month: 5 X-DOI: 10.1080/07474938.2014.966638 File-URL: http://hdl.handle.net/10.1080/07474938.2014.966638 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:5:p:727-750 Template-Type: ReDIF-Article 1.0 Author-Name: Matei Demetrescu Author-X-Name-First: Matei Author-X-Name-Last: Demetrescu Author-Name: Christoph Hanck Author-X-Name-First: Christoph Author-X-Name-Last: Hanck Title: Robust Inference for Near-Unit Root Processes with Time-Varying Error Variances Abstract: The autoregressive Cauchy estimator uses the sign of the first lag as instrumental variable (IV); under independent and identically distributed (i.i.d.) errors, the resulting IV <italic>t</italic>-type statistic is known to have a standard normal limiting distribution in the unit root case. With unconditional heteroskedasticity, the ordinary least squares (OLS) <italic>t</italic> statistic is affected in the unit root case; but the paper shows that, by using some nonlinear transformation behaving asymptotically like the sign as instrument, limiting normality of the IV <italic>t</italic>-type statistic is maintained when the series to be tested has no deterministic trends. Neither estimation of the so-called variance profile nor bootstrap procedures are required to this end. The Cauchy unit root test has power in the same 1/<italic>T</italic> neighborhoods as the usual unit root tests, also for a wide range of magnitudes for the initial value. It is furthermore shown to be competitive with other, bootstrap-based, robust tests. When the series exhibit a linear trend, however, the null distribution of the Cauchy test for a unit root becomes nonstandard, reminiscent of the Dickey-Fuller distribution. In this case, inference robust to nonstationary volatility is obtained via the wild bootstrap. Journal: Econometric Reviews Pages: 751-781 Issue: 5 Volume: 35 Year: 2016 Month: 5 X-DOI: 10.1080/07474938.2014.976525 File-URL: http://hdl.handle.net/10.1080/07474938.2014.976525 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:5:p:751-781 Template-Type: ReDIF-Article 1.0 Author-Name: Pierre Perron Author-X-Name-First: Pierre Author-X-Name-Last: Perron Author-Name: Yohei Yamamoto Author-X-Name-First: Yohei Author-X-Name-Last: Yamamoto Title: On the Usefulness or Lack Thereof of Optimality Criteria for Structural Change Tests Abstract: Elliott and Müller (2006) considered the problem of testing for general types of parameter variations, including infrequent breaks. They developed a framework that yields optimal tests, in the sense that they nearly attain some local Gaussian power envelop. The main ingredient in their setup is that the variance of the process generating the changes in the parameters must go to zero at a fast rate. They recommended the so-called <italic>qL̂L</italic> test, a partial sums type test based on the residuals obtained from the restricted model. We show that for breaks that are very small, its power is indeed higher than other tests, including the popular sup-Wald (SW) test. However, the differences are very minor. When the magnitude of change is moderate to large, the power of the test is very low in the context of a regression with lagged dependent variables or when a correction is applied to account for serial correlation in the errors. In many cases, the power goes to zero as the magnitude of change increases. The power of the SW test does not show this non-monotonicity and its power is far superior to the <italic>qL̂L</italic> test when the break is not very small. We claim that the optimality of the <italic>qL̂L</italic> test does not come from the properties of the test statistics but the criterion adopted, which is not useful to analyze structural change tests. Instead, we use fixed-break size asymptotic approximations to assess the relative efficiency or power of the two tests. When doing so, it is shown that the SW test indeed dominates the <italic>qL̂L</italic> test and, in many cases, the latter has zero relative asymptotic efficiency. Journal: Econometric Reviews Pages: 782-844 Issue: 5 Volume: 35 Year: 2016 Month: 5 X-DOI: 10.1080/07474938.2014.977621 File-URL: http://hdl.handle.net/10.1080/07474938.2014.977621 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:5:p:782-844 Template-Type: ReDIF-Article 1.0 Author-Name: Joakim Westerlund Author-X-Name-First: Joakim Author-X-Name-Last: Westerlund Author-Name: Mehdi Hosseinkouchack Author-X-Name-First: Mehdi Author-X-Name-Last: Hosseinkouchack Author-Name: Martin Solberger Author-X-Name-First: Martin Author-X-Name-Last: Solberger Title: The Local Power of the CADF and CIPS Panel Unit Root Tests Abstract: Very little is known about the local power of second generation panel unit root tests that are robust to cross-section dependence. This article derives the local asymptotic power functions of the cross-section argumented Dickey--Fuller Cross-section Augmented Dickey-Fuller (CADF) and CIPS tests of Pesaran (2007), which are among the most popular tests around. Journal: Econometric Reviews Pages: 845-870 Issue: 5 Volume: 35 Year: 2016 Month: 5 X-DOI: 10.1080/07474938.2014.977077 File-URL: http://hdl.handle.net/10.1080/07474938.2014.977077 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:5:p:845-870 Template-Type: ReDIF-Article 1.0 Author-Name: Efthymios G. Tsionas Author-X-Name-First: Efthymios G. Author-X-Name-Last: Tsionas Author-Name: Kien C. Tran Author-X-Name-First: Kien C. Author-X-Name-Last: Tran Title: On the Joint Estimation of Heterogeneous Technologies, Technical, and Allocative Inefficiency Abstract: In this article, we provide a semiparametric approach to the joint measurement of technical and allocative inefficiency in a way that the internal consistency of the specification of allocative errors in the objective function (e.g., cost function) and the derivative equations (e.g., share or input demand functions) is assured. We start from the Cobb--Douglas production and shadow cost system. We show that the shadow cost system has a closed-form likelihood function contrary to what was previously thought. In turn, we use the method of local maximum likelihood applied to a system of equations to obtain firm-specific parameter estimates (which reveal heterogeneity in production) as well as measures of technical and allocative inefficiency and its cost. We illustrate its practical application using data on U.S. electric utilities. Journal: Econometric Reviews Pages: 871-893 Issue: 5 Volume: 35 Year: 2016 Month: 5 X-DOI: 10.1080/07474938.2014.975635 File-URL: http://hdl.handle.net/10.1080/07474938.2014.975635 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:5:p:871-893 Template-Type: ReDIF-Article 1.0 Author-Name: Alan T. K. Wan Author-X-Name-First: Alan T. K. Author-X-Name-Last: Wan Author-Name: Jinhong You Author-X-Name-First: Jinhong Author-X-Name-Last: You Author-Name: Riquan Zhang Author-X-Name-First: Riquan Author-X-Name-Last: Zhang Title: A Seemingly Unrelated Nonparametric Additive Model with Autoregressive Errors Abstract: This article considers a nonparametric additive seemingly unrelated regression model with autoregressive errors, and develops estimation and inference procedures for this model. Our proposed method first estimates the unknown functions by combining polynomial spline series approximations with least squares, and then uses the fitted residuals together with the smoothly clipped absolute deviation (SCAD) penalty to identify the error structure and estimate the unknown autoregressive coefficients. Based on the polynomial spline series estimator and the fitted error structure, a two-stage local polynomial improved estimator for the unknown functions of the mean is further developed. Our procedure applies a prewhitening transformation of the dependent variable, and also takes into account the contemporaneous correlations across equations. We show that the resulting estimator possesses an oracle property, and is asymptotically more efficient than estimators that neglect the autocorrelation and/or contemporaneous correlations of errors. We investigate the small sample properties of the proposed procedure in a simulation study. Journal: Econometric Reviews Pages: 894-928 Issue: 5 Volume: 35 Year: 2016 Month: 5 X-DOI: 10.1080/07474938.2014.998149 File-URL: http://hdl.handle.net/10.1080/07474938.2014.998149 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:5:p:894-928 Template-Type: ReDIF-Article 1.0 Author-Name: Álvaro Cartea Author-X-Name-First: Álvaro Author-X-Name-Last: Cartea Author-Name: Dimitrios Karyampas Author-X-Name-First: Dimitrios Author-X-Name-Last: Karyampas Title: The Relationship between the Volatility of Returns and the Number of Jumps in Financial Markets Abstract: We propose a methodology to employ high frequency financial data to obtain estimates of volatility of log-prices which are not affected by microstructure noise and Lévy jumps. We introduce the “number of jumps” as a variable to explain and predict volatility and show that the number of jumps in SPY prices is an important variable to explain the daily volatility of the SPY log-returns, has more explanatory power than other variables (e.g., high and low, open and close), and has a similar explanatory power to that of the VIX. Finally, the number of jumps is very useful to forecast volatility and contains information that is not impounded in the VIX. Journal: Econometric Reviews Pages: 929-950 Issue: 6 Volume: 35 Year: 2016 Month: 6 X-DOI: 10.1080/07474938.2014.976529 File-URL: http://hdl.handle.net/10.1080/07474938.2014.976529 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:6:p:929-950 Template-Type: ReDIF-Article 1.0 Author-Name: George Kapetanios Author-X-Name-First: George Author-X-Name-Last: Kapetanios Author-Name: Zacharias Psaradakis Author-X-Name-First: Zacharias Author-X-Name-Last: Psaradakis Title: Semiparametric Sieve-Type Generalized Least Squares Inference Abstract: This article considers the problem of statistical inference in linear regression models with dependent errors. A sieve-type generalized least squares (GLS) procedure is proposed based on an autoregressive approximation to the generating mechanism of the errors. The asymptotic properties of the sieve-type GLS estimator are established under general conditions, including mixingale-type conditions as well as conditions which allow for long-range dependence in the stochastic regressors and/or the errors. A Monte Carlo study examines the finite-sample properties of the method for testing regression hypotheses. Journal: Econometric Reviews Pages: 951-985 Issue: 6 Volume: 35 Year: 2016 Month: 6 X-DOI: 10.1080/07474938.2014.975639 File-URL: http://hdl.handle.net/10.1080/07474938.2014.975639 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:6:p:951-985 Template-Type: ReDIF-Article 1.0 Author-Name: Aaron D. Smallwood Author-X-Name-First: Aaron D. Author-X-Name-Last: Smallwood Title: A Monte Carlo Investigation of Unit Root Tests and Long Memory in Detecting Mean Reversion in I(0) Regime Switching, Structural Break, and Nonlinear Data Abstract: The potential observational equivalence between various types of nonlinearity and long memory has been recognized by the econometrics community since at least the contribution of Diebold and Inoue (2001). A large literature has developed in an attempt to ascertain whether or not the long memory finding in many economic series is spurious. Yet to date, no study has analyzed the consequences of using long memory methods to test for unit roots when the “truth” derives from regime switching, structural breaks, or other types of mean reverting nonlinearity. In this article, I conduct a comprehensive Monte Carlo analysis to investigate the consequences of using tests designed to have power against fractional integration when the actual data generating process is unknown. I additionally consider the use of tests designed to have power against breaks and threshold nonlinearity. The findings are compelling and demonstrate that the use of long memory as an approximation to nonlinearity yields tests with relatively high power. In contrast, misspecification has severe consequences for tests designed to have power against threshold nonlinearity, and especially for tests designed to have power against breaks. Journal: Econometric Reviews Pages: 986-1012 Issue: 6 Volume: 35 Year: 2016 Month: 6 X-DOI: 10.1080/07474938.2014.976526 File-URL: http://hdl.handle.net/10.1080/07474938.2014.976526 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:6:p:986-1012 Template-Type: ReDIF-Article 1.0 Author-Name: Hendrik Wolff Author-X-Name-First: Hendrik Author-X-Name-Last: Wolff Title: Imposing and Testing for Shape Restrictions in Flexible Parametric Models Abstract: In many economic models, theory restricts the shape of functions, such as monotonicity or curvature conditions. This article reviews and presents a framework for constrained estimation and inference to test for shape conditions in parametric models. We show that “regional” shape-restricting estimators have important advantages in terms of model fit and flexibility (as opposed to standard “local” or “global” shape-restricting estimators). In our empirical illustration, this is the first article to impose and test for all shape restrictions required by economic theory simultaneously in the “Berndt and Wood” data. We find that this dataset is consistent with “duality theory,” whereas previous studies have found violations of economic theory. We discuss policy consequences for key parameters, such as whether energy and capital are complements or substitutes. Journal: Econometric Reviews Pages: 1013-1039 Issue: 6 Volume: 35 Year: 2016 Month: 6 X-DOI: 10.1080/07474938.2014.975637 File-URL: http://hdl.handle.net/10.1080/07474938.2014.975637 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:6:p:1013-1039 Template-Type: ReDIF-Article 1.0 Author-Name: Jan R. Magnus Author-X-Name-First: Jan R. Author-X-Name-Last: Magnus Author-Name: Wendun Wang Author-X-Name-First: Wendun Author-X-Name-Last: Wang Author-Name: Xinyu Zhang Author-X-Name-First: Xinyu Author-X-Name-Last: Zhang Title: Weighted-Average Least Squares Prediction Abstract: Prediction under model uncertainty is an important and difficult issue. Traditional prediction methods (such as pretesting) are based on model selection followed by prediction in the selected model, but the reported prediction and the reported prediction variance ignore the uncertainty from the selection procedure. This article proposes a weighted-average least squares (WALS) prediction procedure that is not conditional on the selected model. Taking both model and error uncertainty into account, we also propose an appropriate estimate of the variance of the WALS predictor. Correlations among the random errors are explicitly allowed. Compared to other prediction averaging methods, the WALS predictor has important advantages both theoretically and computationally. Simulation studies show that the WALS predictor generally produces lower mean squared prediction errors than its competitors, and that the proposed estimator for the prediction variance performs particularly well when model uncertainty increases. Journal: Econometric Reviews Pages: 1040-1074 Issue: 6 Volume: 35 Year: 2016 Month: 6 X-DOI: 10.1080/07474938.2014.977065 File-URL: http://hdl.handle.net/10.1080/07474938.2014.977065 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:6:p:1040-1074 Template-Type: ReDIF-Article 1.0 Author-Name: Gerard J. van den Berg Author-X-Name-First: Gerard J. Author-X-Name-Last: van den Berg Author-Name: Bettina Drepper Author-X-Name-First: Bettina Author-X-Name-Last: Drepper Title: Inference for Shared-Frailty Survival Models with Left-Truncated Data Abstract: Shared-frailty survival models specify that systematic unobserved determinants of duration outcomes are identical within groups of individuals. We consider random-effects likelihood-based statistical inference if the duration data are subject to left-truncation. Such inference with left-truncated data can be performed in previous versions of the Stata software package for parametric and semi-parametric shared frailty models. We show that with left-truncated data, the commands ignore the weeding-out process before the left-truncation points, affecting the distribution of unobserved determinants among group members in the data, namely among the group members who survive until their truncation points. We critically examine studies in the statistical literature on this issue as well as published empirical studies that use the commands. Simulations illustrate the size of the (asymptotic) bias and its dependence on the degree of truncation. Journal: Econometric Reviews Pages: 1075-1098 Issue: 6 Volume: 35 Year: 2016 Month: 6 X-DOI: 10.1080/07474938.2014.975640 File-URL: http://hdl.handle.net/10.1080/07474938.2014.975640 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:6:p:1075-1098 Template-Type: ReDIF-Article 1.0 Author-Name: Jeremiah Richey Author-X-Name-First: Jeremiah Author-X-Name-Last: Richey Title: An Odd Couple: Monotone Instrumental Variables and Binary Treatments Abstract: This article investigates Monotone Instrumental Variables (MIV) and their ability to aid in identifying treatment effects when the treatment is binary in a nonparametric bounding framework. I show that an MIV can only aid in identification beyond that of a Monotone Treatment Selection assumption if for some region of the instrument the observed conditional-on-received-treatment outcomes exhibit monotonicity in the instrument in the opposite direction as that assumed by the MIV in a Simpson's Paradox-like fashion. Furthermore, an MIV can only aid in identification beyond that of a Monotone Treatment Response assumption if for some region of the instrument either the above Simpson's Paradox-like relationship exists or the instrument's indirect effect on the outcome (as through its influence on treatment selection) is the opposite of its direct effect as assumed by the MIV. The implications of the main findings for empirical work are discussed and the results are highlighted with an application investigating the effect of criminal convictions on job match quality using data from the 1997 National Longitudinal Survey of the Youth. Though the main results are shown to hold only for the binary treatment case in general, they are shown to have important implications for the multi-valued treatment case as well. Journal: Econometric Reviews Pages: 1099-1110 Issue: 6 Volume: 35 Year: 2016 Month: 6 X-DOI: 10.1080/07474938.2014.977082 File-URL: http://hdl.handle.net/10.1080/07474938.2014.977082 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:6:p:1099-1110 Template-Type: ReDIF-Article 1.0 Author-Name: Indeewara Perera Author-X-Name-First: Indeewara Author-X-Name-Last: Perera Author-Name: Javier Hidalgo Author-X-Name-First: Javier Author-X-Name-Last: Hidalgo Author-Name: Mervyn J. Silvapulle Author-X-Name-First: Mervyn J. Author-X-Name-Last: Silvapulle Title: A Goodness-of-Fit Test for a Class of Autoregressive Conditional Duration Models Abstract: This article develops a method for testing the goodness-of-fit of a given parametric autoregressive conditional duration model against unspecified nonparametric alternatives. The test statistics are functions of the residuals corresponding to the quasi maximum likelihood estimate of the given parametric model, and are easy to compute. The limiting distributions of the test statistics are not free from nuisance parameters. Hence, critical values cannot be tabulated for general use. A bootstrap procedure is proposed to implement the tests, and its asymptotic validity is established. The finite sample performances of the proposed tests and several other competing ones in the literature, were compared using a simulation study. The tests proposed in this article performed well consistently throughout, and they were either the best or close to the best. None of the tests performed uniformly the best. The tests are illustrated using an empirical example. Journal: Econometric Reviews Pages: 1111-1141 Issue: 6 Volume: 35 Year: 2016 Month: 6 X-DOI: 10.1080/07474938.2014.975644 File-URL: http://hdl.handle.net/10.1080/07474938.2014.975644 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:6:p:1111-1141 Template-Type: ReDIF-Article 1.0 Author-Name: J. Isaac Miller Author-X-Name-First: J. Isaac Author-X-Name-Last: Miller Title: Conditionally Efficient Estimation of Long-Run Relationships Using Mixed-Frequency Time Series Abstract: I analyze efficient estimation of a cointegrating vector when the regressand and regressor are observed at different frequencies. Previous authors have examined the effects of specific temporal aggregation or sampling schemes, finding conventionally efficient techniques to be efficient only when both the regressand and the regressors are average sampled. Using an alternative method for analyzing aggregation under more general weighting schemes, I derive an efficiency bound that is conditional on the type of aggregation used on the low-frequency series and differs from the unconditional bound defined by the full-information high-frequency data-generating process, which is infeasible due to aggregation of at least one series. I modify a conventional estimator, canonical cointegrating regression (CCR), to accommodate cases in which the aggregation weights are known. The correlation structure may be utilized to offset the potential information loss from aggregation, resulting in a conditionally efficient estimator. In the case of unknown weights, the correlation structure of the error term generally confounds identification of conditionally efficient weights. Efficiency is illustrated using a simulation study and an application to estimating a gasoline demand equation. Journal: Econometric Reviews Pages: 1142-1171 Issue: 6 Volume: 35 Year: 2016 Month: 6 X-DOI: 10.1080/07474938.2014.976527 File-URL: http://hdl.handle.net/10.1080/07474938.2014.976527 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:6:p:1142-1171 Template-Type: ReDIF-Article 1.0 Author-Name: Yuzhi Cai Author-X-Name-First: Yuzhi Author-X-Name-Last: Cai Title: A General Quantile Function Model for Economic and Financial Time Series Abstract: This article proposed a general quantile function model that covers both one- and multiple-dimensional models and that takes several existing models in the literature as its special cases. This article also developed a new uniform Bayesian framework for quantile function modelling and illustrated the developed approach through different quantile function models. Many distributions are defined explicitly only via their quanitle functions as the corresponding distribution or density functions do not have an explicit mathematical expression. Such distributions are rarely used in economic and financial modelling in practice. The developed methodology makes it more convenient to use these distributions in analyzing economic and financial data. Empirical applications to economic and financial time series and comparisons with other types of models and methods show that the developed method can be very useful in practice. Journal: Econometric Reviews Pages: 1173-1193 Issue: 7 Volume: 35 Year: 2016 Month: 8 X-DOI: 10.1080/07474938.2014.976528 File-URL: http://hdl.handle.net/10.1080/07474938.2014.976528 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:7:p:1173-1193 Template-Type: ReDIF-Article 1.0 Author-Name: Kun Ho Kim Author-X-Name-First: Kun Ho Author-X-Name-Last: Kim Title: Inference of the Trend in a Partially Linear Model with Locally Stationary Regressors Abstract: In this article, we construct the uniform confidence band (UCB) of nonparametric trend in a partially linear model with locally stationary regressors. A two-stage semiparametric regression is employed to estimate the trend function. Based on this estimate, we develop an invariance principle to construct the UCB of the trend function. The proposed methodology is used to estimate the Non-Accelerating Inflation Rate of Unemployment (NAIRU) in the Phillips Curve and to perform inference of the parameter based on its UCB. The empirical results strongly suggest that the U.S. NAIRU is time-varying. Journal: Econometric Reviews Pages: 1194-1220 Issue: 7 Volume: 35 Year: 2016 Month: 8 X-DOI: 10.1080/07474938.2014.976530 File-URL: http://hdl.handle.net/10.1080/07474938.2014.976530 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:7:p:1194-1220 Template-Type: ReDIF-Article 1.0 Author-Name: Marcelo Fernandes Author-X-Name-First: Marcelo Author-X-Name-Last: Fernandes Author-Name: Marcelo C. Medeiros Author-X-Name-First: Marcelo C. Author-X-Name-Last: Medeiros Author-Name: Alvaro Veiga Author-X-Name-First: Alvaro Author-X-Name-Last: Veiga Title: A (Semi)Parametric Functional Coefficient Logarithmic Autoregressive Conditional Duration Model Abstract: In this article, we propose a class of logarithmic autoregressive conditional duration (ACD)-type models that accommodates overdispersion, intermittent dynamics, multiple regimes, and asymmetries in financial durations. In particular, our functional coefficient logarithmic autoregressive conditional duration (FC-LACD) model relies on a smooth-transition autoregressive specification. The motivation lies on the fact that the latter yields a universal approximation if one lets the number of regimes grows without bound. After establishing sufficient conditions for strict stationarity, we address model identifiability as well as the asymptotic properties of the quasi-maximum likelihood (QML) estimator for the FC-LACD model with a fixed number of regimes. In addition, we also discuss how to consistently estimate a semiparametric variant of the FC-LACD model that takes the number of regimes to infinity. An empirical illustration indicates that our functional coefficient model is flexible enough to model IBM price durations. Journal: Econometric Reviews Pages: 1221-1250 Issue: 7 Volume: 35 Year: 2016 Month: 8 X-DOI: 10.1080/07474938.2014.977071 File-URL: http://hdl.handle.net/10.1080/07474938.2014.977071 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:7:p:1221-1250 Template-Type: ReDIF-Article 1.0 Author-Name: Mariano Kulish Author-X-Name-First: Mariano Author-X-Name-Last: Kulish Author-Name: Adrian Pagan Author-X-Name-First: Adrian Author-X-Name-Last: Pagan Title: Issues in Estimating New Keynesian Phillips Curves in the Presence of Unknown Structural Change Abstract: Many articles which have estimated models with forward looking expectations have reported that the magnitude of the coefficients of the expectations term is very large when compared with the effects coming from past dynamics. This has sometimes been regarded as implausible and led to the feeling that the expectations coefficient is biased upwards. A relatively general argument that has been advanced is that the bias could be due to structural changes in the means of the variables entering the structural equation. An alternative explanation is that the bias comes from weak instruments. In this article, we investigate the issue of upward bias in the estimated coefficients of the expectations variable based on a model where we can see what causes the breaks and how to control for them. We conclude that weak instruments are the most likely cause of any bias and note that structural change can affect the quality of instruments. We also look at some empirical work in Castle et al. (2014) on the new Kaynesian Phillips curve (NYPC) in the Euro Area and U.S. assessing whether the smaller coefficient on expectations that Castle et al. (2014) highlight is due to structural change. Our conclusion is that it is not. Instead it comes from their addition of variables to the NKPC. After allowing for the fact that there are weak instruments in the estimated re-specified model, it would seem that the forward coefficient estimate is actually quite high rather than low. Journal: Econometric Reviews Pages: 1251-1270 Issue: 7 Volume: 35 Year: 2016 Month: 8 X-DOI: 10.1080/07474938.2014.977075 File-URL: http://hdl.handle.net/10.1080/07474938.2014.977075 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:7:p:1251-1270 Template-Type: ReDIF-Article 1.0 Author-Name: F. Bartolucci Author-X-Name-First: F. Author-X-Name-Last: Bartolucci Author-Name: R. Bellio Author-X-Name-First: R. Author-X-Name-Last: Bellio Author-Name: A. Salvan Author-X-Name-First: A. Author-X-Name-Last: Salvan Author-Name: N. Sartori Author-X-Name-First: N. Author-X-Name-Last: Sartori Title: Modified Profile Likelihood for Fixed-Effects Panel Data Models Abstract: We show how modified profile likelihood methods, developed in the statistical literature, may be effectively applied to estimate the structural parameters of econometric models for panel data, with a remarkable reduction of bias with respect to ordinary likelihood methods. Initially, the implementation of these methods is illustrated for general models for panel data including individual-specific fixed effects and then, in more detail, for the truncated linear regression model and dynamic regression models for binary data formulated along with different specifications. Simulation studies show the good behavior of the inference based on the modified profile likelihood, even when compared to an ideal, although infeasible, procedure (in which the fixed effects are known) and also to alternative estimators existing in the econometric literature. The proposed estimation methods are implemented in an <sans-serif>R</sans-serif> package that we make available to the reader. Journal: Econometric Reviews Pages: 1271-1289 Issue: 7 Volume: 35 Year: 2016 Month: 8 X-DOI: 10.1080/07474938.2014.975642 File-URL: http://hdl.handle.net/10.1080/07474938.2014.975642 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:7:p:1271-1289 Template-Type: ReDIF-Article 1.0 Author-Name: Benjamin Born Author-X-Name-First: Benjamin Author-X-Name-Last: Born Author-Name: Jörg Breitung Author-X-Name-First: Jörg Author-X-Name-Last: Breitung Title: Testing for Serial Correlation in Fixed-Effects Panel Data Models Abstract: In this article, we propose various tests for serial correlation in fixed-effects panel data regression models with a small number of time periods. First, a simplified version of the test suggested by Wooldridge (2002) and Drukker (2003) is considered. The second test is based on the Lagrange Multiplier (LM) statistic suggested by Baltagi and Li (1995), and the third test is a modification of the classical Durbin--Watson statistic. Under the null hypothesis of no serial correlation, all tests possess a standard normal limiting distribution as N tends to infinity and T is fixed. Analyzing the local power of the tests, we find that the LM statistic has superior power properties. Furthermore, a generalization to test for autocorrelation up to some given lag order and a test statistic that is robust against time dependent heteroskedasticity are proposed. Journal: Econometric Reviews Pages: 1290-1316 Issue: 7 Volume: 35 Year: 2016 Month: 8 X-DOI: 10.1080/07474938.2014.976524 File-URL: http://hdl.handle.net/10.1080/07474938.2014.976524 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:7:p:1290-1316 Template-Type: ReDIF-Article 1.0 Author-Name: Maria Grazia Pittau Author-X-Name-First: Maria Grazia Author-X-Name-Last: Pittau Author-Name: Roberto Zelli Author-X-Name-First: Roberto Author-X-Name-Last: Zelli Author-Name: Riccardo Massari Author-X-Name-First: Riccardo Author-X-Name-Last: Massari Title: Evidence of Convergence Clubs Using Mixture Models Abstract: Cross-country economic convergence has been increasingly investigated by finite mixture models. Multiple components in a mixture reflect groups of countries that converge locally. Testing for the number of components is crucial for detecting “convergence clubs.” To assess the number of components of the mixture, we propose a sequential procedure that compares the shape of the hypothesized mixture distribution with the true unknown density, consistently estimated through a kernel estimator. The novelty of our approach is its capability to select the number of components along with a satisfactory fitting of the model. Simulation studies and an empirical application to per capita income distribution across countries testify for the good performance of our approach. A three-clubs convergence seems to emerge. Journal: Econometric Reviews Pages: 1317-1342 Issue: 7 Volume: 35 Year: 2016 Month: 8 X-DOI: 10.1080/07474938.2014.977062 File-URL: http://hdl.handle.net/10.1080/07474938.2014.977062 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:7:p:1317-1342 Template-Type: ReDIF-Article 1.0 Author-Name: Mehmet Caner Author-X-Name-First: Mehmet Author-X-Name-Last: Caner Author-Name: Marcelo C. Medeiros Author-X-Name-First: Marcelo C. Author-X-Name-Last: Medeiros Title: Model Selection and Shrinkage: An Overview Abstract: This special issue is concerned with model selection and shrinkage estimators. This Introduction gives an overview of the papers published in this special issue. Journal: Econometric Reviews Pages: 1343-1346 Issue: 8-10 Volume: 35 Year: 2016 Month: 12 X-DOI: 10.1080/07474938.2015.1071157 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1071157 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:8-10:p:1343-1346 Template-Type: ReDIF-Article 1.0 Author-Name: Clifford Lam Author-X-Name-First: Clifford Author-X-Name-Last: Lam Author-Name: Pedro C. L. Souza Author-X-Name-First: Pedro C. L. Author-X-Name-Last: Souza Title: Detection and Estimation of Block Structure in Spatial Weight Matrix Abstract: In many economic applications, it is often of interest to categorize, classify, or label individuals by groups based on similarity of observed behavior. We propose a method that captures group affiliation or, equivalently, estimates the block structure of a neighboring matrix embedded in a Spatial Econometric model. The main results of the Least Absolute Shrinkage and Selection Operator (Lasso) estimator shows that off-diagonal block elements are estimated as zeros with high probability, property defined as “zero-block consistency.” Furthermore, we present and prove zero-block consistency for the estimated spatial weight matrix even under a thin margin of interaction between groups. The tool developed in this article can be used as a verification of block structure by applied researchers, or as an exploration tool for estimating unknown block structures. We analyzed the U.S. Senate voting data and correctly identified blocks based on party affiliations. Simulations also show that the method performs well. Journal: Econometric Reviews Pages: 1347-1376 Issue: 8-10 Volume: 35 Year: 2016 Month: 12 X-DOI: 10.1080/07474938.2015.1085775 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1085775 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:8-10:p:1347-1376 Template-Type: ReDIF-Article 1.0 Author-Name: Mehmet Caner Author-X-Name-First: Mehmet Author-X-Name-Last: Caner Author-Name: Anders Bredahl Kock Author-X-Name-First: Anders Bredahl Author-X-Name-Last: Kock Title: Oracle Inequalities for Convex Loss Functions with Nonlinear Targets Abstract: This article considers penalized empirical loss minimization of convex loss functions with unknown target functions. Using the elastic net penalty, of which the Least Absolute Shrinkage and Selection Operator (Lasso) is a special case, we establish a finite sample oracle inequality which bounds the loss of our estimator from above with high probability. If the unknown target is linear, this inequality also provides an upper bound of the estimation error of the estimated parameter vector. Next, we use the non-asymptotic results to show that the excess loss of our estimator is asymptotically of the same order as that of the oracle. If the target is linear, we give sufficient conditions for consistency of the estimated parameter vector. We briefly discuss how a thresholded version of our estimator can be used to perform consistent variable selection. We give two examples of loss functions covered by our framework. Journal: Econometric Reviews Pages: 1377-1411 Issue: 8-10 Volume: 35 Year: 2016 Month: 12 X-DOI: 10.1080/07474938.2015.1092797 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1092797 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:8-10:p:1377-1411 Template-Type: ReDIF-Article 1.0 Author-Name: Ulrike Schneider Author-X-Name-First: Ulrike Author-X-Name-Last: Schneider Title: Confidence Sets Based on Thresholding Estimators in High-Dimensional Gaussian Regression Models Abstract: We study confidence intervals based on hard-thresholding, soft-thresholding, and adaptive soft-thresholding in a linear regression model where the number of regressors <italic>k</italic> may depend on and diverge with sample size <italic>n</italic>. In addition to the case of known error variance, we define and study versions of the estimators when the error variance is unknown. In the known-variance case, we provide an exact analysis of the coverage properties of such intervals in finite samples. We show that these intervals are always larger than the standard interval based on the least-squares estimator. Asymptotically, the intervals based on the thresholding estimators are larger even by an order of magnitude when the estimators are tuned to perform consistent variable selection. For the unknown-variance case, we provide nontrivial lower bounds and a small numerical study for the coverage probabilities in finite samples. We also conduct an asymptotic analysis where the results from the known-variance case can be shown to carry over asymptotically if the number of degrees of freedom <italic>n</italic> − <italic>k</italic> tends to infinity fast enough in relation to the thresholding parameter. Journal: Econometric Reviews Pages: 1412-1455 Issue: 8-10 Volume: 35 Year: 2016 Month: 12 X-DOI: 10.1080/07474938.2015.1092798 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1092798 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:8-10:p:1412-1455 Template-Type: ReDIF-Article 1.0 Author-Name: Bruce E. Hansen Author-X-Name-First: Bruce E. Author-X-Name-Last: Hansen Title: The Risk of James--Stein and Lasso Shrinkage Abstract: This article compares the mean-squared error (or ℓ<sub>2</sub> risk) of ordinary least squares (OLS), James--Stein, and least absolute shrinkage and selection operator (Lasso) shrinkage estimators in simple linear regression where the number of regressors is smaller than the sample size. We compare and contrast the known risk bounds for these estimators, which shows that neither James--Stein nor Lasso uniformly dominates the other. We investigate the finite sample risk using a simple simulation experiment. We find that the risk of Lasso estimation is particularly sensitive to coefficient parameterization, and for a significant portion of the parameter space Lasso has higher mean-squared error than OLS. This investigation suggests that there are potential pitfalls arising with Lasso estimation, and simulation studies need to be more attentive to careful exploration of the parameter space. Journal: Econometric Reviews Pages: 1456-1470 Issue: 8-10 Volume: 35 Year: 2016 Month: 12 X-DOI: 10.1080/07474938.2015.1092799 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1092799 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:8-10:p:1456-1470 Template-Type: ReDIF-Article 1.0 Author-Name: Keith Knight Author-X-Name-First: Keith Author-X-Name-Last: Knight Title: The Penalized Analytic Center Estimator Abstract: In a linear regression model, the Dantzig selector (Candès and Tao, 2007) minimizes the <italic>L</italic><sub>1</sub> norm of the regression coefficients subject to a bound <italic>λ</italic> on the <italic>L</italic><sub>∞</sub> norm of the covariances between the predictors and the residuals; the resulting estimator is the solution of a linear program, which may be nonunique or unstable. We propose a regularized alternative to the Dantzig selector. These estimators (which depend on <italic>λ</italic> and an additional tuning parameter <italic>r</italic>) minimize objective functions that are the sum of the <italic>L</italic><sub>1</sub> norm of the regression coefficients plus <italic>r</italic> times the logarithmic potential function of the Dantzig selector constraints, and can be viewed as penalized analytic centers of the latter constraints. The tuning parameter <italic>r</italic> controls the smoothness of the estimators as functions of <italic>λ</italic> and, when <italic>λ</italic> is sufficiently large, the estimators depend approximately on <italic>r</italic> and <italic>λ</italic> via <italic>r</italic>/<italic>λ</italic>-super-2. Journal: Econometric Reviews Pages: 1471-1484 Issue: 8-10 Volume: 35 Year: 2016 Month: 12 X-DOI: 10.1080/07474938.2015.1092800 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1092800 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:8-10:p:1471-1484 Template-Type: ReDIF-Article 1.0 Author-Name: Francesco Audrino Author-X-Name-First: Francesco Author-X-Name-Last: Audrino Author-Name: Simon D. Knaus Author-X-Name-First: Simon D. Author-X-Name-Last: Knaus Title: Lassoing the HAR Model: A Model Selection Perspective on Realized Volatility Dynamics Abstract: Realized volatility computed from high-frequency data is an important measure for many applications in finance, and its dynamics have been widely investigated. Recent notable advances that perform well include the heterogeneous autoregressive (HAR) model which can approximate long memory, is very parsimonious, is easy to estimate, and features good out-of-sample performance. We prove that the least absolute shrinkage and selection operator (Lasso) recovers the lags structure of the HAR model asymptotically if it is the true model, and we present Monte Carlo evidence in finite samples. The HAR model's lags structure is not fully in agreement with the one found using the Lasso on real data. Moreover, we provide empirical evidence that there are two clear breaks in structure for most of the assets we consider. These results bring into question the appropriateness of the HAR model for realized volatility. Finally, in an out-of-sample analysis, we show equal performance of the HAR model and the Lasso approach. Journal: Econometric Reviews Pages: 1485-1521 Issue: 8-10 Volume: 35 Year: 2016 Month: 12 X-DOI: 10.1080/07474938.2015.1092801 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1092801 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:8-10:p:1485-1521 Template-Type: ReDIF-Article 1.0 Author-Name: Malene Kallestrup-Lamb Author-X-Name-First: Malene Author-X-Name-Last: Kallestrup-Lamb Author-Name: Anders Bredahl Kock Author-X-Name-First: Anders Bredahl Author-X-Name-Last: Kock Author-Name: Johannes Tang Kristensen Author-X-Name-First: Johannes Tang Author-X-Name-Last: Kristensen Title: Lassoing the Determinants of Retirement Abstract: This article uses Danish register data to explain the retirement decision of workers in 1990 and 1998. Many variables might be conjectured to influence this decision such as demographic, socioeconomic, financial, and health related variables as well as all the same factors for the spouse in case the individual is married. In total, we have access to 399 individual specific variables that all could potentially impact the retirement decision. We use variants of the least absolute shrinkage and selection operator (Lasso) and the adaptive Lasso applied to logistic regression in order to uncover determinants of the retirement decision. To the best of our knowledge, this is the first application of these estimators in microeconometrics to a problem of this type and scale. Furthermore, we investigate whether the factors influencing the retirement decision are stable over time, gender, and marital status. It is found that this is the case for core variables such as age, income, wealth, and general health. We also point out the most important differences between these groups and explain why these might be present. Journal: Econometric Reviews Pages: 1522-1561 Issue: 8-10 Volume: 35 Year: 2016 Month: 12 X-DOI: 10.1080/07474938.2015.1092803 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1092803 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:8-10:p:1522-1561 Template-Type: ReDIF-Article 1.0 Author-Name: Mehmet Caner Author-X-Name-First: Mehmet Author-X-Name-Last: Caner Author-Name: Esfandiar Maasoumi Author-X-Name-First: Esfandiar Author-X-Name-Last: Maasoumi Author-Name: Juan Andrés Riquelme Author-X-Name-First: Juan Andrés Author-X-Name-Last: Riquelme Title: Moment and IV Selection Approaches: A Comparative Simulation Study Abstract: We compare three moment selection approaches, followed by post-selection estimation strategies. The first is adaptive least absolute shrinkage and selection operator (ALASSO) of Zou (2006), recently extended by Liao (2013) to possibly invalid moments in GMM. In this method, we select the valid instruments with ALASSO. The second method is based on the <italic>J</italic> test, as in Andrews and Lu (2001). The third one is using a Continuous Updating Objective (CUE) function. This last approach is based on Hong et al. (2003), who propose a penalized generalized empirical likelihood-based function to pick up valid moments. They use empirical likelihood, and exponential tilting in their simulations. However, the J-test-based approach of Andrews and Lu (2001) provides generally better moment selection results than the empirical likelihood and exponential tilting as can be seen in Hong et al. (2003). In this article, we examine penalized CUE as a third way of selecting valid moments.Following a determination of valid moments, we run unpenalized generalized method of moments (GMM) and CUE and model averaging technique of Okui (2011) to see which one has better postselection estimator performance for structural parameters. The simulations are aimed at the following questions: Which moment selection criterion can better select the valid ones and eliminate the invalid ones? Given the chosen instruments in the first stage, which strategy delivers the best finite sample performance?We find that the ALASSO in the model selection stage, coupled with either unpenalized GMM or moment averaging of Okui delivers generally the smallest root mean square error (RMSE) for the second stage coefficient estimators. Journal: Econometric Reviews Pages: 1562-1581 Issue: 8-10 Volume: 35 Year: 2016 Month: 12 X-DOI: 10.1080/07474938.2015.1092804 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1092804 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:8-10:p:1562-1581 Template-Type: ReDIF-Article 1.0 Author-Name: Zhentao Shi Author-X-Name-First: Zhentao Author-X-Name-Last: Shi Title: Estimation of Sparse Structural Parameters with Many Endogenous Variables Abstract: We apply the generalized method of moments--least absolute shinkage and selection operator (GMM-Lasso) (Caner, 2009) to a linear structural model with many endogenous regressors. If the true parameter is sufficiently sparse, we can establish a new oracle inequality, which implies that GMM-Lasso performs almost as well as if we knew <italic>a priori</italic> the identities of the relevant variables. Sparsity, meaning that most of the true coefficients are too small to matter, naturally arises in econometric applications where the model can be derived from economic theory. In addition, we propose to use a modified version of AIC or BIC to select the tuning parameter in practical implementation. Simulations provide supportive evidence concerning the finite sample properties of the GMM-Lasso. Journal: Econometric Reviews Pages: 1582-1608 Issue: 8-10 Volume: 35 Year: 2016 Month: 12 X-DOI: 10.1080/07474938.2015.1092805 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1092805 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:8-10:p:1582-1608 Template-Type: ReDIF-Article 1.0 Author-Name: Marine Carrasco Author-X-Name-First: Marine Author-X-Name-Last: Carrasco Author-Name: Guy Tchuente Author-X-Name-First: Guy Author-X-Name-Last: Tchuente Title: Efficient Estimation with Many Weak Instruments Using Regularization Techniques Abstract: The problem of weak instruments is due to a very small concentration parameter. To boost the concentration parameter, we propose to increase the number of instruments to a large number or even up to a continuum. However, in finite samples, the inclusion of an excessive number of moments may be harmful. To address this issue, we use regularization techniques as in Carrasco (2012) and Carrasco and Tchuente (2014). We show that normalized regularized two-stage least squares (2SLS) and limited maximum likelihood (LIML) are consistent and asymptotically normally distributed. Moreover, our estimators are asymptotically more efficient than most competing estimators. Our simulations show that the leading regularized estimators (LF and T of LIML) work very well (are nearly median unbiased) even in the case of relatively weak instruments. An application to the effect of institutions on output growth completes the article. Journal: Econometric Reviews Pages: 1609-1637 Issue: 8-10 Volume: 35 Year: 2016 Month: 12 X-DOI: 10.1080/07474938.2015.1092806 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1092806 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:8-10:p:1609-1637 Template-Type: ReDIF-Article 1.0 Author-Name: Eric Eisenstat Author-X-Name-First: Eric Author-X-Name-Last: Eisenstat Author-Name: Joshua C. C. Chan Author-X-Name-First: Joshua C. C. Author-X-Name-Last: Chan Author-Name: Rodney W. Strachan Author-X-Name-First: Rodney W. Author-X-Name-Last: Strachan Title: Stochastic Model Specification Search for Time-Varying Parameter VARs Abstract: This article develops a new econometric methodology for performing stochastic model specification search (SMSS) in the vast model space of time-varying parameter vector autoregressions (VARs) with stochastic volatility and correlated state transitions. This is motivated by the concern of overfitting and the typically imprecise inference in these highly parameterized models. For each VAR coefficient, this new method automatically decides whether it is constant or time-varying. Moreover, it can be used to shrink an otherwise unrestricted time-varying parameter VAR to a stationary VAR, thus providing an easy way to (probabilistically) impose stationarity in time-varying parameter models. We demonstrate the effectiveness of the approach with a topical application, where we investigate the dynamic effects of structural shocks in government spending on U.S. taxes and gross domestic product (GDP) during a period of very low interest rates. Journal: Econometric Reviews Pages: 1638-1665 Issue: 8-10 Volume: 35 Year: 2016 Month: 12 X-DOI: 10.1080/07474938.2015.1092808 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1092808 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:8-10:p:1638-1665 Template-Type: ReDIF-Article 1.0 Author-Name: Hedibert F. Lopes Author-X-Name-First: Hedibert F. Author-X-Name-Last: Lopes Author-Name: Nicholas G. Polson Author-X-Name-First: Nicholas G. Author-X-Name-Last: Polson Title: Particle Learning for Fat-Tailed Distributions Abstract: It is well known that parameter estimates and forecasts are sensitive to assumptions about the tail behavior of the error distribution. In this article, we develop an approach to sequential inference that also simultaneously estimates the tail of the accompanying error distribution. Our simulation-based approach models errors with a <italic>t</italic><sub>ν</sub>-distribution and, as new data arrives, we sequentially compute the marginal posterior distribution of the tail thickness. Our method naturally incorporates fat-tailed error distributions and can be extended to other data features such as stochastic volatility. We show that the sequential Bayes factor provides an optimal test of fat-tails versus normality. We provide an empirical and theoretical analysis of the rate of learning of tail thickness under a default Jeffreys prior. We illustrate our sequential methodology on the British pound/U.S. dollar daily exchange rate data and on data from the 2008--2009 credit crisis using daily S&P500 returns. Our method naturally extends to multivariate and dynamic panel data. Journal: Econometric Reviews Pages: 1666-1691 Issue: 8-10 Volume: 35 Year: 2016 Month: 12 X-DOI: 10.1080/07474938.2015.1092809 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1092809 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:8-10:p:1666-1691 Template-Type: ReDIF-Article 1.0 Author-Name: Qingfeng Liu Author-X-Name-First: Qingfeng Author-X-Name-Last: Liu Author-Name: Ryo Okui Author-X-Name-First: Ryo Author-X-Name-Last: Okui Author-Name: Arihiro Yoshimura Author-X-Name-First: Arihiro Author-X-Name-Last: Yoshimura Title: Generalized Least Squares Model Averaging Abstract: In this article, we propose a method of averaging generalized least squares estimators for linear regression models with heteroskedastic errors. The averaging weights are chosen to minimize Mallows’ <italic>C</italic><sub><italic>p</italic></sub>-like criterion. We show that the weight vector selected by our method is optimal. It is also shown that this optimality holds even when the variances of the error terms are estimated and the feasible generalized least squares estimators are averaged. The variances can be estimated parametrically or nonparametrically. Monte Carlo simulation results are encouraging. An empirical example illustrates that the proposed method is useful for predicting a measure of firms’ performance. Journal: Econometric Reviews Pages: 1692-1752 Issue: 8-10 Volume: 35 Year: 2016 Month: 12 X-DOI: 10.1080/07474938.2015.1092817 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1092817 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:8-10:p:1692-1752 Template-Type: ReDIF-Article 1.0 Author-Name: Anders Bredahl Kock Author-X-Name-First: Anders Author-X-Name-Last: Bredahl Kock Author-Name: Timo Teräsvirta Author-X-Name-First: Timo Author-X-Name-Last: Teräsvirta Title: Forecasting Macroeconomic Variables Using Neural Network Models and Three Automated Model Selection Techniques Abstract: When forecasting with neural network models one faces several problems, all of which influence the accuracy of the forecasts. First, neural networks are often hard to estimate due to their highly nonlinear structure. To alleviate the problem, White (2006) presented a solution (QuickNet) that converts the specification and nonlinear estimation problem into a linear model selection and estimation problem. We shall compare its performance to that of two other procedures building on the linearization idea: the Marginal Bridge Estimator and Autometrics. Second, one must decide whether forecasting should be carried out recursively or directly. This choice is investigated in this work. The economic time series used in this study are the consumer price indices for the G7 and the Scandinavian countries. In addition, a number of simulations are carried out and results reported in the article. Journal: Econometric Reviews Pages: 1753-1779 Issue: 8-10 Volume: 35 Year: 2016 Month: 12 X-DOI: 10.1080/07474938.2015.1035163 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1035163 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:35:y:2016:i:8-10:p:1753-1779 Template-Type: ReDIF-Article 1.0 Author-Name: Esfandiar Maasoumi Author-X-Name-First: Esfandiar Author-X-Name-Last: Maasoumi Author-Name: Robin Sickles Author-X-Name-First: Robin Author-X-Name-Last: Sickles Title: Peter Schmidt: Econometrician and consummate professional Abstract: Peter Schmidt has been one of its best-known and most respected econometricians in the profession for four decades. He has brought his talents to many scholarly outlets and societies, and has played a foundational and constructive role in the development of the field of econometrics. Peter Schmidt has also served and led the development of Econometric Reviews since its inception in 1982. His judgment has always been fair, informed, clear, decisive, and constructive. Respect for ideas and scholarship of others, young and old, is second nature to him. This is the best of traits, and Peter serves as an uncommon example to us all. The seventeen articles that make up this Econometric Reviews Special Issue in Honor of Peter Schmidt represent the work of fifty of the very best econometricians in our profession. They honor Professor Schmidt's lifelong accomplishments by providing fundamental research work that reflects many of the broad research themes that have distinguished his long and productive career. These include time series econometrics, panel data econometrics, and stochastic frontier production analysis. Journal: Econometric Reviews Pages: 1-5 Issue: 1-3 Volume: 36 Year: 2017 Month: 3 X-DOI: 10.1080/07474938.2015.1116051 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1116051 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:1-3:p:1-5 Template-Type: ReDIF-Article 1.0 Author-Name: Chunrong Ai Author-X-Name-First: Chunrong Author-X-Name-Last: Ai Author-Name: Yuanqing Zhang Author-X-Name-First: Yuanqing Author-X-Name-Last: Zhang Title: Estimation of partially specified spatial panel data models with fixed-effects Abstract: This article extends the spatial panel data regression with fixed-effects to the case where the regression function is partially linear and some regressors may be endogenous or predetermined. Under the assumption that the spatial weighting matrix is strictly exogenous, we propose a sieve two stage least squares (S2SLS) regression. Under some sufficient conditions, we show that the proposed estimator for the finite dimensional parameter is root-N consistent and asymptotically normally distributed and that the proposed estimator for the unknown function is consistent and also asymptotically normally distributed but at a rate slower than root-N. Consistent estimators for the asymptotic variances of the proposed estimators are provided. A small scale simulation study is conducted, and the simulation results show that the proposed procedure has good finite sample performance. Journal: Econometric Reviews Pages: 6-22 Issue: 1-3 Volume: 36 Year: 2017 Month: 3 X-DOI: 10.1080/07474938.2015.1113641 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1113641 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:1-3:p:6-22 Template-Type: ReDIF-Article 1.0 Author-Name: Martyn Andrews Author-X-Name-First: Martyn Author-X-Name-Last: Andrews Author-Name: Obbey Elamin Author-X-Name-First: Obbey Author-X-Name-Last: Elamin Author-Name: Alastair R. Hall Author-X-Name-First: Alastair R. Author-X-Name-Last: Hall Author-Name: Kostas Kyriakoulis Author-X-Name-First: Kostas Author-X-Name-Last: Kyriakoulis Author-Name: Matthew Sutton Author-X-Name-First: Matthew Author-X-Name-Last: Sutton Title: Inference in the presence of redundant moment conditions and the impact of government health expenditure on health outcomes in England Abstract: In his 1999 article with Breusch, Qian, and Wyhowski in the <italic>Journal of Econometrics</italic>, Peter Schmidt introduced the concept of “redundant” moment conditions. Such conditions arise when estimation is based on moment conditions that are valid and can be divided into two subsets: one that identifies the parameters and another that provides no further information. Their framework highlights an important concept in the moment-based estimation literature, namely, that not all valid moment conditions need be informative about the parameters of interest. In this article, we demonstrate the empirical relevance of the concept in the context of the impact of government health expenditure on health outcomes in England. Using a simulation study calibrated to this data, we perform a comparative study of the finite performance of inference procedures based on the Generalized Method of Moment (GMM) and info-metric (IM) estimators. The results indicate that the properties of GMM procedures deteriorate as the number of redundant moment conditions increases; in contrast, the IM methods provide reliable point estimators, but the performance of associated inference techniques based on first order asymptotic theory, such as confidence intervals and overidentifying restriction tests, deteriorates as the number of redundant moment conditions increases. However, for IM methods, it is shown that bootstrap procedures can provide reliable inferences; we illustrate such methods when analysing the impact of government health expenditure on health outcomes in England. Journal: Econometric Reviews Pages: 23-41 Issue: 1-3 Volume: 36 Year: 2017 Month: 3 X-DOI: 10.1080/07474938.2016.1114205 File-URL: http://hdl.handle.net/10.1080/07474938.2016.1114205 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:1-3:p:23-41 Template-Type: ReDIF-Article 1.0 Author-Name: Manabu Asai Author-X-Name-First: Manabu Author-X-Name-Last: Asai Author-Name: Michael McAleer Author-X-Name-First: Michael Author-X-Name-Last: McAleer Title: A fractionally integrated Wishart stochastic volatility model Abstract: There has recently been growing interest in modeling and estimating alternative continuous time multivariate stochastic volatility models. We propose a continuous time fractionally integrated Wishart stochastic volatility (FIWSV) process, and derive the conditional Laplace transform of the FIWSV model in order to obtain a closed form expression of moments. A two-step procedure is used, namely estimating the parameter of fractional integration via the local Whittle estimator in the first step, and estimating the remaining parameters via the generalized method of moments in the second step. Monte Carlo results for the procedure show a reasonable performance in finite samples. The empirical results for the S&P 500 and FTSE 100 indexes show that the data favor the new FIWSV process rather than the one-factor and two-factor models of the Wishart autoregressive process for the covariance structure. Journal: Econometric Reviews Pages: 42-59 Issue: 1-3 Volume: 36 Year: 2017 Month: 3 X-DOI: 10.1080/07474938.2015.1114235 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1114235 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:1-3:p:42-59 Template-Type: ReDIF-Article 1.0 Author-Name: Richard T. Baillie Author-X-Name-First: Richard T. Author-X-Name-Last: Baillie Author-Name: George Kapetanios Author-X-Name-First: George Author-X-Name-Last: Kapetanios Author-Name: Fotis Papailias Author-X-Name-First: Fotis Author-X-Name-Last: Papailias Title: Inference for impulse response coefficients from multivariate fractionally integrated processes Abstract: This article considers a multivariate system of fractionally integrated time series and investigates the most appropriate way for estimating Impulse Response (<italic>IR</italic>) coefficients and their associated confidence intervals. The article extends the univariate analysis recently provided by Baillie and Kapetanios (2013), and uses a semiparametric, time domain estimator, based on a vector autoregression (<italic>VAR</italic>) approximation. Results are also derived for the orthogonalized estimated <italic>IRs</italic> which are generally more practically relevant. Simulation evidence strongly indicates the desirability of applying the Kilian small sample bias correction, which is found to improve the coverage accuracy of confidence intervals for <italic>IRs</italic>. The most appropriate order of the <italic>VAR</italic> turns out to be relevant for the lag length of the <italic>IR</italic> being estimated. Journal: Econometric Reviews Pages: 60-84 Issue: 1-3 Volume: 36 Year: 2017 Month: 3 X-DOI: 10.1080/07474938.2015.1114253 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1114253 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:1-3:p:60-84 Template-Type: ReDIF-Article 1.0 Author-Name: Badi H. Baltagi Author-X-Name-First: Badi H. Author-X-Name-Last: Baltagi Author-Name: Chihwa Kao Author-X-Name-First: Chihwa Author-X-Name-Last: Kao Author-Name: Long Liu Author-X-Name-First: Long Author-X-Name-Last: Liu Title: Estimation and identification of change points in panel models with nonstationary or stationary regressors and error term Abstract: This article studies the estimation of change point in panel models. We extend Bai (2010) and Feng et al. (2009) to the case of stationary or nonstationary regressors and error term, and whether the change point is present or not. We prove consistency and derive the asymptotic distributions of the Ordinary Least Squares (OLS) and First Difference (FD) estimators. We find that the FD estimator is robust for all cases considered. Journal: Econometric Reviews Pages: 85-102 Issue: 1-3 Volume: 36 Year: 2017 Month: 3 X-DOI: 10.1080/07474938.2015.1114262 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1114262 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:1-3:p:85-102 Template-Type: ReDIF-Article 1.0 Author-Name: Herman J. Bierens Author-X-Name-First: Herman J. Author-X-Name-Last: Bierens Author-Name: Li Wang Author-X-Name-First: Li Author-X-Name-Last: Wang Title: Weighted simulated integrated conditional moment tests for parametric conditional distributions of stationary time series processes Abstract: In this article, we propose a weighted simulated integrated conditional moment (WSICM) test of the validity of parametric specifications of conditional distribution models for stationary time series data, by combining the weighted integrated conditional moment (ICM) test of Bierens (1984) for time series regression models with the simulated ICM test of Bierens and Wang (2012) of conditional distribution models for cross-section data. To the best of our knowledge, no other consistent test for parametric conditional time series distributions has been proposed yet in the literature, despite consistency claims made by some authors. Journal: Econometric Reviews Pages: 103-135 Issue: 1-3 Volume: 36 Year: 2017 Month: 3 X-DOI: 10.1080/07474938.2015.1114275 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1114275 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:1-3:p:103-135 Template-Type: ReDIF-Article 1.0 Author-Name: Yoosoon Chang Author-X-Name-First: Yoosoon Author-X-Name-Last: Chang Author-Name: Robin C. Sickles Author-X-Name-First: Robin C. Author-X-Name-Last: Sickles Author-Name: Wonho Song Author-X-Name-First: Wonho Author-X-Name-Last: Song Title: Bootstrapping unit root tests with covariates Abstract: We consider the bootstrap method for the covariates augmented Dickey--Fuller (CADF) unit root test suggested in Hansen (1995) which uses related variables to improve the power of univariate unit root tests. It is shown that there are substantial power gains from including correlated covariates. The limit distribution of the CADF test, however, depends on the nuisance parameter that represents the correlation between the equation error and the covariates. Hence, inference based directly on the CADF test is not possible. To provide a valid inferential basis for the CADF test, we propose to use the parametric bootstrap procedure to obtain critical values, and establish the asymptotic validity of the bootstrap CADF test. Simulations show that the bootstrap CADF test significantly improves the asymptotic and the finite sample size performances of the CADF test, especially when the covariates are highly correlated with the error. Indeed, the bootstrap CADF test offers drastic power gains over the conventional unit root tests. Our testing procedures are applied to the extended Nelson and Plosser data set. Journal: Econometric Reviews Pages: 136-155 Issue: 1-3 Volume: 36 Year: 2017 Month: 3 X-DOI: 10.1080/07474938.2015.1114279 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1114279 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:1-3:p:136-155 Template-Type: ReDIF-Article 1.0 Author-Name: Abdelaati Daouia Author-X-Name-First: Abdelaati Author-X-Name-Last: Daouia Author-Name: Léopold Simar Author-X-Name-First: Léopold Author-X-Name-Last: Simar Author-Name: Paul W. Wilson Author-X-Name-First: Paul W. Author-X-Name-Last: Wilson Title: Measuring firm performance using nonparametric quantile-type distances Abstract: When faced with multiple inputs <inline-formula><inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="lecr_a_1114289_ilm0001.gif"/></inline-formula> and outputs <inline-formula><inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="lecr_a_1114289_ilm0002.gif"/></inline-formula>, traditional quantile regression of <italic>Y</italic> conditional on <italic>X</italic> = <italic>x</italic> for measuring economic efficiency in the output (input) direction is thwarted by the absence of a natural ordering of Euclidean space for dimensions <italic>q</italic> (<italic>p</italic>) greater than one. Daouia and Simar (2007) used nonstandard conditional quantiles to address this problem, conditioning on <italic>Y</italic> ≥ <italic>y</italic> (<italic>X</italic> ≤ <italic>x</italic>) in the output (input) orientation, but the resulting quantiles depend on the a priori chosen direction. This article uses a dimensionless transformation of the (<italic>p</italic> + <italic>q</italic>)-dimensional production process to develop an alternative formulation of distance from a realization of (<italic>X</italic>, <italic>Y</italic>) to the efficient support boundary, motivating a new, <italic>unconditional</italic> quantile frontier lying inside the joint support of (<italic>X</italic>, <italic>Y</italic>), but near the full, efficient frontier. The interpretation is analogous to univariate quantiles and corrects some of the disappointing properties of the conditional quantile-based approach. By contrast with the latter, our approach determines a unique partial-quantile frontier independent of the chosen orientation (input, output, hyperbolic, or directional distance). We prove that both the resulting efficiency score and its estimator share desirable monotonicity properties. Simple arguments from extreme-value theory are used to derive the asymptotic distributional properties of the corresponding empirical efficiency scores (both full and partial). The usefulness of the quantile-type estimator is shown from an infinitesimal and global robustness theory viewpoints via a comparison with the previous conditional quantile-based approach. A diagnostic tool is developed to find the appropriate quantile-order; in the literature to date, this trimming order has been fixed <italic>a priori</italic>. The methodology is used to analyze the performance of U.S. credit unions, where outliers are likely to affect traditional approaches. Journal: Econometric Reviews Pages: 156-181 Issue: 1-3 Volume: 36 Year: 2017 Month: 3 X-DOI: 10.1080/07474938.2015.1114289 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1114289 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:1-3:p:156-181 Template-Type: ReDIF-Article 1.0 Author-Name: Jean-Marie Dufour Author-X-Name-First: Jean-Marie Author-X-Name-Last: Dufour Author-Name: Alain Trognon Author-X-Name-First: Alain Author-X-Name-Last: Trognon Author-Name: Purevdorj Tuvaandorj Author-X-Name-First: Purevdorj Author-X-Name-Last: Tuvaandorj Title: Invariant tests based on <italic>M</italic>-estimators, estimating functions, and the generalized method of moments Abstract: We study the invariance properties of various test criteria which have been proposed for hypothesis testing in the context of incompletely specified models, such as models which are formulated in terms of estimating functions (Godambe, 1960) or moment conditions and are estimated by generalized method of moments (GMM) procedures (Hansen, 1982), and models estimated by pseudo-likelihood (Gouriéroux, Monfort, and Trognon, 1984b,c) and <italic>M</italic>-estimation methods. The invariance properties considered include invariance to (possibly nonlinear) hypothesis reformulations and reparameterizations. The test statistics examined include Wald-type, LR-type, LM-type, score-type, and <italic>C</italic>(<italic>α</italic>)−type criteria. Extending the approach used in Dagenais and Dufour (1991), we show first that all these test statistics except the Wald-type ones are invariant to equivalent hypothesis reformulations (under usual regularity conditions), but all five of them are <italic>not generally invariant</italic> to model reparameterizations, including measurement unit changes in nonlinear models. In other words, testing two equivalent hypotheses in the context of equivalent models may lead to completely different inferences. For example, this may occur after an apparently innocuous rescaling of some model variables. Then, in view of avoiding such undesirable properties, we study restrictions that can be imposed on the objective functions used for pseudo-likelihood (or M-estimation) as well as the structure of the test criteria used with estimating functions and generalized method of moments (GMM) procedures to obtain invariant tests. In particular, we show that using linear exponential pseudo-likelihood functions allows one to obtain invariant score-type and <italic>C</italic>(<italic>α</italic>)−type test criteria, while in the context of estimating function (or GMM) procedures it is possible to modify a LR-type statistic proposed by Newey and West (1987) to obtain a test statistic that is invariant to general reparameterizations. The invariance associated with linear exponential pseudo-likelihood functions is interpreted as a strong argument for using such pseudo-likelihood functions in empirical work. Journal: Econometric Reviews Pages: 182-204 Issue: 1-3 Volume: 36 Year: 2017 Month: 3 X-DOI: 10.1080/07474938.2015.1114285 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1114285 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:1-3:p:182-204 Template-Type: ReDIF-Article 1.0 Author-Name: Carl Green Author-X-Name-First: Carl Author-X-Name-Last: Green Author-Name: Qi Li Author-X-Name-First: Qi Author-X-Name-Last: Li Author-Name: Yu Yvette Zhang Author-X-Name-First: Yu Yvette Author-X-Name-Last: Zhang Title: Nonparametric estimation of regression models with mixed discrete and continuous covariates by the K-nn method Abstract: In this article we consider the problem of estimating a nonparametric conditional mean function with mixed discrete and continuous covariates by the nonparametric <italic>k</italic>-nearest-neighbor (<italic>k-nn</italic>) method. We derive the asymptotic normality result of the proposed estimator and use Monte Carlo simulations to demonstrate its finite sample performance. We also provide an illustrative empirical example of our method. Journal: Econometric Reviews Pages: 205-224 Issue: 1-3 Volume: 36 Year: 2017 Month: 3 X-DOI: 10.1080/07474938.2015.1114295 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1114295 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:1-3:p:205-224 Template-Type: ReDIF-Article 1.0 Author-Name: Chirok Han Author-X-Name-First: Chirok Author-X-Name-Last: Han Author-Name: Peter C. B. Phillips Author-X-Name-First: Peter C. B. Author-X-Name-Last: Phillips Author-Name: Donggyu Sul Author-X-Name-First: Donggyu Author-X-Name-Last: Sul Title: Lag length selection in panel autoregression Abstract: Model selection by BIC is well known to be inconsistent in the presence of incidental parameters. This article shows that, somewhat surprisingly, even without fixed effects in dynamic panels BIC is inconsistent and overestimates the true lag length with considerable probability. The reason for the inconsistency is explained, and the probability of overestimation is found to be 50% asymptotically. Three alternative consistent lag selection methods are considered. Two of these modify BIC, and the third involves sequential testing. Simulations evaluate the performance of these alternative lag selection methods in finite samples. Journal: Econometric Reviews Pages: 225-240 Issue: 1-3 Volume: 36 Year: 2017 Month: 3 X-DOI: 10.1080/07474938.2015.1114313 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1114313 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:1-3:p:225-240 Template-Type: ReDIF-Article 1.0 Author-Name: Nicholas M. Kiefer Author-X-Name-First: Nicholas M. Author-X-Name-Last: Kiefer Author-Name: Jeffrey S. Racine Author-X-Name-First: Jeffrey S. Author-X-Name-Last: Racine Title: The smooth colonel and the reverend find common ground Abstract: A semiparametric regression estimator that exploits categorical (i.e., discrete-support) kernel functions is developed for a broad class of hierarchical models including the pooled regression estimator, the fixed-effects estimator familiar from panel data, and the varying coefficient estimator, among others. Separate shrinking is allowed for each coefficient. Regressors may be continuous or discrete. The estimator is motivated as an intuitive and appealing generalization of existing methods. It is then supported by demonstrating that it can be realized as a posterior mean in the Lindley and Smith (1972) framework. As a demonstration of the flexibility of the proposed approach, the model is extended to nonparametric hierarchical regression based on B-splines. Journal: Econometric Reviews Pages: 241-256 Issue: 1-3 Volume: 36 Year: 2017 Month: 3 X-DOI: 10.1080/07474938.2015.1114304 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1114304 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:1-3:p:241-256 Template-Type: ReDIF-Article 1.0 Author-Name: Kajal Lahiri Author-X-Name-First: Kajal Author-X-Name-Last: Lahiri Author-Name: Huaming Peng Author-X-Name-First: Huaming Author-X-Name-Last: Peng Author-Name: Yongchen Zhao Author-X-Name-First: Yongchen Author-X-Name-Last: Zhao Title: Online learning and forecast combination in unbalanced panels Abstract: This article evaluates the performance of a few newly proposed online forecast combination algorithms and compares them with some of the existing ones including the simple average and that of Bates and Granger (1969). We derive asymptotic results for the new algorithms that justify certain established approaches to forecast combination including trimming, clustering, weighting, and shrinkage. We also show that when implemented on unbalanced panels, different combination algorithms implicitly impute missing data differently, so that the performance of the resulting combined forecasts are not comparable. After explicitly imputing the missing observations in the U.S. Survey of Professional Forecasters (SPF) over 1968 IV-2013 I, we find that the equally weighted average continues to be hard to beat, but the new algorithms can potentially deliver superior performance at shorter horizons, especially during periods of volatility clustering and structural breaks. Journal: Econometric Reviews Pages: 257-288 Issue: 1-3 Volume: 36 Year: 2017 Month: 3 X-DOI: 10.1080/07474938.2015.1114550 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1114550 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:1-3:p:257-288 Template-Type: ReDIF-Article 1.0 Author-Name: Ye Li Author-X-Name-First: Ye Author-X-Name-Last: Li Author-Name: Pierre Perron Author-X-Name-First: Pierre Author-X-Name-Last: Perron Title: Inference on locally ordered breaks in multiple regressions Abstract: We consider issues related to inference about locally ordered breaks in a system of equations, as originally proposed by Qu and Perron (2007). These apply when break dates in different equations within the system are not separated by a positive fraction of the sample size. This allows constructing joint confidence intervals of all such locally ordered break dates. We extend the results of Qu and Perron (2007) in several directions. First, we allow the covariates to be any mix of trends and stationary or integrated regressors. Second, we allow for breaks in the variance-covariance matrix of the errors. Third, we allow for multiple locally ordered breaks, each occurring in a different equation within a subset of equations in the system. Via some simulation experiments, we show first that the limit distributions derived provide good approximations to the finite sample distributions. Second, we show that forming confidence intervals in such a joint fashion allows more precision (tighter intervals) compared to the standard approach of forming confidence intervals using the method of Bai and Perron (1998) applied to a single equation. Simulations also indicate that using the locally ordered break confidence intervals yields better coverage rates than using the framework for globally distinct breaks when the break dates are separated by roughly 10% of the total sample size. Journal: Econometric Reviews Pages: 289-353 Issue: 1-3 Volume: 36 Year: 2017 Month: 3 X-DOI: 10.1080/07474938.2015.1114552 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1114552 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:1-3:p:289-353 Template-Type: ReDIF-Article 1.0 Author-Name: Kunpeng Li Author-X-Name-First: Kunpeng Author-X-Name-Last: Li Author-Name: Degui Li Author-X-Name-First: Degui Author-X-Name-Last: Li Author-Name: Zhongwen Liang Author-X-Name-First: Zhongwen Author-X-Name-Last: Liang Author-Name: Cheng Hsiao Author-X-Name-First: Cheng Author-X-Name-Last: Hsiao Title: Estimation of semi-varying coefficient models with nonstationary regressors Abstract: We study a semivarying coefficient model where the regressors are generated by the multivariate unit root I(1) processes. The influence of the explanatory vectors on the response variable satisfies the semiparametric partially linear structure with the nonlinear component being functional coefficients. A semiparametric estimation methodology with the first-stage local polynomial smoothing is applied to estimate both the constant coefficients in the linear component and the functional coefficients in the nonlinear component. The asymptotic distribution theory for the proposed semiparametric estimators is established under some mild conditions, from which both the parametric and nonparametric estimators are shown to enjoy the well-known super-consistency property. Furthermore, a simulation study is conducted to investigate the finite sample performance of the developed methodology and results. Journal: Econometric Reviews Pages: 354-369 Issue: 1-3 Volume: 36 Year: 2017 Month: 3 X-DOI: 10.1080/07474938.2015.1114563 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1114563 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:1-3:p:354-369 Template-Type: ReDIF-Article 1.0 Author-Name: Aman Ullah Author-X-Name-First: Aman Author-X-Name-Last: Ullah Author-Name: Alan T. K. Wan Author-X-Name-First: Alan T. K. Author-X-Name-Last: Wan Author-Name: Huansha Wang Author-X-Name-First: Huansha Author-X-Name-Last: Wang Author-Name: Xinyu Zhang Author-X-Name-First: Xinyu Author-X-Name-Last: Zhang Author-Name: Guohua Zou Author-X-Name-First: Guohua Author-X-Name-Last: Zou Title: A semiparametric generalized ridge estimator and link with model averaging Abstract: In recent years, the suggestion of combining models as an alternative to selecting a single model from a frequentist prospective has been advanced in a number of studies. In this article, we propose a new semiparametric estimator of regression coefficients, which is in the form of a feasible generalized ridge estimator by Hoerl and Kennard (1970b) but with different biasing factors. We prove that after reparameterization such that the regressors are orthogonal, the generalized ridge estimator is algebraically identical to the model average estimator. Further, the biasing factors that determine the properties of both the generalized ridge and semiparametric estimators are directly linked to the weights used in model averaging. These are interesting results for the interpretations and applications of both semiparametric and ridge estimators. Furthermore, we demonstrate that these estimators based on model averaging weights can have properties superior to the well-known feasible generalized ridge estimator in a large region of the parameter space. Two empirical examples are presented. Journal: Econometric Reviews Pages: 370-384 Issue: 1-3 Volume: 36 Year: 2017 Month: 3 X-DOI: 10.1080/07474938.2015.1114564 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1114564 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:1-3:p:370-384 Template-Type: ReDIF-Article 1.0 Author-Name: Tom Wansbeek Author-X-Name-First: Tom Author-X-Name-Last: Wansbeek Author-Name: Dennis Prak Author-X-Name-First: Dennis Author-X-Name-Last: Prak Title: LIML in the static linear panel data model Abstract: We consider the static linear panel data model with a single regressor. For this model, we derive the LIML estimator. We study the asymptotic behavior of this estimator under many-instruments asymptotics, by showing its consistency, deriving its asymptotic variance, and by presenting an estimator of the asymptotic variance that is consistent under many-instruments asymptotics. We briefly indicate the extension to the static panel data model with multiple regressors. Journal: Econometric Reviews Pages: 385-395 Issue: 1-3 Volume: 36 Year: 2017 Month: 3 X-DOI: 10.1080/07474938.2015.1114566 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1114566 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:1-3:p:385-395 Template-Type: ReDIF-Article 1.0 Author-Name: Esmeralda A. Ramalho Author-X-Name-First: Esmeralda A. Author-X-Name-Last: Ramalho Author-Name: Joaquim J. S. Ramalho Author-X-Name-First: Joaquim J. S. Author-X-Name-Last: Ramalho Title: Moment-based estimation of nonlinear regression models with boundary outcomes and endogeneity, with applications to nonnegative and fractional responses Abstract: In this article, we suggest simple moment-based estimators to deal with unobserved heterogeneity in a special class of nonlinear regression models that includes as main particular cases exponential models for nonnegative responses and logit and complementary loglog models for fractional responses. The proposed estimators: (i) treat observed and omitted covariates in a similar manner; (ii) can deal with boundary outcomes; (iii) accommodate endogenous explanatory variables without requiring knowledge on the reduced form model, although such information may be easily incorporated in the estimation process; (iv) do not require distributional assumptions on the unobservables, a conditional mean assumption being enough for consistent estimation of the structural parameters; and (v) under the additional assumption that the dependence between observables and unobservables is restricted to the conditional mean, produce consistent estimators of partial effects conditional only on observables. Journal: Econometric Reviews Pages: 397-420 Issue: 4 Volume: 36 Year: 2017 Month: 4 X-DOI: 10.1080/07474938.2014.976531 File-URL: http://hdl.handle.net/10.1080/07474938.2014.976531 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:4:p:397-420 Template-Type: ReDIF-Article 1.0 Author-Name: Cristina Amado Author-X-Name-First: Cristina Author-X-Name-Last: Amado Author-Name: Timo Teräsvirta Author-X-Name-First: Timo Author-X-Name-Last: Teräsvirta Title: Specification and testing of multiplicative time-varying GARCH models with applications Abstract: In this article, we develop a specification technique for building multiplicative time-varying GARCH models of Amado and Teräsvirta (2008, 2013). The variance is decomposed into an unconditional and a conditional component such that the unconditional variance component is allowed to evolve smoothly over time. This nonstationary component is defined as a linear combination of logistic transition functions with time as the transition variable. The appropriate number of transition functions is determined by a sequence of specification tests. For that purpose, a coherent modelling strategy based on statistical inference is presented. It is heavily dependent on Lagrange multiplier type misspecification tests. The tests are easily implemented as they are entirely based on auxiliary regressions. Finite-sample properties of the strategy and tests are examined by simulation. The modelling strategy is illustrated in practice with two real examples: an empirical application to daily exchange rate returns and another one to daily coffee futures returns. Journal: Econometric Reviews Pages: 421-446 Issue: 4 Volume: 36 Year: 2017 Month: 4 X-DOI: 10.1080/07474938.2014.977064 File-URL: http://hdl.handle.net/10.1080/07474938.2014.977064 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:4:p:421-446 Template-Type: ReDIF-Article 1.0 Author-Name: Chris Blakely Author-X-Name-First: Chris Author-X-Name-Last: Blakely Author-Name: Tucker McElroy Author-X-Name-First: Tucker Author-X-Name-Last: McElroy Title: Signal extraction goodness-of-fit diagnostic tests under model parameter uncertainty: Formulations and empirical evaluation Abstract: We present a time-domain goodness-of-fit (gof) diagnostic test that is based on signal-extraction variances for nonstationary time series. This diagnostic test extends the time-domain gof statistic of Maravall (2003) by taking into account the effects of model parameter uncertainty, utilizing theoretical results of McElroy and Holan (2009). We demonstrate that omitting this correction results in a severely undersized statistic. Adequate size and power are obtained in Monte Carlo studies for fairly short time series (10 to 15 years of monthly data). Our Monte Carlo studies of finite sample size and power consider different combinations of both signal and noise components using seasonal, trend, and irregular component models obtained via canonical decomposition. Details of the implementation appropriate for SARIMA models are given. We apply the gof diagnostic test statistics to several U.S. Census Bureau time series. The results generally corroborate the output of the automatic model selection procedure of the X-12-ARIMA software, which in contrast to our diagnostic test statistic does not involve hypothesis testing. We conclude that these diagnostic test statistics are a useful supplementary model-checking tool for practitioners engaged in the task of model-based seasonal adjustment. Journal: Econometric Reviews Pages: 447-467 Issue: 4 Volume: 36 Year: 2017 Month: 4 X-DOI: 10.1080/07474938.2016.1140277 File-URL: http://hdl.handle.net/10.1080/07474938.2016.1140277 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:4:p:447-467 Template-Type: ReDIF-Article 1.0 Author-Name: Zdeněk Hlávka Author-X-Name-First: Zdeněk Author-X-Name-Last: Hlávka Author-Name: Marie Hušková Author-X-Name-First: Marie Author-X-Name-Last: Hušková Author-Name: Claudia Kirch Author-X-Name-First: Claudia Author-X-Name-Last: Kirch Author-Name: Simos G. Meintanis Author-X-Name-First: Simos G. Author-X-Name-Last: Meintanis Title: Fourier--type tests involving martingale difference processes Abstract: We develop testing procedures which detect if the observed time series is a martingale difference sequence. Furthermore, tests are developed that detect change--points in the conditional expectation of the series given its past. The test statistics are formulated following the approach of Fourier--type conditional expectations first proposed by Bierens (1982) and have the advantage of computational simplicity. The limit behavior of the test statistics is investigated under the null hypothesis as well as under alternatives. Since the asymptotic null distribution contains unknown parameters, a bootstrap procedure is proposed in order to actually perform the test. The performance of the bootstrap version of the test is compared in finite samples with other methods for the same problem. A real--data application is also included. Journal: Econometric Reviews Pages: 468-492 Issue: 4 Volume: 36 Year: 2017 Month: 4 X-DOI: 10.1080/07474938.2014.977074 File-URL: http://hdl.handle.net/10.1080/07474938.2014.977074 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:4:p:468-492 Template-Type: ReDIF-Article 1.0 Author-Name: Massimilano Caporin Author-X-Name-First: Massimilano Author-X-Name-Last: Caporin Author-Name: Paolo Paruolo Author-X-Name-First: Paolo Author-X-Name-Last: Paruolo Title: Correction of Caporin and Paruolo (2015) Journal: Econometric Reviews Pages: 493-493 Issue: 4 Volume: 36 Year: 2017 Month: 4 X-DOI: 10.1080/07474938.2016.1275203 File-URL: http://hdl.handle.net/10.1080/07474938.2016.1275203 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:4:p:493-493 Template-Type: ReDIF-Article 1.0 Author-Name: Tucker McElroy Author-X-Name-First: Tucker Author-X-Name-Last: McElroy Author-Name: Michael W. McCracken Author-X-Name-First: Michael W. Author-X-Name-Last: McCracken Title: Multistep ahead forecasting of vector time series Abstract: This article develops the theory of multistep ahead forecasting for vector time series that exhibit temporal nonstationarity and co-integration. We treat the case of a semi-infinite past by developing the forecast filters and the forecast error filters explicitly. We also provide formulas for forecasting from a finite data sample. This latter application can be accomplished by using large matrices, which remains practicable when the total sample size is moderate. Expressions for the mean square error of forecasts are also derived and can be implemented readily. The flexibility and generality of these formulas are illustrated by four diverse applications: forecasting euro area macroeconomic aggregates; backcasting fertility rates by racial category; forecasting long memory inflation data; and forecasting regional housing starts using a seasonally co-integrated model. Journal: Econometric Reviews Pages: 495-513 Issue: 5 Volume: 36 Year: 2017 Month: 5 X-DOI: 10.1080/07474938.2014.977088 File-URL: http://hdl.handle.net/10.1080/07474938.2014.977088 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:5:p:495-513 Template-Type: ReDIF-Article 1.0 Author-Name: Guillaume Chevillon Author-X-Name-First: Guillaume Author-X-Name-Last: Chevillon Title: Robust cointegration testing in the presence of weak trends, with an application to the human origin of global warming Abstract: Standard tests for the rank of cointegration of a vector autoregressive process present distributions that are affected by the presence of deterministic trends. We consider the recent approach of Demetrescu et al. (2009) who recommend testing a composite null. We assess this methodology in the presence of trends (linear or broken) whose magnitude is small enough not to be always detectable at conventional significance levels. We model them using local asymptotics and derive the properties of the test statistics. We show that whether the trend is orthogonal to the cointegrating vector has a major impact on the distributions but that the test combination approach remains valid. We apply of the methodology to the study of cointegration properties between global temperatures and the radiative forcing of human gas emissions. We find new evidence of Granger Causality. Journal: Econometric Reviews Pages: 514-545 Issue: 5 Volume: 36 Year: 2017 Month: 5 X-DOI: 10.1080/07474938.2014.977080 File-URL: http://hdl.handle.net/10.1080/07474938.2014.977080 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:5:p:514-545 Template-Type: ReDIF-Article 1.0 Author-Name: Jouchi Nakajima Author-X-Name-First: Jouchi Author-X-Name-Last: Nakajima Title: Bayesian analysis of multivariate stochastic volatility with skew return distribution Abstract: Multivariate stochastic volatility models with skew distributions are proposed. Exploiting Cholesky stochastic volatility modeling, univariate stochastic volatility processes with leverage effect and generalized hyperbolic skew t-distributions are embedded to multivariate analysis with time-varying correlations. Bayesian modeling allows this approach to provide parsimonious skew structure and to easily scale up for high-dimensional problem. Analyses of daily stock returns are illustrated. Empirical results show that the time-varying correlations and the sparse skew structure contribute to improved prediction performance and Value-at-Risk forecasts. Journal: Econometric Reviews Pages: 546-562 Issue: 5 Volume: 36 Year: 2017 Month: 5 X-DOI: 10.1080/07474938.2014.977093 File-URL: http://hdl.handle.net/10.1080/07474938.2014.977093 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:5:p:546-562 Template-Type: ReDIF-Article 1.0 Author-Name: Zongwu Cai Author-X-Name-First: Zongwu Author-X-Name-Last: Cai Author-Name: Ying Fang Author-X-Name-First: Ying Author-X-Name-Last: Fang Author-Name: Henong Li Author-X-Name-First: Henong Author-X-Name-Last: Li Title: Weak Instrumental Variables Models for Longitudinal Data Abstract: This article considers the estimation and testing of a within-group two-stage least squares (TSLS) estimator for instruments with varying degrees of weakness in a longitudinal (panel) data model. We show that adding the repeated cross-sectional information into a regression model can improve the estimation in weak instruments. Moreover, the consistency and limiting distribution of the TSLS estimator are established when both N and T tend to infinity. Some asymptotically pivotal tests are extended to a longitudinal data model and their asymptotic properties are examined. A Monte Carlo experiment is conducted to evaluate the finite sample performance of the proposed estimators. Journal: Econometric Reviews Pages: 361-389 Issue: 4 Volume: 31 Year: 2012 X-DOI: 10.1080/07474938.2011.607356 File-URL: http://hdl.handle.net/10.1080/07474938.2011.607356 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:31:y:2012:i:4:p:361-389 Template-Type: ReDIF-Article 1.0 Author-Name: Chihwa Kao Author-X-Name-First: Chihwa Author-X-Name-Last: Kao Author-Name: Lorenzo Trapani Author-X-Name-First: Lorenzo Author-X-Name-Last: Trapani Author-Name: Giovanni Urga Author-X-Name-First: Giovanni Author-X-Name-Last: Urga Title: Asymptotics for Panel Models with Common Shocks Abstract: This article develops a novel asymptotic theory for panel models with common shocks. We assume that contemporaneous correlation can be generated by both the presence of common regressors among units and weak spatial dependence among the error terms. Several characteristics of the panel are considered: cross-sectional and time-series dimensions can either be fixed or large; factors can either be observable or unobservable; the factor model can describe either a cointegration relationship or a spurious regression, and we also consider the stationary case. We derive the rate of convergence and the limit distributions for the ordinary least square (OLS) estimates of the model parameters under all the aforementioned cases. Journal: Econometric Reviews Pages: 390-439 Issue: 4 Volume: 31 Year: 2012 X-DOI: 10.1080/07474938.2011.607991 File-URL: http://hdl.handle.net/10.1080/07474938.2011.607991 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:31:y:2012:i:4:p:390-439 Template-Type: ReDIF-Article 1.0 Author-Name: J. Arteche Author-X-Name-First: J. Author-X-Name-Last: Arteche Title: Semiparametric Inference in Correlated Long Memory Signal Plus Noise Models Abstract: This article proposes an extension of the log periodogram regression in perturbed long memory series that accounts for the added noise, while also allowing for correlation between signal and noise, a common situation in many economic and financial series. Consistency (for d < 1) and asymptotic normality (for d < 3/4) are shown with the same bandwidth restriction as required for the original log periodogram regression in a fully observable series, with the corresponding gain in asymptotic efficiency and faster convergence over competitors. Local Wald, Lagrange Multiplier, and Hausman type tests of the hypothesis of no correlation between the latent signal and noise are also proposed. Journal: Econometric Reviews Pages: 440-474 Issue: 4 Volume: 31 Year: 2012 X-DOI: 10.1080/07474938.2011.607996 File-URL: http://hdl.handle.net/10.1080/07474938.2011.607996 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:31:y:2012:i:4:p:440-474 Template-Type: ReDIF-Article 1.0 Author-Name: Saralees Nadarajah Author-X-Name-First: Saralees Author-X-Name-Last: Nadarajah Author-Name: Mahdi Teimouri Author-X-Name-First: Mahdi Author-X-Name-Last: Teimouri Title: On the Characteristic Function for Asymmetric Exponential Power Distributions Abstract: The econometric literature has seen a surge of developments in the theory and applications of asymmetric exponential power distributions (AEPDs). Here, for the first time, we derive explicit closed form expressions for the characteristic function of AEPDs. The expressions involve the complex parameter Wright generalized hypergeometric function. Journal: Econometric Reviews Pages: 475-481 Issue: 4 Volume: 31 Year: 2012 X-DOI: 10.1080/07474938.2011.608000 File-URL: http://hdl.handle.net/10.1080/07474938.2011.608000 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:31:y:2012:i:4:p:475-481 Template-Type: ReDIF-Article 1.0 Author-Name: Xuexin Wang Author-X-Name-First: Xuexin Author-X-Name-Last: Wang Title: A general approach to conditional moment specification testing with projections Abstract: This article develops a general approach for model specification analysis within the conditional moment specification testing framework. The new methodology removes the non-negligible estimation effect of test statistic via a projection-based transformation, exploiting the nature of conditional moment specification testing. That is, the conditional moment restrictions, which are implicitly defined in conditional moment testing framework, not only imply the unconditional moment restrictions we are testing, but also many other unconditional moment restrictions. This approach is robust to departures from the distributional assumptions that are not being tested; moreover, only a preliminary \begin{equation}{\sqrt {T}}\end{equation} T-consistent estimator is needed, and the transformation is asymptotically distribution free. Furthermore, the transformed statistic reaches asymptotic efficiency in the sense of generalized method of moments (GMM) estimation. In some specific alternatives, we establish the optimal tests. We apply the methodology to test the adequacy and nonlinearity of the generalized autoregressive conditional heteroskedasticity (GARCH) models. Finally, an application to the S&P 500 daily data highlights the merits of our approach. Journal: Econometric Reviews Pages: 140-165 Issue: 2 Volume: 37 Year: 2018 Month: 2 X-DOI: 10.1080/07474938.2015.1032165 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1032165 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:2:p:140-165 Template-Type: ReDIF-Article 1.0 Author-Name: Koji Miyawaki Author-X-Name-First: Koji Author-X-Name-Last: Miyawaki Author-Name: Yasuhiro Omori Author-X-Name-First: Yasuhiro Author-X-Name-Last: Omori Author-Name: Akira Hibiki Author-X-Name-First: Akira Author-X-Name-Last: Hibiki Title: A discrete/continuous choice model on a nonconvex budget set Abstract: Decreasing block rate pricing is a nonlinear price system often used for public utility services. Residential gas services in Japan and the United Kingdom are provided under this price schedule. The discrete/continuous choice approach is used to analyze the demand under decreasing block rate pricing. However, the nonlinearity problem, which has not been examined in previous studies, arises because a consumer’s budget set (a set of affordable consumption amounts) is nonconvex, and hence, the resulting model includes highly nonlinear functions. To address this problem, we propose a feasible, efficient method of demand estimation on the nonconvex budget. The advantages of our method are as follows: (i) the construction of an Markov chain Monte Carlo algorithm with an efficient blanket based on the Hermite–Hadamard integral inequality and the power-mean inequality, (ii) the explicit consideration of the (highly nonlinear) separability condition, which often makes numerical likelihood maximization difficult, and (iii) the introduction of normal disturbance into the discrete/continuous choice model on the nonconvex budget set. The proposed method is applied to estimate the Japanese residential gas demand function and evaluate the effect of price schedule changes as a policy experiment. Journal: Econometric Reviews Pages: 89-113 Issue: 2 Volume: 37 Year: 2018 Month: 2 X-DOI: 10.1080/07474938.2015.1032166 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1032166 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:2:p:89-113 Template-Type: ReDIF-Article 1.0 Author-Name: Stanislav Anatolyev Author-X-Name-First: Stanislav Author-X-Name-Last: Anatolyev Author-Name: Nikita Kobotaev Author-X-Name-First: Nikita Author-X-Name-Last: Kobotaev Title: Modeling and forecasting realized covariance matrices with accounting for leverage Abstract: The existing dynamic models for realized covariance matrices do not account for an asymmetry with respect to price directions. We modify the recently proposed conditional autoregressive Wishart (CAW) model to allow for the leverage effect. In the conditional threshold autoregressive Wishart (CTAW) model and its variations the parameters governing each asset's volatility and covolatility dynamics are subject to switches that depend on signs of previous asset returns or previous market returns. We evaluate the predictive ability of the CTAW model and its restricted and extended specifications from both statistical and economic points of view. We find strong evidence that many CTAW specifications have a better in-sample fit and tend to have a better out-of-sample predictive ability than the original CAW model and its modifications. Journal: Econometric Reviews Pages: 114-139 Issue: 2 Volume: 37 Year: 2018 Month: 2 X-DOI: 10.1080/07474938.2015.1035165 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1035165 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:2:p:114-139 Template-Type: ReDIF-Article 1.0 Author-Name: Francisco Blasques Author-X-Name-First: Francisco Author-X-Name-Last: Blasques Author-Name: André Lucas Author-X-Name-First: André Author-X-Name-Last: Lucas Author-Name: Erkki Silde Author-X-Name-First: Erkki Author-X-Name-Last: Silde Title: A stochastic recurrence equations approach for score driven correlation models Abstract: We describe stationarity and ergodicity (SE) regions for a recently proposed class of score driven dynamic correlation models. These models have important applications in empirical work. The regions are derived from sufficiency conditions in Bougerol (1993) and take a nonstandard form. We show that the nonstandard shape of the sufficiency regions cannot be avoided by reparameterizing the model or by rescaling the score steps in the transition equation for the correlation parameter. This makes the result markedly different from the volatility case. Observationally equivalent decompositions of the stochastic recurrence equation yield regions with different shapes and sizes. We use these results to establish the consistency and asymptotic normality of the maximum likelihood estimator. We illustrate our results with an analysis of time-varying correlations between U.K. and Greek equity indices. We find that also in empirical applications different decompositions can give rise to different conclusions regarding the stability of the estimated model. Journal: Econometric Reviews Pages: 166-181 Issue: 2 Volume: 37 Year: 2018 Month: 2 X-DOI: 10.1080/07474938.2016.1139821 File-URL: http://hdl.handle.net/10.1080/07474938.2016.1139821 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:2:p:166-181 Template-Type: ReDIF-Article 1.0 Author-Name: Yoshimasa Uematsu Author-X-Name-First: Yoshimasa Author-X-Name-Last: Uematsu Title: Nonstationary nonlinear quantile regression Abstract: This study examines estimation and inference based on quantile regression for parametric nonlinear models with an integrated time series covariate. We first derive the limiting distribution of the nonlinear quantile regression estimator and then consider testing for parameter restrictions, when the regression function is specified as an asymptotically homogeneous function. We also study linear-in-parameter regression models when the regression function is given by integrable regression functions as well as asymptotically homogeneous regression functions. We, furthermore, propose a fully modified estimator to reduce the bias in the original estimator under a certain set of conditions. Finally, simulation studies show that the estimators behave well, especially when the regression error term has a fat-tailed distribution. Journal: Econometric Reviews Pages: 386-416 Issue: 4 Volume: 38 Year: 2019 Month: 4 X-DOI: 10.1080/07474938.2017.1308056 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1308056 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:4:p:386-416 Template-Type: ReDIF-Article 1.0 Author-Name: Xiaodong Liu Author-X-Name-First: Xiaodong Author-X-Name-Last: Liu Author-Name: Paulo Saraiva Author-X-Name-First: Paulo Author-X-Name-Last: Saraiva Title: GMM estimation of spatial autoregressive models in a system of simultaneous equations with heteroskedasticity Abstract: This paper proposes a GMM estimation framework for the SAR model in a system of simultaneous equations with heteroskedastic disturbances. Besides linear moment conditions, the proposed GMM estimator also utilizes quadratic moment conditions based on the covariance structure of model disturbances within and across equations. Compared with the QML approach, the GMM estimator is easier to implement and robust under heteroskedasticity of unknown form. We derive the heteroskedasticity-robust standard error for the GMM estimator. Monte Carlo experiments show that the proposed GMM estimator performs well in finite samples. Journal: Econometric Reviews Pages: 359-385 Issue: 4 Volume: 38 Year: 2019 Month: 4 X-DOI: 10.1080/07474938.2017.1308087 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1308087 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:4:p:359-385 Template-Type: ReDIF-Article 1.0 Author-Name: Liangjun Su Author-X-Name-First: Liangjun Author-X-Name-Last: Su Author-Name: Pai Xu Author-X-Name-First: Pai Author-X-Name-Last: Xu Title: Common threshold in quantile regressions with an application to pricing for reputation Abstract: The paper develops a systematic estimation and inference procedure for quantile regression models where there may exist a common threshold effect across different quantile indices. We first propose a sup-Wald test for the existence of a threshold effect, and then study the asymptotic properties of the estimators in a threshold quantile regression model under the shrinking threshold effect framework. We consider several tests for the presence of a common threshold value across different quantile indices and obtain their limiting distributions. We apply our methodology to study the pricing strategy for reputation through the use of a data set from Taobao.com. In our economic model, an online seller maximizes the sum of the profit from current sales and the possible future gain from a targeted higher reputation level. We show that the model can predict a jump in optimal pricing behavior, which is considered as “reputation effect” in this paper. The use of threshold quantile regression model allows us to identify and explore the reputation effect and its heterogeneity in data. We find both reputation effects and common thresholds for a range of quantile indices in seller’s pricing strategy in our application. Journal: Econometric Reviews Pages: 417-450 Issue: 4 Volume: 38 Year: 2019 Month: 4 X-DOI: 10.1080/07474938.2017.1318469 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1318469 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:4:p:417-450 Template-Type: ReDIF-Article 1.0 Author-Name: Sivagowry Sriananthakumar Author-X-Name-First: Sivagowry Author-X-Name-Last: Sriananthakumar Title: Using point optimal test of a simple null hypothesis for testing a composite null hypothesis via maximized Monte Carlo approach Abstract: King’s Point Optimal (PO) test of a simple null hypothesis is useful in a number of ways, for example it can be used to trace the power envelope against which existing tests can be compared. However, this test cannot always be constructed when testing a composite null hypothesis. It is suggested in the literature that approximate PO (APO) tests can overcome this problem, but they also have some drawbacks. This paper investigates if King’s PO test can be used for testing a composite null in the presence of nuisance parameters via a maximized Monte Carlo (MMC) approach, with encouraging results. Journal: Econometric Reviews Pages: 451-464 Issue: 4 Volume: 38 Year: 2019 Month: 4 X-DOI: 10.1080/07474938.2017.1382781 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1382781 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:4:p:451-464 Template-Type: ReDIF-Article 1.0 Author-Name: Arnaud Dufays Author-X-Name-First: Arnaud Author-X-Name-Last: Dufays Author-Name: Jeroen V. K. Rombouts Author-X-Name-First: Jeroen V. K. Author-X-Name-Last: Rombouts Title: Sparse Change-point HAR Models for Realized Variance Abstract: Change-point time series specifications constitute flexible models that capture unknown structural changes by allowing for switches in the model parameters. Nevertheless most models suffer from an over-parametrization issue since typically only one latent state variable drives the switches in all parameters. This implies that all parameters have to change when a break happens. To gauge whether and where there are structural breaks in realized variance, we introduce the sparse change-point HAR model. The approach controls for model parsimony by limiting the number of parameters which evolve from one regime to another. Sparsity is achieved thanks to employing a nonstandard shrinkage prior distribution. We derive a Gibbs sampler for inferring the parameters of this process. Simulation studies illustrate the excellent performance of the sampler. Relying on this new framework, we study the stability of the HAR model using realized variance series of several major international indices between January 2000 and August 2015. Journal: Econometric Reviews Pages: 857-880 Issue: 8 Volume: 38 Year: 2019 Month: 9 X-DOI: 10.1080/07474938.2018.1454366 File-URL: http://hdl.handle.net/10.1080/07474938.2018.1454366 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:8:p:857-880 Template-Type: ReDIF-Article 1.0 Author-Name: Roberto León-González Author-X-Name-First: Roberto Author-X-Name-Last: León-González Title: Efficient Bayesian inference in generalized inverse gamma processes for stochastic volatility Abstract: This paper develops a novel and efficient algorithm for Bayesian inference in inverse Gamma stochastic volatility models. It is shown that by conditioning on auxiliary variables, it is possible to sample all the volatilities jointly directly from their posterior conditional density, using simple and easy to draw from distributions. Furthermore, this paper develops a generalized inverse gamma process with more flexible tails in the distribution of volatilities, which still allows for simple and efficient calculations. Using several macroeconomic and financial datasets, it is shown that the inverse gamma and generalized inverse gamma processes can greatly outperform the commonly used log normal volatility processes with Student’s t errors or jumps in the mean equation. Journal: Econometric Reviews Pages: 899-920 Issue: 8 Volume: 38 Year: 2019 Month: 9 X-DOI: 10.1080/07474938.2018.1485614 File-URL: http://hdl.handle.net/10.1080/07474938.2018.1485614 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:8:p:899-920 Template-Type: ReDIF-Article 1.0 Author-Name: Takahide Yanagi Author-X-Name-First: Takahide Author-X-Name-Last: Yanagi Title: Inference on local average treatment effects for misclassified treatment Abstract: We develop point-identification for the local average treatment effect when the binary treatment contains a measurement error. The standard instrumental variable estimator is inconsistent for the parameter since the measurement error is nonclassical by construction. We correct the problem by identifying the distribution of the measurement error based on the use of an exogenous variable that can even be a binary covariate. The moment conditions derived from the identification lead to generalized method of moments estimation with asymptotically valid inferences. Monte Carlo simulations and an empirical illustration demonstrate the usefulness of the proposed procedure. Journal: Econometric Reviews Pages: 938-960 Issue: 8 Volume: 38 Year: 2019 Month: 9 X-DOI: 10.1080/07474938.2018.1485833 File-URL: http://hdl.handle.net/10.1080/07474938.2018.1485833 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:8:p:938-960 Template-Type: ReDIF-Article 1.0 Author-Name: Xiaodong Liu Author-X-Name-First: Xiaodong Author-X-Name-Last: Liu Title: Simultaneous equations with binary outcomes and social interactions Abstract: This paper introduces a discrete-choice simultaneous-equation social interaction model. We provide a microfoundation for the econometric model by considering an incomplete information game where individuals interact in multiple activities through a network. We characterize the sufficient condition for the existence of a unique BNE of the game. We discuss the identification of the econometric model and propose a two-stage estimation procedure, where the reduced form parameters are estimated by the NPL algorithm in the first stage and the structural parameters are recovered from the estimated reduced form parameters by the AGLS estimator in the second stage. Monte Carlo experiments show that the proposed estimation procedure performs well in finite samples and remains computationally feasible when networks are large. We also provide an empirical example to illustrate the empirical relevance of the proposed model. Journal: Econometric Reviews Pages: 921-937 Issue: 8 Volume: 38 Year: 2019 Month: 9 X-DOI: 10.1080/07474938.2018.1485836 File-URL: http://hdl.handle.net/10.1080/07474938.2018.1485836 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:8:p:921-937 Template-Type: ReDIF-Article 1.0 Author-Name: Chaohua Dong Author-X-Name-First: Chaohua Author-X-Name-Last: Dong Author-Name: Jiti Gao Author-X-Name-First: Jiti Author-X-Name-Last: Gao Author-Name: Bin Peng Author-X-Name-First: Bin Author-X-Name-Last: Peng Title: Estimation in a semiparametric panel data model with nonstationarity Abstract: In this paper, we consider a partially linear panel data model with nonstationarity and certain cross-sectional dependence. Accounting for the explosive feature of the nonstationary time series, we particularly employ Hermite orthogonal functions in this study. Under a general spatial error dependence structure, we then establish some consistent closed-form estimates for both the unknown parameters and the unknown functions for the cases where N and T go jointly to infinity. Rates of convergence and asymptotic normalities are established for the proposed estimators. Both the finite sample performance and the empirical applications show that the proposed estimation methods work well. Journal: Econometric Reviews Pages: 961-977 Issue: 8 Volume: 38 Year: 2019 Month: 9 X-DOI: 10.1080/07474938.2018.1514021 File-URL: http://hdl.handle.net/10.1080/07474938.2018.1514021 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:8:p:961-977 Template-Type: ReDIF-Article 1.0 Author-Name: Josep Lluís Carrion-i-Silvestre Author-X-Name-First: Josep Lluís Author-X-Name-Last: Carrion-i-Silvestre Author-Name: Dukpa Kim Author-X-Name-First: Dukpa Author-X-Name-Last: Kim Title: Quasi-likelihood ratio tests for cointegration, cobreaking, and cotrending Abstract: We consider a set of variables with two types of nonstationary features, stochastic trends and broken linear trends. We develop tests that can determine whether there is a linear combination of these variables under which the nonstationary features can be canceled out. The first test can determine whether stochastic trends can be eliminated and thus whether cointegration holds, regardless of whether structural breaks in linear trends are eliminated. The second test can determine whether both stochastic trends and breaks in linear trends are simultaneously removed and thus whether cointegration and cobreaking simultaneously hold. The third test can determine whether not only breaks in linear trends but also linear trends themselves are eliminated along with stochastic trends and thus whether both cointegration and cotrending hold. Journal: Econometric Reviews Pages: 881-898 Issue: 8 Volume: 38 Year: 2019 Month: 9 X-DOI: 10.1080/07474938.2018.1528416 File-URL: http://hdl.handle.net/10.1080/07474938.2018.1528416 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:8:p:881-898 Template-Type: ReDIF-Article 1.0 Author-Name: Laszlo Balazsi Author-X-Name-First: Laszlo Author-X-Name-Last: Balazsi Author-Name: Laszlo Matyas Author-X-Name-First: Laszlo Author-X-Name-Last: Matyas Author-Name: Tom Wansbeek Author-X-Name-First: Tom Author-X-Name-Last: Wansbeek Title: The estimation of multidimensional fixed effects panel data models Abstract: This article introduces the appropriate within estimators for the most frequently used three-dimensional fixed effects panel data models. It analyzes the behavior of these estimators in the cases of no self-flow data, unbalanced data, and dynamic autoregressive models. The main results are then generalized for higher dimensional panel data sets as well. Journal: Econometric Reviews Pages: 212-227 Issue: 3 Volume: 37 Year: 2018 Month: 3 X-DOI: 10.1080/07474938.2015.1032164 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1032164 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:3:p:212-227 Template-Type: ReDIF-Article 1.0 Author-Name: D. S. G. Pollock Author-X-Name-First: D. S. G. Author-X-Name-Last: Pollock Title: Trends cycles and seasons: Econometric methods of signal extraction Abstract: Alternative methods of trend extraction and of seasonal adjustment are described that operate in the time domain and in the frequency domain.The time-domain methods that are implemented in the TRAMO–SEATS and the STAMP programs are compared. An abbreviated time-domain method of seasonal adjustment that is implemented in the IDEOLOG program is also presented. Finite-sample versions of the Wiener–Kolmogorov filter are described that can be used to implement the methods in a common way.The frequency-domain method, which is also implemented in the IDEOLOG program, employs an ideal frequency selective filter that depends on identifying the ordinates of the Fourier transform of a detrended data sequence that should lie in the pass band of the filter and those that should lie in its stop band. Filters of this nature can be used both for extracting a low-frequency cyclical component of the data and for extracting the seasonal component. Journal: Econometric Reviews Pages: 228-246 Issue: 3 Volume: 37 Year: 2018 Month: 3 X-DOI: 10.1080/07474938.2015.1033218 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1033218 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:3:p:228-246 Template-Type: ReDIF-Article 1.0 Author-Name: William C. Horrace Author-X-Name-First: William C. Author-X-Name-Last: Horrace Author-Name: Christopher F. Parmeter Author-X-Name-First: Christopher F. Author-X-Name-Last: Parmeter Title: A Laplace stochastic frontier model Abstract: We propose a Laplace stochastic frontier model as an alternative to the traditional model with normal errors. An interesting feature of the Laplace model is that the distribution of inefficiency conditional on the composed error is constant for positive values of the composed error, but varies for negative values. A simulation study suggests that the model performs well relative to the normal-exponential model when the two-sided error is misspecified. An application to U.S. Airlines is provided. Journal: Econometric Reviews Pages: 260-280 Issue: 3 Volume: 37 Year: 2018 Month: 3 X-DOI: 10.1080/07474938.2015.1059715 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1059715 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:3:p:260-280 Template-Type: ReDIF-Article 1.0 Author-Name: Tomohiro Ando Author-X-Name-First: Tomohiro Author-X-Name-Last: Ando Author-Name: Jushan Bai Author-X-Name-First: Jushan Author-X-Name-Last: Bai Title: Selecting the regularization parameters in high-dimensional panel data models: Consistency and efficiency Abstract: This article considers panel data models in the presence of a large number of potential predictors and unobservable common factors. The model is estimated by the regularization method together with the principal components procedure. We propose a panel information criterion for selecting the regularization parameter and the number of common factors under a diverging number of predictors. Under the correct model specification, we show that the proposed criterion consistently identifies the true model. If the model is instead misspecified, the proposed criterion achieves asymptotically efficient model selection. Simulation results confirm these theoretical arguments. Journal: Econometric Reviews Pages: 183-211 Issue: 3 Volume: 37 Year: 2018 Month: 3 X-DOI: 10.1080/07474938.2015.1092822 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1092822 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:3:p:183-211 Template-Type: ReDIF-Article 1.0 Author-Name: S. M. Hatefi Author-X-Name-First: S. M. Author-X-Name-Last: Hatefi Author-Name: S. A. Torabi Author-X-Name-First: S. A. Author-X-Name-Last: Torabi Title: A slack analysis framework for improving composite indicators with applications to human development and sustainable energy indices Abstract: Data envelopment analysis models are used for measuring composite indicators in various areas. Although there are many models for measuring composite indicators in the literature, surprisingly, there is no methodology that clearly shows how composite indicators improvement could be performed. This article proposes a slack analysis framework for improving the composite indicator of inefficient entities. For doing so, two dual problems originated from two data envelopment analysis models in the literature are proposed, which can guide decision makers on how to adjust the subindicators of inefficient entities to improve their composite indicators through identifying which subindicators must be improved and how much they should be augmented. The proposed methodology for improving composite indicators is inspired from data envelopment analysis and slack analysis approaches. Applicability of the proposed methodology is investigated for improving two well-known composite indicators, i.e., Sustainable Energy Index and Human Development Index. The results show that 12 out of 18 economies are inefficient in the context of sustainable energy index, for which the proposed slack analysis models provide the suggested adjustments in terms of their respected subindicators. Furthermore, the proposed methodology suggests how to adjust the life expectancy, the education, and the gross domestic product (GDP) as the three socioeconomic indicators to improve the human development index of 24 countries which are identified as inefficient entities among 27 countries. Journal: Econometric Reviews Pages: 247-259 Issue: 3 Volume: 37 Year: 2018 Month: 3 X-DOI: 10.1080/07474938.2016.1140286 File-URL: http://hdl.handle.net/10.1080/07474938.2016.1140286 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:3:p:247-259 Template-Type: ReDIF-Article 1.0 Author-Name: Stanislav Anatolyev Author-X-Name-First: Stanislav Author-X-Name-Last: Anatolyev Author-Name: Nikolay Gospodinov Author-X-Name-First: Nikolay Author-X-Name-Last: Gospodinov Title: Multivariate Return Decomposition: Theory and Implications Abstract: In this paper, we propose a model based on multivariate decomposition of multiplicative – absolute values and signs – components of asset returns. In the m-variate case, the marginals for the m absolute values and the binary marginals for the m directions are linked through a 2m-dimensional copula. The approach is detailed in the case of a bivariate decomposition. We outline the construction of the likelihood function and the computation of different conditional measures. The finite-sample properties of the maximum likelihood estimator are assessed by simulation. An application to predicting bond returns illustrates the usefulness of the proposed method. Journal: Econometric Reviews Pages: 487-508 Issue: 5 Volume: 38 Year: 2019 Month: 5 X-DOI: 10.1080/07474938.2017.1348677 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1348677 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:5:p:487-508 Template-Type: ReDIF-Article 1.0 Author-Name: Ricardo Mora Author-X-Name-First: Ricardo Author-X-Name-Last: Mora Author-Name: Iliana Reggio Author-X-Name-First: Iliana Author-X-Name-Last: Reggio Title: Alternative diff-in-diffs estimators with several pretreatment periods Abstract: This paper deals with the identification of treatment effects using difference-in-differences estimators when several pretreatment periods are available. We define a family of identifying nonnested assumptions that lead to alternative difference-in-differences estimators. We show that the most usual difference-in-differences estimators imply equivalence conditions for the identifying nonnested assumptions. We further propose a model that can be used to test multiple equivalence conditions without imposing any of them. We conduct a Monte Carlo analysis and apply our approach to several recent papers to show its practical relevance. Journal: Econometric Reviews Pages: 465-486 Issue: 5 Volume: 38 Year: 2019 Month: 5 X-DOI: 10.1080/07474938.2017.1348683 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1348683 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:5:p:465-486 Template-Type: ReDIF-Article 1.0 Author-Name: Giuseppe Cavaliere Author-X-Name-First: Giuseppe Author-X-Name-Last: Cavaliere Author-Name: Anton Skrobotov Author-X-Name-First: Anton Author-X-Name-Last: Skrobotov Author-Name: A. M. Robert Taylor Author-X-Name-First: A. M. Robert Author-X-Name-Last: Taylor Title: Wild bootstrap seasonal unit root tests for time series with periodic nonstationary volatility Abstract: We investigate the behavior of the well-known Hylleberg, Engle, Granger and Yoo (HEGY) regression-based seasonal unit root tests in cases where the driving shocks can display periodic nonstationary volatility and conditional heteroskedasticity. Our set up allows for periodic heteroskedasticity, nonstationary volatility and (seasonal) generalized autoregressive-conditional heteroskedasticity as special cases. We show that the limiting null distributions of the HEGY tests depend, in general, on nuisance parameters which derive from the underlying volatility process. Monte Carlo simulations show that the standard HEGY tests can be substantially oversized in the presence of such effects. As a consequence, we propose wild bootstrap implementations of the HEGY tests. Two possible wild bootstrap resampling schemes are discussed, both of which are shown to deliver asymptotically pivotal inference under our general conditions on the shocks. Simulation evidence is presented which suggests that our proposed bootstrap tests perform well in practice, largely correcting the size problems seen with the standard HEGY tests even under extreme patterns of heteroskedasticity, yet not losing finite sample relative to the standard HEGY tests. Journal: Econometric Reviews Pages: 509-532 Issue: 5 Volume: 38 Year: 2019 Month: 5 X-DOI: 10.1080/07474938.2017.1348684 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1348684 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:5:p:509-532 Template-Type: ReDIF-Article 1.0 Author-Name: Qiang Chen Author-X-Name-First: Qiang Author-X-Name-Last: Chen Author-Name: Meidi Hu Author-X-Name-First: Meidi Author-X-Name-Last: Hu Author-Name: Xiaojun Song Author-X-Name-First: Xiaojun Author-X-Name-Last: Song Title: A nonparametric specification test for the volatility functions of diffusion processes Abstract: This paper develops a new test for the parametric volatility function of a diffusion model based on nonparametric estimation techniques. The proposed test imposes no restriction on the functional form of the drift function and has an asymptotically standard normal distribution under the null hypothesis of correct specification. It is consistent against any fixed alternatives and has nontrivial asymptotic power against a class of local alternatives with proper rates. Monte Carlo simulations show that the test performs well in finite samples and generally has better power performance than the nonparametric test of Li (2007) and the stochastic process-based tests of Dette and Podolskij (2008). When applying the test to high frequency data of EUR/USD exchange rate, the empirical results show that the commonly used volatility functions fit more poorly when the data frequency becomes higher, and the general volatility functions fit relatively better than the constant volatility function. Journal: Econometric Reviews Pages: 557-576 Issue: 5 Volume: 38 Year: 2019 Month: 5 X-DOI: 10.1080/07474938.2017.1365428 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1365428 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:5:p:557-576 Template-Type: ReDIF-Article 1.0 Author-Name: M. Victoria Caballero-Pintado Author-X-Name-First: M. Victoria Author-X-Name-Last: Caballero-Pintado Author-Name: Mariano Matilla-García Author-X-Name-First: Mariano Author-X-Name-Last: Matilla-García Author-Name: Manuel Ruiz Marín Author-X-Name-First: Manuel Ruiz Author-X-Name-Last: Marín Title: Symbolic correlation integral Abstract: This paper aims to introduce the concept of symbolic correlation integral SC that is extensively used in many scientific fields. The new correlation integral SC avoids the noisy parameter 𝜀 of the classical correlation integral, defined by Grassberger and Procaccia (1983) and extensively used for constructing correlation-integral-based statistics, as in the BDS test. Once the free parameter 𝜀 disappears, it is possible to construct a nonparametric powerful test for independence that can also be used as a diagnostic tool for model selection. The symbolic correlation integral is also extended to deal with multivariate models, and a test for causality is proposed as an example of the theoretical power of the new concept. With extensive Monte Carlo simulations, the paper shows the good size and power performance of symbolic correlation-integral-based tests. Journal: Econometric Reviews Pages: 533-556 Issue: 5 Volume: 38 Year: 2019 Month: 5 X-DOI: 10.1080/07474938.2017.1365431 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1365431 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:5:p:533-556 Template-Type: ReDIF-Article 1.0 Author-Name: Joachim Freyberger Author-X-Name-First: Joachim Author-X-Name-Last: Freyberger Author-Name: Matthew A. Masten Author-X-Name-First: Matthew A. Author-X-Name-Last: Masten Title: A practical guide to compact infinite dimensional parameter spaces Abstract: Compactness is a widely used assumption in econometrics. In this article, we gather and review general compactness results for many commonly used parameter spaces in nonparametric estimation, and we provide several new results. We consider three kinds of functions: (1) functions with bounded domains which satisfy standard norm bounds, (2) functions with bounded domains which do not satisfy standard norm bounds, and (3) functions with unbounded domains. In all three cases, we provide two kinds of results, compact embedding and closedness, which together allow one to show that parameter spaces defined by a ||·||s-norm bound are compact under a norm ||·||c. We illustrate how the choice of norms affects the parameter space, the strength of the conclusions, as well as other regularity conditions in two common settings: nonparametric mean regression and nonparametric instrumental variables estimation. Journal: Econometric Reviews Pages: 979-1006 Issue: 9 Volume: 38 Year: 2019 Month: 10 X-DOI: 10.1080/07474938.2018.1514025 File-URL: http://hdl.handle.net/10.1080/07474938.2018.1514025 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:9:p:979-1006 Template-Type: ReDIF-Article 1.0 Author-Name: Audronė Virbickaitė Author-X-Name-First: Audronė Author-X-Name-Last: Virbickaitė Author-Name: Hedibert F. Lopes Author-X-Name-First: Hedibert F. Author-X-Name-Last: Lopes Author-Name: M. Concepción Ausín Author-X-Name-First: M. Author-X-Name-Last: Concepción Ausín Author-Name: Pedro Galeano Author-X-Name-First: Pedro Author-X-Name-Last: Galeano Title: Particle learning for Bayesian semi-parametric stochastic volatility model Abstract: This article designs a Sequential Monte Carlo (SMC) algorithm for estimation of Bayesian semi-parametric Stochastic Volatility model for financial data. In particular, it makes use of one of the most recent particle filters called Particle Learning (PL). SMC methods are especially well suited for state-space models and can be seen as a cost-efficient alternative to Markov Chain Monte Carlo (MCMC), since they allow for online type inference. The posterior distributions are updated as new data is observed, which is exceedingly costly using MCMC. Also, PL allows for consistent online model comparison using sequential predictive log Bayes factors. A simulated data is used in order to compare the posterior outputs for the PL and MCMC schemes, which are shown to be almost identical. Finally, a short real data application is included. Journal: Econometric Reviews Pages: 1007-1023 Issue: 9 Volume: 38 Year: 2019 Month: 10 X-DOI: 10.1080/07474938.2018.1514022 File-URL: http://hdl.handle.net/10.1080/07474938.2018.1514022 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:9:p:1007-1023 Template-Type: ReDIF-Article 1.0 Author-Name: Artem Prokhorov Author-X-Name-First: Artem Author-X-Name-Last: Prokhorov Author-Name: Ulf Schepsmeier Author-X-Name-First: Ulf Author-X-Name-Last: Schepsmeier Author-Name: Yajing Zhu Author-X-Name-First: Yajing Author-X-Name-Last: Zhu Title: Generalized information matrix tests for copulas Abstract: We propose a family of goodness-of-fit tests for copulas. The tests use generalizations of the information matrix (IM) equality of White and so relate to the copula test proposed by Huang and Prokhorov. The idea is that eigenspectrum-based statements of the IM equality reduce the degrees of freedom of the test’s asymptotic distribution and lead to better size-power properties, even in high dimensions. The gains are especially pronounced for vine copulas, where additional benefits come from simplifications of score functions and the Hessian. We derive the asymptotic distribution of the generalized tests, accounting for the nonparametric estimation of the marginals and apply a parametric bootstrap procedure, valid when asymptotic critical values are inaccurate. In Monte Carlo simulations, we study the behavior of the new tests, compare them with several Cramer–von Mises type tests and confirm the desired properties of the new tests in high dimensions. Journal: Econometric Reviews Pages: 1024-1054 Issue: 9 Volume: 38 Year: 2019 Month: 10 X-DOI: 10.1080/07474938.2018.1514023 File-URL: http://hdl.handle.net/10.1080/07474938.2018.1514023 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:9:p:1024-1054 Template-Type: ReDIF-Article 1.0 Author-Name: Kazuhiko Hayakawa Author-X-Name-First: Kazuhiko Author-X-Name-Last: Hayakawa Author-Name: Meng Qi Author-X-Name-First: Meng Author-X-Name-Last: Qi Author-Name: Jörg Breitung Author-X-Name-First: Jörg Author-X-Name-Last: Breitung Title: Double filter instrumental variable estimation of panel data models with weakly exogenous variables Abstract: In this article, we propose instrumental variables (IV) and generalized method of moments (GMM) estimators for panel data models with weakly exogenous variables. The model is allowed to include heterogeneous time trends besides the standard fixed effects (FE). The proposed IV and GMM estimators are obtained by applying a forward filter to the model and a backward filter to the instruments in order to remove FE, thereby called the double filter IV and GMM estimators. We derive the asymptotic properties of the proposed estimators under fixed T and large N, and large T and large N asymptotics where N and T denote the dimensions of cross section and time series, respectively. It is shown that the proposed IV estimator has the same asymptotic distribution as the bias corrected FE estimator when both N and T are large. Monte Carlo simulation results reveal that the proposed estimator performs well in finite samples and outperforms the conventional IV/GMM estimators using instruments in levels in many cases. Journal: Econometric Reviews Pages: 1055-1088 Issue: 9 Volume: 38 Year: 2019 Month: 10 X-DOI: 10.1080/07474938.2018.1514024 File-URL: http://hdl.handle.net/10.1080/07474938.2018.1514024 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:9:p:1055-1088 Template-Type: ReDIF-Article 1.0 Author-Name: Stephan Smeekes Author-X-Name-First: Stephan Author-X-Name-Last: Smeekes Author-Name: Joakim Westerlund Author-X-Name-First: Joakim Author-X-Name-Last: Westerlund Title: Robust block bootstrap panel predictability tests Abstract: This article develops two block bootstrap-based panel predictability test procedures that are valid under very general conditions. Some of the allowable features include cross-sectional dependence, heterogeneous predictive slopes, persistent predictors, and complex error dynamics, including cross-unit endogeneity. While the first test procedure tests if there is any predictability at all, the second procedure determines the units for which predictability holds in case of a rejection by the first. A weak unit root framework is adopted to allow persistent predictors, and a novel theory is developed to establish asymptotic validity of the proposed bootstrap. Simulations are used to evaluate the performance of our tests in small samples, and their implementation is illustrated through an empirical application to stock returns. Journal: Econometric Reviews Pages: 1089-1107 Issue: 9 Volume: 38 Year: 2019 Month: 10 X-DOI: 10.1080/07474938.2018.1536102 File-URL: http://hdl.handle.net/10.1080/07474938.2018.1536102 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:9:p:1089-1107 Template-Type: ReDIF-Article 1.0 Author-Name: In Choi Author-X-Name-First: In Author-X-Name-Last: Choi Author-Name: Hanbat Jeong Author-X-Name-First: Hanbat Author-X-Name-Last: Jeong Title: Model selection for factor analysis: Some new criteria and performance comparisons Abstract: This paper derives Akaike information criterion (AIC), corrected AIC, the Bayesian information criterion (BIC) and Hannan and Quinn’s information criterion for approximate factor models assuming a large number of cross-sectional observations and studies the consistency properties of these information criteria. It also reports extensive simulation results comparing the performance of the extant and new procedures for the selection of the number of factors. The simulation results show the difficulty of determining which criterion performs best. In practice, it is advisable to consider several criteria at the same time, especially Hannan and Quinn’s information criterion, Bai and Ng’s ICp2 and BIC3, and Onatski’s and Ahn and Horenstein’s eigenvalue-based criteria. The model-selection criteria considered in this paper are also applied to Stock and Watson’s two macroeconomic data sets. The results differ considerably depending on the model-selection criterion in use, but evidence suggesting five factors for the first data and five to seven factors for the second data is obtainable. Journal: Econometric Reviews Pages: 577-596 Issue: 6 Volume: 38 Year: 2019 Month: 7 X-DOI: 10.1080/07474938.2017.1382763 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1382763 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:6:p:577-596 Template-Type: ReDIF-Article 1.0 Author-Name: Tingting Cheng Author-X-Name-First: Tingting Author-X-Name-Last: Cheng Title: Functional coefficient time series models with trending regressors Abstract: This paper studies a functional coefficient time series model with trending regressors, where the coefficients are unknown functions of time and random variables. We propose a local linear estimation method to estimate the unknown coefficient functions, and establish the corresponding asymptotic theory under mild conditions. We also develop a test procedure to see if the functional coefficients take particular parametric forms. For practical use, we further propose a Bayesian approach to select the bandwidths, and conduct several numerical experiments to examine the finite sample performance of our proposed local linear estimator and the test procedure. The results show that the local linear estimator works well and the proposed test has satisfactory size and power. In addition, our simulation studies show that the Bayesian bandwidth selection method performs better than the cross-validation method. Furthermore, we use the functional coefficient model to study the relationship between consumption per capita and income per capita in United States, and it was shown that the functional coefficient model with our proposed local linear estimator and Bayesian bandwidth selection method performs well in both in-sample fitting and out-of-sample forecasting. Journal: Econometric Reviews Pages: 636-659 Issue: 6 Volume: 38 Year: 2019 Month: 7 X-DOI: 10.1080/07474938.2017.1382774 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1382774 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:6:p:636-659 Template-Type: ReDIF-Article 1.0 Author-Name: Jan Mutl Author-X-Name-First: Jan Author-X-Name-Last: Mutl Author-Name: Leopold Sögner Author-X-Name-First: Leopold Author-X-Name-Last: Sögner Title: Parameter estimation and inference with spatial lags and cointegration Abstract: This article studies dynamic panel data models in which the long run outcome for a particular cross-section is affected by a weighted average of the outcomes in the other cross-sections. We show that imposing such a structure implies a model with several cointegrating relationships that, unlike in the standard case, are nonlinear in the coefficients to be estimated. Assuming that the weights are exogenously given, we extend the dynamic ordinary least squares methodology and provide a dynamic two-stage least squares estimator. We derive the large sample properties of our proposed estimator under a set of low-level assumptions. Then our methodology is applied to US financial market data, which consist of credit default swap spreads, as well as firm-specific and industry data. We construct the economic space using a “closeness” measure for firms based on input–output matrices. Our estimates show that this particular form of spatial correlation of credit default swap spreads is substantial and highly significant. Journal: Econometric Reviews Pages: 597-635 Issue: 6 Volume: 38 Year: 2019 Month: 7 X-DOI: 10.1080/07474938.2017.1382803 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1382803 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:6:p:597-635 Template-Type: ReDIF-Article 1.0 Author-Name: Andreea G. Halunga Author-X-Name-First: Andreea G. Author-X-Name-Last: Halunga Author-Name: Christos S. Savva Author-X-Name-First: Christos S. Author-X-Name-Last: Savva Title: Neglecting structural breaks when estimating and valuing dynamic correlations for asset allocation Abstract: This paper assesses the econometric and economic value consequences of neglecting structural breaks in dynamic correlation models and in the context of asset allocation framework. It is shown that changes in the parameters of the conditional correlation process can lead to biased estimates of persistence. Monte Carlo simulations reveal that short-run persistence is downward biased while long-run persistence is severely upward biased, leading to spurious high persistence of shocks to conditional correlation. An application to stock returns supports these results and concludes that neglecting such structural shifts could lead to misleading decisions on portfolio diversification, hedging, and risk management. Journal: Econometric Reviews Pages: 660-678 Issue: 6 Volume: 38 Year: 2019 Month: 7 X-DOI: 10.1080/07474938.2017.1411431 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1411431 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:6:p:660-678 Template-Type: ReDIF-Article 1.0 Author-Name: Katerina Aristodemou Author-X-Name-First: Katerina Author-X-Name-Last: Aristodemou Author-Name: Jian He Author-X-Name-First: Jian Author-X-Name-Last: He Author-Name: Keming Yu Author-X-Name-First: Keming Author-X-Name-Last: Yu Title: Binary quantile regression and variable selection: A new approach Abstract: In this paper, we propose a new estimation method for binary quantile regression and variable selection which can be implemented by an iteratively reweighted least square approach. In contrast to existing approaches, this method is computationally simple, guaranteed to converge to a unique solution and implemented with standard software packages. We demonstrate our methods using Monte-Carlo experiments and then we apply the proposed method to the widely used work trip mode choice dataset. The results indicate that the proposed estimators work well in finite samples. Journal: Econometric Reviews Pages: 679-694 Issue: 6 Volume: 38 Year: 2019 Month: 7 X-DOI: 10.1080/07474938.2017.1417701 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1417701 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:6:p:679-694 Template-Type: ReDIF-Article 1.0 Author-Name: Christian Schluter Author-X-Name-First: Christian Author-X-Name-Last: Schluter Author-Name: Mark Trede Author-X-Name-First: Mark Author-X-Name-Last: Trede Title: Size distributions reconsidered Abstract: We consider tests of the hypothesis that the tail of size distributions decays faster than any power function. These are based on a single parameter that emerges from the Fisher–Tippett limit theorem, and discriminate between leading laws considered in the literature without requiring fully parametric models/specifications. We study the proposed tests taking into account the higher order regular variation of the size distribution that can lead to catastrophic distortions. The theoretical bias corrections realign successfully nominal and empirical test behavior, and inform a sensitivity analysis for practical work. The methods are used in an examination of the size distribution of cities and firms. Journal: Econometric Reviews Pages: 695-710 Issue: 6 Volume: 38 Year: 2019 Month: 7 X-DOI: 10.1080/07474938.2017.1417732 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1417732 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:6:p:695-710 Template-Type: ReDIF-Article 1.0 Author-Name: Francesco Bartolucci Author-X-Name-First: Francesco Author-X-Name-Last: Bartolucci Author-Name: Valentina Nigro Author-X-Name-First: Valentina Author-X-Name-Last: Nigro Author-Name: Claudia Pigini Author-X-Name-First: Claudia Author-X-Name-Last: Pigini Title: Testing for state dependence in binary panel data with individual covariates by a modified quadratic exponential model Abstract: We propose a test for state dependence in binary panel data with individual covariates. For this aim, we rely on a quadratic exponential model in which the association between the response variables is accounted for in a different way with respect to more standard formulations. The level of association is measured by a single parameter that may be estimated by a Conditional Maximum Likelihood (CML) approach. Under the dynamic logit model, the conditional estimator of this parameter converges to zero when the hypothesis of absence of state dependence is true. Therefore, it is possible to implement a t-test for this hypothesis which may be very simply performed and attains the nominal significance level under several structures of the individual covariates. Through an extensive simulation study, we find that our test has good finite sample properties and it is more robust to the presence of (autocorrelated) covariates in the model specification in comparison with other existing testing procedures for state dependence. The proposed approach is illustrated by two empirical applications: the first is based on data coming from the Panel Study of Income Dynamics and concerns employment and fertility; the second is based on the Health and Retirement Study and concerns the self reported health status. Journal: Econometric Reviews Pages: 61-88 Issue: 1 Volume: 37 Year: 2018 Month: 1 X-DOI: 10.1080/07474938.2015.1060039 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1060039 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:1:p:61-88 Template-Type: ReDIF-Article 1.0 Author-Name: Saburo Ohno Author-X-Name-First: Saburo Author-X-Name-Last: Ohno Author-Name: Tomohiro Ando Author-X-Name-First: Tomohiro Author-X-Name-Last: Ando Title: Stock return predictability: A factor-augmented predictive regression system with shrinkage method Abstract: To predict stock market behaviors, we use a factor-augmented predictive regression with shrinkage to incorporate the information available across literally thousands of financial and economic variables. The system is constructed in terms of both expected returns and the tails of the return distribution. We develop the variable selection consistency and asymptotic normality of the estimator. To select the regularization parameter, we employ the prediction error, with the aim of predicting the behavior of the stock market. Through analysis of the Tokyo Stock Exchange, we find that a large number of variables provide useful information for predicting stock market behaviors. Journal: Econometric Reviews Pages: 29-60 Issue: 1 Volume: 37 Year: 2018 Month: 1 X-DOI: 10.1080/07474938.2014.977086 File-URL: http://hdl.handle.net/10.1080/07474938.2014.977086 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:1:p:29-60 Template-Type: ReDIF-Article 1.0 Author-Name: Eric S. Lin Author-X-Name-First: Eric S. Author-X-Name-Last: Lin Author-Name: Ta-Sheng Chou Author-X-Name-First: Ta-Sheng Author-X-Name-Last: Chou Title: Finite-sample refinement of GMM approach to nonlinear models under heteroskedasticity of unknown form Abstract: It is quite common to observe heteroskedasticity in real data, in particular, cross-sectional or micro data. Previous studies concentrate on improving the finite-sample properties of tests under heteroskedasticity of unknown forms in linear models. The advantage of a heteroskedasticity consistent covariance matrix estimator (HCCME)-type small-sample improvement for linear models does not carry over to the nonlinear model specifications since there is no obvious counterpart for the diagonal element of the projection matrix in linear models, which is crucial for implementing the finite-sample refinement. Within the framework of nonlinear models, we develop a straightforward approach by extending the applicability of HCCME-type corrections to the two-step GMM method. The Monte Carlo experiments show that the proposed method not only refines the testing procedure in terms of the error of rejection probability, but also improves the coefficient estimation based on the mean squared error (MSE) and the mean absolute error (MAE). The estimation of a constant elasticity of substitution (CES)-type production function is also provided to illustrate how to implement the proposed method empirically. Journal: Econometric Reviews Pages: 1-28 Issue: 1 Volume: 37 Year: 2018 Month: 1 X-DOI: 10.1080/07474938.2014.999499 File-URL: http://hdl.handle.net/10.1080/07474938.2014.999499 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:1:p:1-28 Template-Type: ReDIF-Article 1.0 Author-Name: Tingting Cheng Author-X-Name-First: Tingting Author-X-Name-Last: Cheng Author-Name: Jiti Gao Author-X-Name-First: Jiti Author-X-Name-Last: Gao Author-Name: Xibin Zhang Author-X-Name-First: Xibin Author-X-Name-Last: Zhang Title: Nonparametric localized bandwidth selection for Kernel density estimation Abstract: As conventional cross-validation bandwidth selection methods do not work properly in the situation where the data are serially dependent time series, alternative bandwidth selection methods are necessary. In recent years, Bayesian-based methods for global bandwidth selection have been studied. Our experience shows that a global bandwidth is however less suitable than a localized bandwidth in kernel density estimation based on serially dependent time series data. Nonetheless, a difficult issue is how we can consistently estimate a localized bandwidth. This paper presents a nonparametric localized bandwidth estimator, for which we establish a completely new asymptotic theory. Applications of this new bandwidth estimator to the kernel density estimation of Eurodollar deposit rate and the S&P 500 daily return demonstrate the effectiveness and competitiveness of the proposed localized bandwidth. Journal: Econometric Reviews Pages: 733-762 Issue: 7 Volume: 38 Year: 2019 Month: 8 X-DOI: 10.1080/07474938.2017.1397835 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1397835 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:7:p:733-762 Template-Type: ReDIF-Article 1.0 Author-Name: Marie Bessec Author-X-Name-First: Marie Author-X-Name-Last: Bessec Title: Revisiting the transitional dynamics of business cycle phases with mixed-frequency data Abstract: This paper introduces a Markov-switching model in which transition probabilities depend on higher frequency indicators and their lags through polynomial weighting schemes. The MSV-MIDAS model is estimated through maximum likelihood (ML) methods with a slightly modified version of Hamilton’s filter. Monte Carlo simulations show that ML provides accurate estimates, but they suggest some caution in interpreting the tests of the parameters in the transition probabilities. We apply this new model to forecast business cycle turning points in the United States. We properly detect recessions by exploiting the link between GDP growth and higher frequency variables from financial and energy markets. Journal: Econometric Reviews Pages: 711-732 Issue: 7 Volume: 38 Year: 2019 Month: 8 X-DOI: 10.1080/07474938.2017.1397837 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1397837 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:7:p:711-732 Template-Type: ReDIF-Article 1.0 Author-Name: Jan Lohmeyer Author-X-Name-First: Jan Author-X-Name-Last: Lohmeyer Author-Name: Franz Palm Author-X-Name-First: Franz Author-X-Name-Last: Palm Author-Name: Hanno Reuvers Author-X-Name-First: Hanno Author-X-Name-Last: Reuvers Author-Name: Jean-Pierre Urbain Author-X-Name-First: Jean-Pierre Author-X-Name-Last: Urbain Title: Focused information criterion for locally misspecified vector autoregressive models Abstract: This paper investigates the focused information criterion and plug-in average for vector autoregressive models with local-to-zero misspecification. These methods have the advantage of focusing on a quantity of interest rather than aiming at overall model fit. Any (sufficiently regular) function of the parameters can be used as a quantity of interest. We determine the asymptotic properties and elaborate on the role of the locally misspecified parameters. In particular, we show that the inability to consistently estimate locally misspecified parameters translates into suboptimal selection and averaging. We apply this framework to impulse response analysis. A Monte Carlo simulation study supports our claims. Journal: Econometric Reviews Pages: 763-792 Issue: 7 Volume: 38 Year: 2019 Month: 8 X-DOI: 10.1080/07474938.2017.1409410 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1409410 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:7:p:763-792 Template-Type: ReDIF-Article 1.0 Author-Name: Uwe Hassler Author-X-Name-First: Uwe Author-X-Name-Last: Hassler Author-Name: Mehdi Hosseinkouchack Author-X-Name-First: Mehdi Author-X-Name-Last: Hosseinkouchack Title: Ratio tests under limiting normality Abstract: We propose a class of ratio tests that is applicable whenever a cumulation (of transformed) data is asymptotically normal upon appropriate normalization. The Karhunen–Loève theorem is employed to compute weighted averages. The test statistics are ratios of quadratic forms of these averages and hence scale-invariant, also called self-normalizing: The scaling parameter cancels asymptotically. Limiting distributions are obtained. Critical values and asymptotic local power functions can be calculated by standard numerical means. The ratio tests are directed against local alternatives and turn out to be almost as powerful as optimal competitors, without being plagued by nuisance parameters at the same time. Also in finite samples they perform well relative to self-normalizing competitors. Journal: Econometric Reviews Pages: 793-813 Issue: 7 Volume: 38 Year: 2019 Month: 8 X-DOI: 10.1080/07474938.2018.1427296 File-URL: http://hdl.handle.net/10.1080/07474938.2018.1427296 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:7:p:793-813 Template-Type: ReDIF-Article 1.0 Author-Name: Maurice J. G. Bun Author-X-Name-First: Maurice J. G. Author-X-Name-Last: Bun Author-Name: Teresa D. Harrison Author-X-Name-First: Teresa D. Author-X-Name-Last: Harrison Title: OLS and IV estimation of regression models including endogenous interaction terms Abstract: We analyze a class of linear regression models including interactions of endogenous regressors and exogenous covariates. We show how to generate instrumental variables using the nonlinear functional form of the structural equation when traditional excluded instruments are unknown. We propose to use these instruments with identification robust IV inference. We furthermore show that, whenever functional form identification is not valid, the ordinary least squares (OLS) estimator of the coefficient of the interaction term is consistent and standard OLS inference applies. Using our alternative empirical methods we confirm recent empirical findings on the nonlinear causal relation between financial development and economic growth. Journal: Econometric Reviews Pages: 814-827 Issue: 7 Volume: 38 Year: 2019 Month: 8 X-DOI: 10.1080/07474938.2018.1427486 File-URL: http://hdl.handle.net/10.1080/07474938.2018.1427486 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:7:p:814-827 Template-Type: ReDIF-Article 1.0 Author-Name: Jaromír Antoch Author-X-Name-First: Jaromír Author-X-Name-Last: Antoch Author-Name: Jan Hanousek Author-X-Name-First: Jan Author-X-Name-Last: Hanousek Author-Name: Lajos Horváth Author-X-Name-First: Lajos Author-X-Name-Last: Horváth Author-Name: Marie Hušková Author-X-Name-First: Marie Author-X-Name-Last: Hušková Author-Name: Shixuan Wang Author-X-Name-First: Shixuan Author-X-Name-Last: Wang Title: Structural breaks in panel data: Large number of panels and short length time series Abstract: The detection of (structural) breaks or the so called change point problem has drawn increasing attention from the theoretical, applied economic and financial fields. Much of the existing research concentrates on the detection of change points and asymptotic properties of their estimators in panels when N, the number of panels, as well as T, the number of observations in each panel are large. In this paper we pursue a different approach, i.e., we consider the asymptotic properties when N→∞ while keeping T fixed. This situation is typically related to large (firm-level) data containing financial information about an immense number of firms/stocks across a limited number of years/quarters/months. We propose a general approach for testing for break(s) in this setup. In particular, we obtain the asymptotic behavior of test statistics. We also propose a wild bootstrap procedure that could be used to generate the critical values of the test statistics. The theoretical approach is supplemented by numerous simulations and by an empirical illustration. We demonstrate that the testing procedure works well in the framework of the four factors CAPM model. In particular, we estimate the breaks in the monthly returns of US mutual funds during the period January 2006 to February 2010 which covers the subprime crises. Journal: Econometric Reviews Pages: 828-855 Issue: 7 Volume: 38 Year: 2019 Month: 8 X-DOI: 10.1080/07474938.2018.1454378 File-URL: http://hdl.handle.net/10.1080/07474938.2018.1454378 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:7:p:828-855 Template-Type: ReDIF-Article 1.0 Author-Name: Wasel Shadat Author-X-Name-First: Wasel Author-X-Name-Last: Shadat Author-Name: Chris Orme Author-X-Name-First: Chris Author-X-Name-Last: Orme Title: Robust parametric tests of constant conditional correlation in a MGARCH model Abstract: This article provides a rigorous asymptotic treatment of new and existing asymptotically valid conditional moment (CM) testing procedures of the constant conditional correlation (CCC) assumption in a multivariate GARCH model. Full and partial quasi maximum likelihood estimation (QMLE) frameworks are considered, as is the robustness of these tests to non-normality. In particular, the asymptotic validity of the LM procedure proposed by Tse (2000) is analyzed, and new asymptotically robust versions of this test are proposed for both estimation frameworks. A Monte Carlo study suggests that a robust Tse test procedure exhibits good size and power properties, unlike the original variant which exhibits size distortion under non-normality. Journal: Econometric Reviews Pages: 551-576 Issue: 6 Volume: 37 Year: 2018 Month: 7 X-DOI: 10.1080/07474938.2015.1122120 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1122120 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:6:p:551-576 Template-Type: ReDIF-Article 1.0 Author-Name: Seong Yeon Chang Author-X-Name-First: Seong Yeon Author-X-Name-Last: Chang Author-Name: Pierre Perron Author-X-Name-First: Pierre Author-X-Name-Last: Perron Title: A comparison of alternative methods to construct confidence intervals for the estimate of a break date in linear regression models Abstract: This article considers constructing confidence intervals for the date of a structural break in linear regression models. Using extensive simulations, we compare the performance of various procedures in terms of exact coverage rates and lengths of the confidence intervals. These include the procedures of Bai (1997) based on the asymptotic distribution under a shrinking shift framework, Elliott and Müller (2007) based on inverting a test locally invariant to the magnitude of break, Eo and Morley (2015) based on inverting a likelihood ratio test, and various bootstrap procedures. On the basis of achieving an exact coverage rate that is closest to the nominal level, Elliott and Müller's (2007) approach is by far the best one. However, this comes with a very high cost in terms of the length of the confidence intervals. When the errors are serially correlated and dealing with a change in intercept or a change in the coefficient of a stationary regressor with a high signal-to-noise ratio, the length of the confidence interval increases and approaches the whole sample as the magnitude of the change increases. The same problem occurs in models with a lagged dependent variable, a common case in practice. This drawback is not present for the other methods, which have similar properties. Theoretical results are provided to explain the drawbacks of Elliott and Müller's (2007) method. Journal: Econometric Reviews Pages: 577-601 Issue: 6 Volume: 37 Year: 2018 Month: 7 X-DOI: 10.1080/07474938.2015.1122142 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1122142 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:6:p:577-601 Template-Type: ReDIF-Article 1.0 Author-Name: Liangjun Su Author-X-Name-First: Liangjun Author-X-Name-Last: Su Author-Name: Zhenlin Yang Author-X-Name-First: Zhenlin Author-X-Name-Last: Yang Title: Asymptotics and bootstrap for random-effects panel data transformation models Abstract: This article investigates the asymptotic properties of quasi-maximum likelihood (QML) estimators for random-effects panel data transformation models where both the response and (some of) the covariates are subject to transformations for inducing normality, flexible functional form, homoskedasticity, and simple model structure. We develop a QML-type procedure for model estimation and inference. We prove the consistency and asymptotic normality of the QML estimators, and propose a simple bootstrap procedure that leads to a robust estimate of the variance-covariance (VC) matrix. Monte Carlo results reveal that the QML estimators perform well in finite samples, and that the gains by using the robust VC matrix estimate for inference can be enormous. Journal: Econometric Reviews Pages: 602-625 Issue: 6 Volume: 37 Year: 2018 Month: 7 X-DOI: 10.1080/07474938.2015.1122235 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1122235 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:6:p:602-625 Template-Type: ReDIF-Article 1.0 Author-Name: Renée Fry-McKibbin Author-X-Name-First: Renée Author-X-Name-Last: Fry-McKibbin Author-Name: Cody Yu-Ling Hsiao Author-X-Name-First: Cody Yu-Ling Author-X-Name-Last: Hsiao Title: Extremal dependence tests for contagion Abstract: A new test for financial market contagion based on changes in extremal dependence defined as co-kurtosis and co-volatility is developed to identify the propagation mechanism of shocks across international financial markets. The proposed approach captures changes in various aspects of the asset return relationships such as cross-market mean and skewness (co-kurtosis) as well as cross-market volatilities (co-volatility). Monte Carlo experiments show that the tests perform well except for when crisis periods are short in duration. Small crisis sample critical values are calculated for use in this case. In an empirical application involving the global financial crisis of 2008–2009, the results show that significant contagion effects are widespread from the US banking sector to global equity markets and banking sectors through either the co-kurtosis or the co-volatility channels, reinforcing that higher order moments matter during crises. Journal: Econometric Reviews Pages: 626-649 Issue: 6 Volume: 37 Year: 2018 Month: 7 X-DOI: 10.1080/07474938.2015.1122270 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1122270 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:6:p:626-649 Template-Type: ReDIF-Article 1.0 Author-Name: Artūras Juodis Author-X-Name-First: Artūras Author-X-Name-Last: Juodis Title: First difference transformation in panel VAR models: Robustness, estimation, and inference Abstract: This article considers estimation of Panel Vector Autoregressive Models of order 1 (PVAR(1)) with focus on fixed T consistent estimation methods in First Differences (FD) with additional strictly exogenous regressors. Additional results for the Panel FD ordinary least squares (OLS) estimator and the FDLS type estimator of Han and Phillips (2010) are provided. Furthermore, we simplify the analysis of Binder et al. (2005) by providing additional analytical results and extend the original model by taking into account possible cross-sectional heteroscedasticity and presence of strictly exogenous regressors. We show that in the three wave panel the log-likelihood function of the unrestricted Transformed Maximum Likelihood (TML) estimator might violate the global identification assumption. The finite-sample performance of the analyzed methods is investigated in a Monte Carlo study. Journal: Econometric Reviews Pages: 650-693 Issue: 6 Volume: 37 Year: 2018 Month: 7 X-DOI: 10.1080/07474938.2016.1139559 File-URL: http://hdl.handle.net/10.1080/07474938.2016.1139559 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:6:p:650-693 Template-Type: ReDIF-Article 1.0 Author-Name: Qichang Xie Author-X-Name-First: Qichang Author-X-Name-Last: Xie Author-Name: Qiankun Sun Author-X-Name-First: Qiankun Author-X-Name-Last: Sun Author-Name: Junxian Liu Author-X-Name-First: Junxian Author-X-Name-Last: Liu Title: Local weighted composite quantile estimation and smoothing parameter selection for nonparametric derivative function Abstract: Estimating derivatives is of primary interest as it quantitatively measures the rate of change of the relationship between response and explanatory variables. We propose a local weighted composite quantile method to estimate the gradient of an unknown regression function. Because of the use of weights, a data-driven weighting scheme is discussed for maximizing the asymptotic efficiency of the estimators. We derive the leading bias, variance and normality of the estimator proposed. The asymptotic relative efficiency is investigated and reveals that the new approach provides a highly efficient alternative to the local least squares, the local quantile regression and the local composite quantile regression methods. In addition, a fully automatic bandwidth selection method is considered and is shown to deliver the bandwidth with oracle property meaning that it is asymptotically equivalent to the optimal bandwidth if the true gradient were known. Simulations are conducted to compare different estimators and an example is used to illustrate their performance. Both simulation and empirical results are consistent with our theoretical findings. Journal: Econometric Reviews Pages: 215-233 Issue: 3 Volume: 39 Year: 2020 Month: 3 X-DOI: 10.1080/07474938.2019.1580947 File-URL: http://hdl.handle.net/10.1080/07474938.2019.1580947 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:3:p:215-233 Template-Type: ReDIF-Article 1.0 Author-Name: Halvor Mehlum Author-X-Name-First: Halvor Author-X-Name-Last: Mehlum Title: The polar confidence curve for a ratio Abstract: Based on Fieller’s method for the estimation of a confidence set for a ratio, I construct a polar plot of the test statistics for all angles associated with the ratio. This polar confidence plot clarifies and systematizes the inherent properties of the confidence set for ratios and, in particular, determines how the confidence set may be uninformative or disconnected. Journal: Econometric Reviews Pages: 234-243 Issue: 3 Volume: 39 Year: 2020 Month: 3 X-DOI: 10.1080/07474938.2019.1580951 File-URL: http://hdl.handle.net/10.1080/07474938.2019.1580951 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:3:p:234-243 Template-Type: ReDIF-Article 1.0 Author-Name: Rasmus Søndergaard Pedersen Author-X-Name-First: Rasmus Søndergaard Author-X-Name-Last: Pedersen Title: Robust inference in conditionally heteroskedastic autoregressions Abstract: We consider robust inference for an autoregressive parameter in a stationary linear autoregressive model with GARCH innovations. As the innovations exhibit GARCH, they are by construction heavy-tailed with some tail index κ. This implies that the rate of convergence as well as the limiting distribution of the least squares estimator depend on κ. In the spirit of Ibragimov and Müller (“t-statistic based correlation and heterogeneity robust inference”, Journal of Business & Economic Statistics, 2010, vol. 28, pp. 453–468), we consider testing a hypothesis about a parameter based on a Student’s t-statistic based on least squares estimates for a fixed number of groups of the original sample. The merit of this approach is that no knowledge about the value of κ nor about the rate of convergence and the limiting distribution of the least squares estimator is required. We verify that the two-sided t-test is asymptotically a level α test whenever α≤5% for any κ≥2, which includes cases where the innovations have infinite variance. A simulation experiment suggests that the finite-sample properties of the test are quite good. Journal: Econometric Reviews Pages: 244-259 Issue: 3 Volume: 39 Year: 2020 Month: 3 X-DOI: 10.1080/07474938.2019.1580950 File-URL: http://hdl.handle.net/10.1080/07474938.2019.1580950 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:3:p:244-259 Template-Type: ReDIF-Article 1.0 Author-Name: N. R. Ramírez-Rondán Author-X-Name-First: N. R. Author-X-Name-Last: Ramírez-Rondán Title: Maximum likelihood estimation of dynamic panel threshold models Abstract: Threshold estimation methods are developed for dynamic panels with individual specific fixed effects covering short time periods. Maximum likelihood estimation of the threshold and slope parameters is proposed using first difference transformations. Threshold estimate is shown to be consistent and its asymptotic distribution is nonstandard when the number of individuals grows to infinity for a fixed time period; the slope estimates are consistent and asymptotically normally distributed. The method is applied to a sample of 74 countries and 11 periods of 5-year averages to determine the effect of inflation rate on long-run economic growth. Journal: Econometric Reviews Pages: 260-276 Issue: 3 Volume: 39 Year: 2020 Month: 3 X-DOI: 10.1080/07474938.2019.1624401 File-URL: http://hdl.handle.net/10.1080/07474938.2019.1624401 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:3:p:260-276 Template-Type: ReDIF-Article 1.0 Author-Name: Alexandra Soberon Author-X-Name-First: Alexandra Author-X-Name-Last: Soberon Author-Name: Winfried Stute Author-X-Name-First: Winfried Author-X-Name-Last: Stute Author-Name: Juan M. Rodriguez-Poo Author-X-Name-First: Juan M. Author-X-Name-Last: Rodriguez-Poo Title: Testing for distributional features in varying coefficient panel data models Abstract: This article provides several tests for skewness and kurtosis for the error terms in a one-way fixed-effects varying coefficient panel data model. To obtain these tests, estimators of higher-order moments of both error components are obtained as solutions of estimating equations. Additionally, to obtain the nonparametric residuals, a local constant estimator based on a pairwise differencing transformation is proposed. The asymptotic properties of these estimators and tests are established. The proposed estimators and test statistics are augmented by simulation studies, and they are also illustrated in an empirical analysis regarding the technical efficiency of European Union companies. Journal: Econometric Reviews Pages: 277-298 Issue: 3 Volume: 39 Year: 2020 Month: 3 X-DOI: 10.1080/07474938.2019.1624403 File-URL: http://hdl.handle.net/10.1080/07474938.2019.1624403 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:3:p:277-298 Template-Type: ReDIF-Article 1.0 Author-Name: Yundong Tu Author-X-Name-First: Yundong Author-X-Name-Last: Tu Author-Name: Ying Wang Author-X-Name-First: Ying Author-X-Name-Last: Wang Title: Adaptive estimation of heteroskedastic functional-coefficient regressions with an application to fiscal policy evaluation on asset markets Abstract: This article studies the adaptive estimation of the heteroskedastic functional-coefficient regressions. The motivation for such a theoretical study originates from the empirical analysis of Jansen et al., where the role of fiscal policy on the U.S. asset markets (treasury bonds) is evaluated via the functional-coefficient model. It is found that this model is subject to time-varying heteroskedasticity. As a result, the local least square (LLS) estimator suffers from efficiency loss. To overcome this problem, we propose an adaptive LLS (ALLS) estimator, which can adapt to heteroskedasticity of unknown form asymptotically. Simulation studies confirm that the ALLS estimator can achieve significant efficiency gain in finite samples, compared to the LLS estimator. Real data analysis reveals that the heteroskedastic functional-coefficient model provides adequate fit and better out-of-sample forecasting. Journal: Econometric Reviews Pages: 299-318 Issue: 3 Volume: 39 Year: 2020 Month: 3 X-DOI: 10.1080/07474938.2019.1624402 File-URL: http://hdl.handle.net/10.1080/07474938.2019.1624402 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:3:p:299-318 Template-Type: ReDIF-Article 1.0 Author-Name: Otilia Boldea Author-X-Name-First: Otilia Author-X-Name-Last: Boldea Author-Name: Alastair Hall Author-X-Name-First: Alastair Author-X-Name-Last: Hall Author-Name: Sanggohn Han Author-X-Name-First: Sanggohn Author-X-Name-Last: Han Title: Asymptotic Distribution Theory for Break Point Estimators in Models Estimated via 2SLS Abstract: In this article, we present a limiting distribution theory for the break point estimator in a linear regression model with multiple structural breaks obtained by minimizing a Two Stage Least Squares (2SLS) objective function. Our analysis covers both the case in which the reduced form for the endogenous regressors is stable and the case in which it is unstable with multiple structural breaks. For stable reduced forms, we present a limiting distribution theory under two different scenarios: in the case where the parameter change is of fixed magnitude, it is shown that the resulting distribution depends on the distribution of the data and is not of much practical use for inference; in the case where the magnitude of the parameter change shrinks with the sample size, it is shown that the resulting distribution can be used to construct approximate large sample confidence intervals for the break points. For unstable reduced forms, we consider the case where the magnitudes of the parameter changes in both the equation of interest and the reduced forms shrink with the sample size at potentially different rates and not necessarily the same locations in the sample. The resulting limiting distribution theory can be used to construct approximate large sample confidence intervals for the break points. Its usefulness is illustrated via an application to the New Keynesian Phillips curve. Journal: Econometric Reviews Pages: 1-33 Issue: 1 Volume: 31 Year: 2012 X-DOI: 10.1080/07474938.2011.607082 File-URL: http://hdl.handle.net/10.1080/07474938.2011.607082 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:31:y:2012:i:1:p:1-33 Template-Type: ReDIF-Article 1.0 Author-Name: Changli He Author-X-Name-First: Changli Author-X-Name-Last: He Author-Name: Rickard Sandberg Author-X-Name-First: Rickard Author-X-Name-Last: Sandberg Title: Testing Parameter Constancy in Unit Root Autoregressive Models Against Multiple Continuous Structural Changes Abstract: This article considers tests for logistic smooth transition autoregressive (LSTAR) models accommodating multiple time dependent transitions between regimes when the data generating process is a random walk. The asymptotic null distributions of the tests, in contrast to the standard results in Lin and Teräsvirta (1994), are nonstandard. Monte Carlo experiments reveal that the tests have modest size distortions and satisfactory power against LSTAR models with multiple smooth breaks. The tests are applied to Swedish unemployment rates and the hysteresis hypothesis is over-turned in favour of an LSTAR model with two transitions between extreme regimes. Journal: Econometric Reviews Pages: 34-59 Issue: 1 Volume: 31 Year: 2012 X-DOI: 10.1080/07474938.2011.607085 File-URL: http://hdl.handle.net/10.1080/07474938.2011.607085 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:31:y:2012:i:1:p:34-59 Template-Type: ReDIF-Article 1.0 Author-Name: George Athanasopoulos Author-X-Name-First: George Author-X-Name-Last: Athanasopoulos Author-Name: D. Poskitt Author-X-Name-First: D. Author-X-Name-Last: Poskitt Author-Name: Farshid Vahid Author-X-Name-First: Farshid Author-X-Name-Last: Vahid Title: Two Canonical VARMA Forms: Scalar Component Models Vis-à-Vis the Echelon Form Abstract: In this article we study two methodologies which identify and specify canonical form VARMA models. The two methodologies are: (1) an extension of the scalar component methodology which specifies canonical VARMA models by identifying scalar components through canonical correlations analysis; and (2) the Echelon form methodology, which specifies canonical VARMA models through the estimation of Kronecker indices. We compare the actual forms and the methodologies on three levels. Firstly, we present a theoretical comparison. Secondly, we present a Monte Carlo simulation study that compares the performances of the two methodologies in identifying some pre-specified data generating processes. Lastly, we compare the out-of-sample forecast performance of the two forms when models are fitted to real macroeconomic data. Journal: Econometric Reviews Pages: 60-83 Issue: 1 Volume: 31 Year: 2012 X-DOI: 10.1080/07474938.2011.607088 File-URL: http://hdl.handle.net/10.1080/07474938.2011.607088 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:31:y:2012:i:1:p:60-83 Template-Type: ReDIF-Article 1.0 Author-Name: Andriy Norets Author-X-Name-First: Andriy Author-X-Name-Last: Norets Title: Estimation of Dynamic Discrete Choice Models Using Artificial Neural Network Approximations Abstract: I propose a method for inference in dynamic discrete choice models (DDCM) that utilizes Markov chain Monte Carlo (MCMC) and artificial neural networks (ANNs). MCMC is intended to handle high-dimensional integration in the likelihood function of richly specified DDCMs. ANNs approximate the dynamic-program (DP) solution as a function of the parameters and state variables prior to estimation to avoid having to solve the DP on each iteration. Potential applications of the proposed methodology include inference in DDCMs with random coefficients, serially correlated unobservables, and dependence across individual observations. The article discusses MCMC estimation of DDCMs, provides relevant background on ANNs, and derives a theoretical justification for the method. Experiments suggest this to be a promising approach. Journal: Econometric Reviews Pages: 84-106 Issue: 1 Volume: 31 Year: 2012 X-DOI: 10.1080/07474938.2011.607089 File-URL: http://hdl.handle.net/10.1080/07474938.2011.607089 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:31:y:2012:i:1:p:84-106 Template-Type: ReDIF-Article 1.0 Author-Name: Patrick Bajari Author-X-Name-First: Patrick Author-X-Name-Last: Bajari Author-Name: Thomas Youle Author-X-Name-First: Thomas Author-X-Name-Last: Youle Title: Book Review: and Journal: Econometric Reviews Pages: 107-117 Issue: 1 Volume: 31 Year: 2012 X-DOI: 10.1080/07474938.2011.607090 File-URL: http://hdl.handle.net/10.1080/07474938.2011.607090 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:31:y:2012:i:1:p:107-117 Template-Type: ReDIF-Article 1.0 Author-Name: Pierre Chaussé Author-X-Name-First: Pierre Author-X-Name-Last: Chaussé Author-Name: Dinghai Xu Author-X-Name-First: Dinghai Author-X-Name-Last: Xu Title: GMM estimation of a realized stochastic volatility model: A Monte Carlo study Abstract: This article investigates alternative generalized method of moments (GMM) estimation procedures of a stochastic volatility model with realized volatility measures. The extended model can accommodate a more general correlation structure. General closed form moment conditions are derived to examine the model properties and to evaluate the performance of various GMM estimation procedures under Monte Carlo environment, including standard GMM, principal component GMM, robust GMM and regularized GMM. An application to five company stocks and one stock index is also provided for an empirical demonstration. Journal: Econometric Reviews Pages: 719-743 Issue: 7 Volume: 37 Year: 2018 Month: 8 X-DOI: 10.1080/07474938.2016.1152654 File-URL: http://hdl.handle.net/10.1080/07474938.2016.1152654 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:7:p:719-743 Template-Type: ReDIF-Article 1.0 Author-Name: Hung-Pin Lai Author-X-Name-First: Hung-Pin Author-X-Name-Last: Lai Author-Name: Wen-Jen Tsay Author-X-Name-First: Wen-Jen Author-X-Name-Last: Tsay Title: Maximum simulated likelihood estimation of the panel sample selection model Abstract: Heckman's (1976, 1979) sample selection model has been employed in many studies of linear and nonlinear regression applications. It is well known that ignoring the sample selectivity may result in inconsistency of the estimator due to the correlation between the statistical errors in the selection and main equations. In this article, we reconsider the maximum likelihood estimator for the panel sample selection model in Keane et al. (1988). Since the panel data model contains individual effects, such as fixed or random effects, the likelihood function is more complicated than that of the classical Heckman model. As an alternative to the existing derivation of the likelihood function in the literature, we show that the conditional distribution of the main equation follows a closed skew-normal (CSN) distribution, of which the linear transformation is still a CSN. Although the evaluation of the likelihood function involves high-dimensional integration, we show that the integration can be further simplified into a one-dimensional problem and can be evaluated by the simulated likelihood method. Moreover, we also conduct a Monte Carlo experiment to investigate the finite sample performance of the proposed estimator and find that our estimator provides reliable and quite satisfactory results. Journal: Econometric Reviews Pages: 744-759 Issue: 7 Volume: 37 Year: 2018 Month: 8 X-DOI: 10.1080/07474938.2016.1152657 File-URL: http://hdl.handle.net/10.1080/07474938.2016.1152657 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:7:p:744-759 Template-Type: ReDIF-Article 1.0 Author-Name: Nikolay Gospodinov Author-X-Name-First: Nikolay Author-X-Name-Last: Gospodinov Author-Name: Raymond Kan Author-X-Name-First: Raymond Author-X-Name-Last: Kan Author-Name: Cesare Robotti Author-X-Name-First: Cesare Author-X-Name-Last: Robotti Title: Asymptotic variance approximations for invariant estimators in uncertain asset-pricing models Abstract: This article derives explicit expressions for the asymptotic variances of the maximum likelihood and continuously-updated GMM estimators in models that may not satisfy the fundamental asset-pricing restrictions in population. The proposed misspecification-robust variance estimators allow the researcher to conduct valid inference on the model parameters even when the model is rejected by the data. While the results for the maximum likelihood estimator are only applicable to linear asset-pricing models, the asymptotic distribution of the continuously-updated GMM estimator is derived for general, possibly nonlinear, models. The large corrections in the asymptotic variances, that arise from explicitly incorporating model misspecification in the analysis, are illustrated using simulations and an empirical application. Journal: Econometric Reviews Pages: 695-718 Issue: 7 Volume: 37 Year: 2018 Month: 8 X-DOI: 10.1080/07474938.2016.1165945 File-URL: http://hdl.handle.net/10.1080/07474938.2016.1165945 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:7:p:695-718 Template-Type: ReDIF-Article 1.0 Author-Name: Ke Yang Author-X-Name-First: Ke Author-X-Name-Last: Yang Title: More efficient local polynomial regression with random-effects panel data models Abstract: We propose a modification on the local polynomial estimation procedure to account for the “within-subject” correlation presented in panel data. The proposed procedure is rather simple to compute and has a closed-form expression. We study the asymptotic bias and variance of the proposed procedure and show that it outperforms the working independence estimator uniformly up to the first order. Simulation study shows that the gains in efficiency with the proposed method in the presence of “within-subject” correlation can be significant in small samples. For illustration purposes, the procedure is applied to explore the impact of market concentration on airfare. Journal: Econometric Reviews Pages: 760-776 Issue: 7 Volume: 37 Year: 2018 Month: 8 X-DOI: 10.1080/07474938.2016.1167813 File-URL: http://hdl.handle.net/10.1080/07474938.2016.1167813 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:7:p:760-776 Template-Type: ReDIF-Article 1.0 Author-Name: Huigang Chen Author-X-Name-First: Huigang Author-X-Name-Last: Chen Author-Name: Alin Mirestean Author-X-Name-First: Alin Author-X-Name-Last: Mirestean Author-Name: Charalambos G. Tsangarides Author-X-Name-First: Charalambos G. Author-X-Name-Last: Tsangarides Title: Bayesian model averaging for dynamic panels with an application to a trade gravity model Abstract: We extend the Bayesian Model Averaging (BMA) framework to dynamic panel data models with endogenous regressors using a Limited Information Bayesian Model Averaging (LIBMA) methodology. Monte Carlo simulations confirm the asymptotic performance of our methodology both in BMA and selection, with high posterior inclusion probabilities for all relevant regressors, and parameter estimates very close to their true values. In addition, we illustrate the use of LIBMA by estimating a dynamic gravity model for bilateral trade. Once model uncertainty, dynamics, and endogeneity are accounted for, we find several factors that are robustly correlated with bilateral trade. We also find that applying methodologies that do not account for either dynamics or endogeneity (or both) results in different sets of robust determinants. Journal: Econometric Reviews Pages: 777-805 Issue: 7 Volume: 37 Year: 2018 Month: 8 X-DOI: 10.1080/07474938.2016.1167857 File-URL: http://hdl.handle.net/10.1080/07474938.2016.1167857 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:7:p:777-805 Template-Type: ReDIF-Article 1.0 Author-Name: Antonia Arsova Author-X-Name-First: Antonia Author-X-Name-Last: Arsova Author-Name: Deniz Dilan Karaman Örsal Author-X-Name-First: Deniz Dilan Karaman Author-X-Name-Last: Örsal Title: Likelihood-based panel cointegration test in the presence of a linear time trend and cross-sectional dependence Abstract: This article proposes a new likelihood-based panel cointegration rank test which extends the test of Örsal and Droge (2014) (henceforth panel SL test) to dependent panels. The dependence is modelled by unobserved common factors which affect the variables in each cross-section through heterogeneous loadings. The data are defactored following the panel analysis of nonstationarity in idiosyncratic and common components (PANIC) approach of Bai and Ng (2004) and the cointegrating rank of the defactored data is then tested by the panel SL test. A Monte Carlo study demonstrates that the proposed testing procedure has reasonable size and power properties in finite samples. Journal: Econometric Reviews Pages: 1033-1050 Issue: 10 Volume: 37 Year: 2018 Month: 11 X-DOI: 10.1080/07474938.2016.1183070 File-URL: http://hdl.handle.net/10.1080/07474938.2016.1183070 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:10:p:1033-1050 Template-Type: ReDIF-Article 1.0 Author-Name: Jing Zheng Author-X-Name-First: Jing Author-X-Name-Last: Zheng Author-Name: Wentao Gu Author-X-Name-First: Wentao Author-X-Name-Last: Gu Author-Name: Baolin Xu Author-X-Name-First: Baolin Author-X-Name-Last: Xu Author-Name: Zongwu Cai Author-X-Name-First: Zongwu Author-X-Name-Last: Cai Title: The estimation for Lévy processes in high frequency data Abstract: In this article, a generalized Lévy model is proposed and its parameters are estimated in high-frequency data settings. An infinitesimal generator of Lévy processes is used to study the asymptotic properties of the drift and volatility estimators. They are consistent asymptotically and are independent of other parameters making them better than those in Chen et al. (2010). The estimators proposed here also have fast convergence rates and are simple to implement. Journal: Econometric Reviews Pages: 1051-1066 Issue: 10 Volume: 37 Year: 2018 Month: 11 X-DOI: 10.1080/07474938.2016.1188876 File-URL: http://hdl.handle.net/10.1080/07474938.2016.1188876 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:10:p:1051-1066 Template-Type: ReDIF-Article 1.0 Author-Name: M. Hashem Pesaran Author-X-Name-First: M. Hashem Author-X-Name-Last: Pesaran Author-Name: Qiankun Zhou Author-X-Name-First: Qiankun Author-X-Name-Last: Zhou Title: Estimation of time-invariant effects in static panel data models Abstract: This article proposes the Fixed Effects Filtered (FEF) and Fixed Effects Filtered instrumental variable (FEF-IV) estimators for estimation and inference in the case of time-invariant effects in static panel data models when N is large and T is fixed. The FEF-IV allows for endogenous time-invariant regressors but assumes that there exists a sufficient number of instruments for such regressors. It is shown that the FEF and FEF-IV estimators are \begin{equation}{\sqrt {N}}\end{equation} N-consistent and asymptotically normally distributed. The FEF estimator is compared with the Fixed Effects Vector Decomposition (FEVD) estimator proposed by Plumper and Troeger (2007) and conditions under which the two estimators are equivalent are established. It is also shown that the variance estimator proposed for FEVD estimator is inconsistent and its use could lead to misleading inference. Alternative variance estimators are proposed for both FEF and FEF-IV estimators which are shown to be consistent under fairly general conditions. The small sample properties of the FEF and FEF-IV estimators are investigated by Monte Carlo experiments, and it is shown that FEF has smaller bias and RMSE, unless an intercept is included in the second stage of the FEVD procedure which renders the FEF and FEVD estimators identical. The FEVD procedure, however, results in substantial size distortions since it uses incorrect standard errors. In the case where some of the time-invariant regressors are endogenous, the FEF-IV procedure is compared with a modified version of Hausman and Taylor (1981) (HT) estimator. It is shown that both estimators perform well and have similar small sample properties. But the application of standard HT procedure, that incorrectly assumes a subset of time-varying regressors are uncorrelated with the individual effects, will yield biased estimates and significant size distortions. Journal: Econometric Reviews Pages: 1137-1171 Issue: 10 Volume: 37 Year: 2018 Month: 11 X-DOI: 10.1080/07474938.2016.1222225 File-URL: http://hdl.handle.net/10.1080/07474938.2016.1222225 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:10:p:1137-1171 Template-Type: ReDIF-Article 1.0 Author-Name: Rehim Kılıç Author-X-Name-First: Rehim Author-X-Name-Last: Kılıç Title: Robust inference for predictability in smooth transition predictive regressions Abstract: This article provides a novel test for predictability within a nonlinear smooth transition predictive regression (STPR) model where inference is complicated due not only to the presence of persistent, local to unit root, predictors, and endogeneity but also the presence of unidentified parameters under the null of no predictability. In order to circumvent the unidentified parameters problem, t− statistic for the predictor in the STPR model is optimized over the Cartesian product of the spaces for the transition and threshold parameters; and to address the difficulties due to persistent and endogenous predictors, the instrumental variable (IVX) method originally developed in the linear cointegration testing framework is adopted within the STPR model. Limit distribution of this statistic (i.e., sup−tIVX test) is shown to be nuisance parameter-free and robust to the local to unit root and endogenous regressors. Simulations show that sup−tIVX has good size and power properties. An application to stock return predictability reveals presence of asymmetric regime-dependence and variability in the strength and size of predictability across asset-related (e.g., dividend/price ratio) vs. other (e.g., default yield spread) predictors. Journal: Econometric Reviews Pages: 1067-1094 Issue: 10 Volume: 37 Year: 2018 Month: 11 X-DOI: 10.1080/07474938.2016.1222233 File-URL: http://hdl.handle.net/10.1080/07474938.2016.1222233 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:10:p:1067-1094 Template-Type: ReDIF-Article 1.0 Author-Name: Emir Malikov Author-X-Name-First: Emir Author-X-Name-Last: Malikov Author-Name: Diego A. Restrepo-Tobón Author-X-Name-First: Diego A. Author-X-Name-Last: Restrepo-Tobón Author-Name: Subal C. Kumbhakar Author-X-Name-First: Subal C. Author-X-Name-Last: Kumbhakar Title: Heterogeneous credit union production technologies with endogenous switching and correlated effects Abstract: Credit unions differ in the types of financial services they offer to their members. This article explicitly models this observed heterogeneity using a generalized model of endogenous ordered switching. Our approach captures the endogenous choice that credit unions make when adding new products to their financial services mix. The model that we consider also allows for the dependence between unobserved effects and regressors in both the selection and outcome equations and can accommodate the presence of predetermined covariates in the model. We use this model to estimate returns to scale for U.S. retail credit unions from 1996 to 2011. We document strong evidence of persistent technological heterogeneity among credit unions offering different financial service mixes, which, if ignored, can produce quite misleading results. Employing our model, we find that credit unions of all types exhibit substantial economies of scale. Journal: Econometric Reviews Pages: 1095-1119 Issue: 10 Volume: 37 Year: 2018 Month: 11 X-DOI: 10.1080/07474938.2016.1222234 File-URL: http://hdl.handle.net/10.1080/07474938.2016.1222234 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:10:p:1095-1119 Template-Type: ReDIF-Article 1.0 Author-Name: Thomas Demuynck Author-X-Name-First: Thomas Author-X-Name-Last: Demuynck Title: Testing the homogeneous marginal utility of income assumption Abstract: We develop a test for the hypothesis that every agent from a population of heterogeneous consumers has the same marginal utility of income function. This homogeneous marginal utility of income (HMUI) assumption is often (implicitly) used in applied demand studies because it has nice aggregation properties and facilitates welfare analysis. If the HMUI assumption holds, we can also identify the common marginal utility of income function. We apply our results using a U.S. cross sectional dataset on food consumption. Journal: Econometric Reviews Pages: 1120-1136 Issue: 10 Volume: 37 Year: 2018 Month: 11 X-DOI: 10.1080/07474938.2016.1222235 File-URL: http://hdl.handle.net/10.1080/07474938.2016.1222235 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:10:p:1120-1136 Template-Type: ReDIF-Article 1.0 Author-Name: The Editors Title: List of Referees Journal: Econometric Reviews Pages: 1172-1173 Issue: 10 Volume: 37 Year: 2018 Month: 11 X-DOI: 10.1080/07474938.2018.1468300 File-URL: http://hdl.handle.net/10.1080/07474938.2018.1468300 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:10:p:1172-1173 Template-Type: ReDIF-Article 1.0 Author-Name: The Editors Title: Editorial Board EOV Journal: Econometric Reviews Pages: ebi-ebi Issue: 10 Volume: 37 Year: 2018 Month: 11 X-DOI: 10.1080/07474938.2018.1468304 File-URL: http://hdl.handle.net/10.1080/07474938.2018.1468304 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:10:p:ebi-ebi Template-Type: ReDIF-Article 1.0 Author-Name: David Pacini Author-X-Name-First: David Author-X-Name-Last: Pacini Title: Two-sample least squares projection Abstract: This article investigates the problem of making inference about the coefficients in the linear projection of an outcome variable y on covariates (x,z) when data are available from two independent random samples; the first sample contains information on only the variables (y,z), while the second sample contains information on only the covariates. In this context, the validity of existing inference procedures depends crucially on the assumptions imposed on the joint distribution of (y,z,x). This article introduces a novel characterization of the identified set of the coefficients of interest when no assumption (except for the existence of second moments) on this joint distribution is imposed. One finding is that inference is necessarily nonstandard because the function characterizing the identified set is a nondifferentiable (yet directionally differentiable) function of the data. The article then introduces an estimator and a confidence interval based on the directional differential of the function characterizing the identified set. Monte Carlo experiments explore the numerical performance of the proposed estimator and confidence interval. Journal: Econometric Reviews Pages: 95-123 Issue: 1 Volume: 38 Year: 2019 Month: 1 X-DOI: 10.1080/07474938.2016.1222068 File-URL: http://hdl.handle.net/10.1080/07474938.2016.1222068 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:1:p:95-123 Template-Type: ReDIF-Article 1.0 Author-Name: Ulf Schepsmeier Author-X-Name-First: Ulf Author-X-Name-Last: Schepsmeier Title: A goodness-of-fit test for regular vine copula models Abstract: We introduce a new goodness-of-fit test for regular vine (R-vine) copula models, a very flexible class of multivariate copulas based on a pair-copula construction (PCC). The test arises from White’s information matrix test and extends an existing goodness-of-fit test for copulas. The corresponding critical value can be approximated by asymptotic theory or simulation. The simulation based test shows excellent performance with regard to observed size and power in an extensive simulation study, while the asymptotic theory based test is inadequate for n≤10,000 for a 5-dimensional model (in d = 8 even 20,000 are not enough). The simulation based test is applied to select among different R-vine specifications modeling the dependency among exchange rates. Journal: Econometric Reviews Pages: 25-46 Issue: 1 Volume: 38 Year: 2019 Month: 1 X-DOI: 10.1080/07474938.2016.1222231 File-URL: http://hdl.handle.net/10.1080/07474938.2016.1222231 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:1:p:25-46 Template-Type: ReDIF-Article 1.0 Author-Name: Mirza Trokić Author-X-Name-First: Mirza Author-X-Name-Last: Trokić Title: Wavelet energy ratio unit root tests Abstract: This article uses wavelet theory to propose a frequency domain nonparametric and tuning parameter-free family of unit root tests. The proposed test exploits the wavelet power spectrum of the observed series and its fractional partial sum to construct a test of the unit root based on the ratio of the resulting scaling energies. The proposed statistic enjoys good power properties and is robust to severe size distortions even in the presence of serially correlated MA(1) errors with a highly negative moving average (MA) parameter, as well as in the presence of random additive outliers. Any remaining size distortions are effectively eliminated using a novel wavestrapping algorithm. Journal: Econometric Reviews Pages: 69-94 Issue: 1 Volume: 38 Year: 2019 Month: 1 X-DOI: 10.1080/07474938.2016.1222232 File-URL: http://hdl.handle.net/10.1080/07474938.2016.1222232 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:1:p:69-94 Template-Type: ReDIF-Article 1.0 Author-Name: Neshat Beheshti Author-X-Name-First: Neshat Author-X-Name-Last: Beheshti Author-Name: Jeffrey S. Racine Author-X-Name-First: Jeffrey S. Author-X-Name-Last: Racine Author-Name: Ehsan S. Soofi Author-X-Name-First: Ehsan S. Author-X-Name-Last: Soofi Title: Information measures of kernel estimation Abstract: Kernel estimates of entropy and mutual information have been studied extensively in statistics and econometrics. Kullback–Leibler divergence has been used in the kernel estimation literature; yet the information characteristic of kernel estimation remains unexplored. We explore kernel estimation as an information transmission operation where the empirical cumulative distribution function is transformed into a smooth estimate. The smooth kernel estimate is a mixture of kernel functions. The Jensen–Shannon (JS) divergence of the mixture distribution provides the information measure of kernel estimation. This measure admits Kullback–Leibler and mutual information representations and provides a lower bound for the entropy of the kernel estimate of the distribution in terms of the Shannon entropy of the kernel function and the bandwidth. The JS divergence provides guidance for kernel choice based on information-theoretic considerations which helps resolve a conundrum, namely that it is legitimate and desirable to base such choice on considerations other than the mean integrated square error of the kernel smoother. We introduce a generalized polynomial kernel (GPK) family that nests a broad range of popular kernel functions, and explore its properties in terms of Shannon and Rényi entropies. We show that these entropies and variance order the GPK functions similarly. The JS information measures of six kernel functions are compared via simulations from Gaussian, gamma, and Student-t data-generating processes. The proposed framework provides the foundation for further explorations into the information-theoretic nature of kernel smoothing. Journal: Econometric Reviews Pages: 47-68 Issue: 1 Volume: 38 Year: 2019 Month: 1 X-DOI: 10.1080/07474938.2016.1222236 File-URL: http://hdl.handle.net/10.1080/07474938.2016.1222236 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:1:p:47-68 Template-Type: ReDIF-Article 1.0 Author-Name: Luke Taylor Author-X-Name-First: Luke Author-X-Name-Last: Taylor Author-Name: Taisuke Otsu Author-X-Name-First: Taisuke Author-X-Name-Last: Otsu Title: Estimation of nonseparable models with censored dependent variables and endogenous regressors Abstract: In this article we develop a nonparametric estimator for the local average response of a censored dependent variable to endogenous regressors in a nonseparable model where the unobservable error term is not restricted to be scalar and where the nonseparable function need not be monotone in the unobservables. We formalize the identification argument put forward in Altonji, Ichimura, and Otsu (2012), construct a nonparametric estimator, characterize its asymptotic property, and conduct a Monte Carlo investigation to study its small sample properties. Identification is constructive and is achieved through a control function approach. We show that the estimator is consistent and asymptotically normally distributed. The Monte Carlo results are encouraging. Journal: Econometric Reviews Pages: 4-24 Issue: 1 Volume: 38 Year: 2019 Month: 1 X-DOI: 10.1080/07474938.2016.1235310 File-URL: http://hdl.handle.net/10.1080/07474938.2016.1235310 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:1:p:4-24 Template-Type: ReDIF-Article 1.0 Author-Name: Esfandiar Maasoumi Author-X-Name-First: Esfandiar Author-X-Name-Last: Maasoumi Title: “Fellows and Scholars of Econometric Reviews” Journal: Econometric Reviews Pages: 1-3 Issue: 1 Volume: 38 Year: 2019 Month: 1 X-DOI: 10.1080/07474938.2018.1554868 File-URL: http://hdl.handle.net/10.1080/07474938.2018.1554868 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:1:p:1-3 Template-Type: ReDIF-Article 1.0 Author-Name: Laura Magazzini Author-X-Name-First: Laura Author-X-Name-Last: Magazzini Author-Name: Giorgio Calzolari Author-X-Name-First: Giorgio Author-X-Name-Last: Calzolari Title: Testing initial conditions in dynamic panel data models Abstract: We propose a new framework for testing the “mean stationarity” assumption in dynamic panel data models, required for the consistency of the system GMM estimator. In our set up the assumption is obtained as a parametric restriction in an extended set of moment conditions, allowing the use of a LM test to check its validity. Our framework provides a ranking in terms of power of the analyzed test statistics, in which our approach exhibits better power than the difference-in-Sargan/Hansen test that compares system GMM and difference GMM, that is, on its turn, more powerful than the Sargan/Hansen test based on the system GMM moment conditions. Journal: Econometric Reviews Pages: 115-134 Issue: 2 Volume: 39 Year: 2020 Month: 2 X-DOI: 10.1080/07474938.2019.1690194 File-URL: http://hdl.handle.net/10.1080/07474938.2019.1690194 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:2:p:115-134 Template-Type: ReDIF-Article 1.0 Author-Name: Hervé Cardot Author-X-Name-First: Hervé Author-X-Name-Last: Cardot Author-Name: Antonio Musolesi Author-X-Name-First: Antonio Author-X-Name-Last: Musolesi Title: Modeling temporal treatment effects with zero inflated semi-parametric regression models: The case of local development policies in France Abstract: A semi-parametric approach is proposed to estimate the variation along time of the effects of two distinct public policies that were devoted to boost rural development in France over a similar period of time. At a micro data level, it is often observed that the dependent variable, such as local employment, does not vary along time, so that we face a kind of zero inflated phenomenon that cannot be dealt with a continuous response model. We introduce a conditional mixture model which combines a mass at zero and a continuous response. The suggested zero inflated semi-parametric statistical approach relies on the flexibility and modularity of additive models with the ability of panel data to deal with selection bias and to allow for the estimation of dynamic treatment effects. In this multiple treatment analysis, we find evidence of interesting patterns of temporal treatment effects with relevant nonlinear policy effects. The adopted semi-parametric modeling also offers the possibility of making a counterfactual analysis at an individual level. The methodology is illustrated and compared with parametric linear approaches on a few municipalities for which the mean evolution of the potential outcomes is estimated under the different possible treatments. Journal: Econometric Reviews Pages: 135-157 Issue: 2 Volume: 39 Year: 2020 Month: 2 X-DOI: 10.1080/07474938.2019.1690193 File-URL: http://hdl.handle.net/10.1080/07474938.2019.1690193 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:2:p:135-157 Template-Type: ReDIF-Article 1.0 Author-Name: Michael S. Delgado Author-X-Name-First: Michael S. Author-X-Name-Last: Delgado Author-Name: Deniz Ozabaci Author-X-Name-First: Deniz Author-X-Name-Last: Ozabaci Author-Name: Yiguo Sun Author-X-Name-First: Yiguo Author-X-Name-Last: Sun Author-Name: Subal C. Kumbhakar Author-X-Name-First: Subal C. Author-X-Name-Last: Kumbhakar Title: Smooth coefficient models with endogenous environmental variables Abstract: We develop a three-step, oracle-efficient estimator for a structural semiparametric smooth coefficient model with endogenous variables in the nonparametric part of the model. We use a control function approach, combined with both series and kernel estimators to obtain consistent and asymptotically normal estimators of the functions and their partial derivatives. We develop a residual-based test statistic for testing endogeneity, and demonstrate the finite sample performance of our estimators, as well as our test, via Monte Carlo simulations. Finally, we develop an application of our estimator to the relationship between public benefits and private savings. Journal: Econometric Reviews Pages: 158-180 Issue: 2 Volume: 39 Year: 2020 Month: 2 X-DOI: 10.1080/07474938.2018.1552413 File-URL: http://hdl.handle.net/10.1080/07474938.2018.1552413 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:2:p:158-180 Template-Type: ReDIF-Article 1.0 Author-Name: Paul Bekker Author-X-Name-First: Paul Author-X-Name-Last: Bekker Author-Name: Joëlle van Essen Author-X-Name-First: Joëlle Author-X-Name-Last: van Essen Title: ML and GMM with concentrated instruments in the static panel data model Abstract: We study the asymptotic behavior of instrumental variable estimators in the static panel model under many-instruments asymptotics. We provide new estimators and standard errors based on concentrated instruments as alternatives to an estimator based on maximum likelihood. We prove that the latter estimator is consistent under many-instruments asymptotics only if the starting value in an iterative procedure is root-N consistent. A similar approach for continuous updating GMM shows the derivation is nontrivial. For the standard cross-sectional case (T = 1), the simple formulation of standard errors offer an alternative to earlier formulations. Journal: Econometric Reviews Pages: 181-195 Issue: 2 Volume: 39 Year: 2020 Month: 2 X-DOI: 10.1080/07474938.2019.1580946 File-URL: http://hdl.handle.net/10.1080/07474938.2019.1580946 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:2:p:181-195 Template-Type: ReDIF-Article 1.0 Author-Name: Zhengyu Zhang Author-X-Name-First: Zhengyu Author-X-Name-Last: Zhang Author-Name: Zequn Jin Author-X-Name-First: Zequn Author-X-Name-Last: Jin Title: Identification and estimation in a linear correlated random coefficients model with censoring Abstract: In this paper, we study the identification and estimation of a linear correlated random coefficients model with censoring, namely, Y=max{B0+X′B,C}, where C is a known constant or an unknown function of regressors. Here, random coefficients (B0,B) can be correlated with one or more components of X. Under a generalized conditional median restriction similar to that in Hoderlein and Sherman, we show that both the average partial effect and the average partial effect on the treated are identified. We develop estimators for the identified parameters and analyze their large sample properties. A Monte Carlo simulation indicates that our estimators perform reasonably well with small samples. We then present an application. Journal: Econometric Reviews Pages: 196-213 Issue: 2 Volume: 39 Year: 2020 Month: 2 X-DOI: 10.1080/07474938.2019.1580949 File-URL: http://hdl.handle.net/10.1080/07474938.2019.1580949 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:2:p:196-213 Template-Type: ReDIF-Article 1.0 Author-Name: Mototsugu Shintani Author-X-Name-First: Mototsugu Author-X-Name-Last: Shintani Author-Name: Zi-Yi Guo Author-X-Name-First: Zi-Yi Author-X-Name-Last: Guo Title: Improving the finite sample performance of autoregression estimators in dynamic factor models: A bootstrap approach Abstract: We investigate the finite sample properties of the estimator of a persistence parameter of an unobservable common factor when the factor is estimated by the principal components method. When the number of cross-sectional observations is not sufficiently large, relative to the number of time series observations, the autoregressive coefficient estimator of a positively autocorrelated factor is biased downward, and the bias becomes larger for a more persistent factor. Based on theoretical and simulation analyses, we show that bootstrap procedures are effective in reducing the bias, and bootstrap confidence intervals outperform naive asymptotic confidence intervals in terms of the coverage probability. Journal: Econometric Reviews Pages: 360-379 Issue: 4 Volume: 37 Year: 2018 Month: 4 X-DOI: 10.1080/07474938.2015.1092825 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1092825 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:4:p:360-379 Template-Type: ReDIF-Article 1.0 Author-Name: Rosa Bernardini Papalia Author-X-Name-First: Rosa Bernardini Author-X-Name-Last: Papalia Author-Name: Esteban Fernandez-Vazquez Author-X-Name-First: Esteban Author-X-Name-Last: Fernandez-Vazquez Title: Information theoretic methods in small domain estimation Abstract: Small area estimation techniques are becoming increasingly used in survey applications to provide estimates for local areas of interest. The objective of this article is to develop and apply Information Theoretic (IT)-based formulations to estimate small area business and trade statistics. More specifically, we propose a Generalized Maximum Entropy (GME) approach to the problem of small area estimation that exploits auxiliary information relating to other known variables on the population and adjusts for consistency and additivity. The GME formulations, combining information from the sample together with out-of-sample aggregates of the population of interest, can be particularly useful in the context of small area estimation, for both direct and model-based estimators, since they do not require strong distributional assumptions on the disturbances. The performance of the proposed IT formulations is illustrated through real and simulated datasets. Journal: Econometric Reviews Pages: 347-359 Issue: 4 Volume: 37 Year: 2018 Month: 4 X-DOI: 10.1080/07474938.2015.1092834 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1092834 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:4:p:347-359 Template-Type: ReDIF-Article 1.0 Author-Name: Tomasz Woźniak Author-X-Name-First: Tomasz Author-X-Name-Last: Woźniak Title: Granger-causal analysis of GARCH models: A Bayesian approach Abstract: A multivariate GARCH model is used to investigate Granger causality in the conditional variance of time series. Parametric restrictions for the hypothesis of noncausality in conditional variances between two groups of variables, when there are other variables in the system as well, are derived. These novel conditions are convenient for the analysis of potentially large systems of economic variables. To evaluate hypotheses of noncausality, a Bayesian testing procedure is proposed. It avoids the singularity problem that may appear in the Wald test, and it relaxes the assumption of the existence of higher-order moments of the residuals required in classical tests. Journal: Econometric Reviews Pages: 325-346 Issue: 4 Volume: 37 Year: 2018 Month: 4 X-DOI: 10.1080/07474938.2015.1092839 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1092839 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:4:p:325-346 Template-Type: ReDIF-Article 1.0 Author-Name: E. C. Brechmann Author-X-Name-First: E. C. Author-X-Name-Last: Brechmann Author-Name: M. Heiden Author-X-Name-First: M. Author-X-Name-Last: Heiden Author-Name: Y. Okhrin Author-X-Name-First: Y. Author-X-Name-Last: Okhrin Title: A multivariate volatility vine copula model Abstract: This article proposes a dynamic framework for modeling and forecasting of realized covariance matrices using vine copulas to allow for more flexible dependencies between assets. Our model automatically guarantees positive definiteness of the forecast through the use of a Cholesky decomposition of the realized covariance matrix. We explicitly account for long-memory behavior by using fractionally integrated autoregressive moving average (ARFIMA) and heterogeneous autoregressive (HAR) models for the individual elements of the decomposition. Furthermore, our model incorporates non-Gaussian innovations and GARCH effects, accounting for volatility clustering and unconditional kurtosis. The dependence structure between assets is studied using vine copula constructions, which allow for nonlinearity and asymmetry without suffering from an inflexible tail behavior or symmetry restrictions as in conventional multivariate models. Further, the copulas have a direct impact on the point forecasts of the realized covariances matrices, due to being computed as a nonlinear transformation of the forecasts for the Cholesky matrix. Beside studying in-sample properties, we assess the usefulness of our method in a one-day-ahead forecasting framework, comparing recent types of models for the realized covariance matrix based on a model confidence set approach. Additionally, we find that in Value-at-Risk (VaR) forecasting, vine models require less capital requirements due to smoother and more accurate forecasts. Journal: Econometric Reviews Pages: 281-308 Issue: 4 Volume: 37 Year: 2018 Month: 4 X-DOI: 10.1080/07474938.2015.1096695 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1096695 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:4:p:281-308 Template-Type: ReDIF-Article 1.0 Author-Name: Christian M. Hafner Author-X-Name-First: Christian M. Author-X-Name-Last: Hafner Author-Name: Hans Manner Author-X-Name-First: Hans Author-X-Name-Last: Manner Author-Name: Léopold Simar Author-X-Name-First: Léopold Author-X-Name-Last: Simar Title: The “wrong skewness” problem in stochastic frontier models: A new approach Abstract: Stochastic frontier models are widely used to measure, e.g., technical efficiencies of firms. The classical stochastic frontier model often suffers from the empirical artefact that the residuals of the production function may have a positive skewness, whereas a negative one is expected under the model, which leads to estimated full efficiencies of all firms. We propose a new approach to the problem by generalizing the distribution used for the inefficiency variable. This generalized stochastic frontier model allows the sample data to have the wrong skewness while estimating well-defined and nondegenerate efficiency measures. We discuss the statistical properties of the model, and we discuss a test for the symmetry of the error term (no inefficiency). We provide a simulation study to show that our model delivers estimators of efficiency with smaller bias than those of the classical model even if the population skewness has the correct sign. Finally, we apply the model to data of the U.S. textile industry for 1958–2005 and show that for a number of years our model suggests technical efficiencies well below the frontier while the classical one estimates no inefficiency in those years. Journal: Econometric Reviews Pages: 380-400 Issue: 4 Volume: 37 Year: 2018 Month: 4 X-DOI: 10.1080/07474938.2016.1140284 File-URL: http://hdl.handle.net/10.1080/07474938.2016.1140284 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:4:p:380-400 Template-Type: ReDIF-Article 1.0 Author-Name: Yong Bao Author-X-Name-First: Yong Author-X-Name-Last: Bao Title: The asymptotic covariance matrix of the QMLE in ARMA models Abstract: A compact analytical representation of the asymptotic covariance matrix, in terms of model parameters directly, of the quasi maximum likelihood estimator (QMLE) is derived in autoregressive moving average (ARMA) models with possible nonzero means and non-Gaussian error terms. For model parameters excluding the error variance, it is found that the Huber (1967) sandwich form for the asymptotic covariance matrix degenerates into the inverse of the associated information matrix. In comparison to the existing result that involves the second moments of some auxiliary variables for the case of zero-mean ARMA models, the analytical asymptotic covariance in this article has an advantage in that it can be conveniently estimated by plugging in the estimated model parameters directly. Journal: Econometric Reviews Pages: 309-324 Issue: 4 Volume: 37 Year: 2018 Month: 4 X-DOI: 10.1080/07474938.2016.1140287 File-URL: http://hdl.handle.net/10.1080/07474938.2016.1140287 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:4:p:309-324 Template-Type: ReDIF-Article 1.0 Author-Name: Young Min Kim Author-X-Name-First: Young Min Author-X-Name-Last: Kim Author-Name: Kyu Ho Kang Author-X-Name-First: Kyu Ho Author-X-Name-Last: Kang Title: Likelihood inference for dynamic linear models with Markov switching parameters: on the efficiency of the Kim filter Abstract: The Kim filter (KF) approximation is widely used for the likelihood calculation of dynamic linear models with Markov regime-switching parameters. However, despite its popularity, its approximation error has not yet been examined rigorously. Therefore, this study investigates the reliability of the KF approximation for maximum likelihood (ML) and Bayesian estimations. To measure the approximation error, we compare the outcomes of the KF method with those of the auxiliary particle filter (APF). The APF is a numerical method that requires a longer computing time, but its numerical error can be sufficiently minimized by increasing simulation size. According to our extensive simulation and empirical studies, the likelihood values obtained from the KF approximation are practically identical to those of the APF. Furthermore, we show that the KF method is reliable, particularly when regimes are persistent and sample size is small. From the Bayesian perspective, we show that the KF method improves the efficiency of posterior simulation. This study contributes to the literature by providing evidence to justify the use of the KF method in both ML and Bayesian estimations. Journal: Econometric Reviews Pages: 1109-1130 Issue: 10 Volume: 38 Year: 2019 Month: 11 X-DOI: 10.1080/07474938.2018.1514027 File-URL: http://hdl.handle.net/10.1080/07474938.2018.1514027 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:10:p:1109-1130 Template-Type: ReDIF-Article 1.0 Author-Name: David I. Harvey Author-X-Name-First: David I. Author-X-Name-Last: Harvey Author-Name: Stephen J. Leybourne Author-X-Name-First: Stephen J. Author-X-Name-Last: Leybourne Author-Name: Yang Zu Author-X-Name-First: Yang Author-X-Name-Last: Zu Title: Testing explosive bubbles with time-varying volatility Abstract: This article considers the problem of testing for an explosive bubble in financial data in the presence of time-varying volatility. We propose a weighted least squares-based variant of the Phillips et al.) test for explosive autoregressive behavior. We find that such an approach has appealing asymptotic power properties, with the potential to deliver substantially greater power than the established OLS-based approach for many volatility and bubble settings. Given that the OLS-based test can outperform the weighted least squares-based test for other volatility and bubble specifications, we also suggest a union of rejections procedure that succeeds in capturing the better power available from the two constituent tests for a given alternative. Our approach involves a nonparametric kernel-based volatility function estimator for computation of the weighted least squares-based statistic, together with the use of a wild bootstrap procedure applied jointly to both individual tests, delivering a powerful testing procedure that is asymptotically size-robust to a wide range of time-varying volatility specifications. Journal: Econometric Reviews Pages: 1131-1151 Issue: 10 Volume: 38 Year: 2019 Month: 11 X-DOI: 10.1080/07474938.2018.1536099 File-URL: http://hdl.handle.net/10.1080/07474938.2018.1536099 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:10:p:1131-1151 Template-Type: ReDIF-Article 1.0 Author-Name: Oliver Grothe Author-X-Name-First: Oliver Author-X-Name-Last: Grothe Author-Name: Tore Selland Kleppe Author-X-Name-First: Tore Selland Author-X-Name-Last: Kleppe Author-Name: Roman Liesenfeld Author-X-Name-First: Roman Author-X-Name-Last: Liesenfeld Title: The Gibbs sampler with particle efficient importance sampling for state-space models* Abstract: We consider Particle Gibbs (PG) for Bayesian analysis of non-linear non-Gaussian state-space models. As a Monte Carlo (MC) approximation of the Gibbs procedure, PG uses sequential MC (SMC) importance sampling inside the Gibbs to update the latent states. We propose to combine PG with the Particle Efficient Importance Sampling (PEIS). By using SMC sampling densities which are approximately globally fully adapted to the targeted density of the states, PEIS can substantially improve the simulation efficiency of the PG relative to existing PG implementations. The efficiency gains are illustrated in PG applications to a non-linear local-level model and stochastic volatility models. Journal: Econometric Reviews Pages: 1152-1175 Issue: 10 Volume: 38 Year: 2019 Month: 11 X-DOI: 10.1080/07474938.2018.1536098 File-URL: http://hdl.handle.net/10.1080/07474938.2018.1536098 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:10:p:1152-1175 Template-Type: ReDIF-Article 1.0 Author-Name: Massimo Franchi Author-X-Name-First: Massimo Author-X-Name-Last: Franchi Author-Name: Paolo Paruolo Author-X-Name-First: Paolo Author-X-Name-Last: Paruolo Title: A general inversion theorem for cointegration Abstract: A generalization of the Granger and the Johansen Representation Theorems valid for any (possibly fractional) order of integration is presented. This Representation Theorem is based on inversion results that characterize the order of the pole and the coefficients of the Laurent series representation of the inverse of a matrix function around a singular point. Explicit expressions of the matrix coefficients of the (polynomial) cointegrating relations, of the Common Trends and of the Triangular representations are provided, either starting from the Moving Average or the Auto Regressive form. This contribution unifies different approaches in the literature and extends them to an arbitrary order of integration. The role of deterministic terms is discussed in detail. Journal: Econometric Reviews Pages: 1176-1201 Issue: 10 Volume: 38 Year: 2019 Month: 11 X-DOI: 10.1080/07474938.2018.1536100 File-URL: http://hdl.handle.net/10.1080/07474938.2018.1536100 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:10:p:1176-1201 Template-Type: ReDIF-Article 1.0 Author-Name: Shuo Li Author-X-Name-First: Shuo Author-X-Name-Last: Li Author-Name: Yundong Tu Author-X-Name-First: Yundong Author-X-Name-Last: Tu Title: A joint test for parametric specification and independence in nonlinear regression models Abstract: This paper develops a testing procedure to simultaneously check (i) the independence between the error and the regressor(s), and (ii) the parametric specification in nonlinear regression models. This procedure generalizes the existing work of Sen and Sen [“Testing Independence and Goodness-of-fit in Linear Models,” Biometrika, 101, 927–942.] to a regression setting that allows any smooth parametric form of the regression function. We establish asymptotic theory for the test procedure under both conditional homoscedastic error and heteroscedastic error. The derived tests are easily implementable, asymptotically normal, and consistent against a large class of fixed alternatives. Besides, the local power performance is investigated. To calibrate the finite sample distribution of the test statistics, a smooth bootstrap procedure is proposed and found work well in simulation studies. Finally, two real data examples are analyzed to illustrate the practical merit of our proposed tests. Journal: Econometric Reviews Pages: 1202-1215 Issue: 10 Volume: 38 Year: 2019 Month: 11 X-DOI: 10.1080/07474938.2018.1536101 File-URL: http://hdl.handle.net/10.1080/07474938.2018.1536101 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:10:p:1202-1215 Template-Type: ReDIF-Article 1.0 Author-Name: The Editors Title: List of Referees Journal: Econometric Reviews Pages: 1216-1217 Issue: 10 Volume: 38 Year: 2019 Month: 11 X-DOI: 10.1080/07474938.2019.1630074 File-URL: http://hdl.handle.net/10.1080/07474938.2019.1630074 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:10:p:1216-1217 Template-Type: ReDIF-Article 1.0 Author-Name: Federico Martellosio Author-X-Name-First: Federico Author-X-Name-Last: Martellosio Title: Testing for Spatial Autocorrelation: The Regressors that Make the Power Disappear Abstract: We show that for any sample size, any size of the test, and any weights matrix outside a small class of exceptions, there exists a positive measure set of regression spaces such that the power of the Cliff–Ord test vanishes as the autocorrelation increases in a spatial error model. This result extends to the tests that define the Gaussian power envelope of all invariant tests for residual spatial autocorrelation. In most cases, the regression spaces such that the problem occurs depend on the size of the test, but there also exist regression spaces such that the power vanishes regardless of the size. A characterization of such particularly hostile regression spaces is provided. Journal: Econometric Reviews Pages: 215-240 Issue: 2 Volume: 31 Year: 2012 X-DOI: 10.1080/07474938.2011.553571 File-URL: http://hdl.handle.net/10.1080/07474938.2011.553571 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:31:y:2012:i:2:p:215-240 Template-Type: ReDIF-Article 1.0 Author-Name: Silvia Platoni Author-X-Name-First: Silvia Author-X-Name-Last: Platoni Author-Name: Paolo Sckokai Author-X-Name-First: Paolo Author-X-Name-Last: Sckokai Author-Name: Daniele Moro Author-X-Name-First: Daniele Author-X-Name-Last: Moro Title: A Note on Two-Way ECM Estimation of SUR Systems on Unbalanced Panel Data Abstract: This article considers the two-way error components model (ECM) estimation of seemingly unrelated regressions (SUR) on unbalanced panel by generalized least squares (GLS). As suggested by Biørn (2004) for the one-way case, in order to use the standard results for the balanced case the individuals are arranged in groups according to the number of times they are observed. Thus, the GLS estimator can be interpreted as a matrix weighted average of the group specific GLS estimators with weights equal to the inverse of their respective covariance matrices. Journal: Econometric Reviews Pages: 119-141 Issue: 2 Volume: 31 Year: 2012 X-DOI: 10.1080/07474938.2011.607098 File-URL: http://hdl.handle.net/10.1080/07474938.2011.607098 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:31:y:2012:i:2:p:119-141 Template-Type: ReDIF-Article 1.0 Author-Name: Haiqiang Chen Author-X-Name-First: Haiqiang Author-X-Name-Last: Chen Author-Name: Terence Chong Author-X-Name-First: Terence Author-X-Name-Last: Chong Author-Name: Jushan Bai Author-X-Name-First: Jushan Author-X-Name-Last: Bai Title: Theory and Applications of TAR Model with Two Threshold Variables Abstract: A growing body of threshold models has been developed over the past two decades to capture the nonlinear movement of financial time series. Most of these models, however, contain a single threshold variable only. In many empirical applications, models with two or more threshold variables are needed. This article develops a new threshold autoregressive model which contains two threshold variables. A likelihood ratio test is proposed to determine the number of regimes in the model. The finite-sample performance of the estimators is evaluated and an empirical application is provided. Journal: Econometric Reviews Pages: 142-170 Issue: 2 Volume: 31 Year: 2012 X-DOI: 10.1080/07474938.2011.607100 File-URL: http://hdl.handle.net/10.1080/07474938.2011.607100 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:31:y:2012:i:2:p:142-170 Template-Type: ReDIF-Article 1.0 Author-Name: Myoung-Jae Lee Author-X-Name-First: Myoung-Jae Author-X-Name-Last: Lee Title: Semiparametric Estimators for Limited Dependent Variable (LDV) Models with Endogenous Regressors Abstract: This article reviews semiparametric estimators for limited dependent variable (LDV) models with endogenous regressors, where nonlinearity and nonseparability pose difficulties. We first introduce six main approaches in the linear equation system literature to handle endogenous regressors with linear projections: (i) ‘substitution’ replacing the endogenous regressors with their projected versions on the system exogenous regressors x, (ii) instrumental variable estimator (IVE) based on E{(error) × x} = 0, (iii) ‘model-projection’ turning the original model into a model in terms of only x-projected variables, (iv) ‘system reduced form (RF)’ finding RF parameters first and then the structural form (SF) parameters, (v) ‘artificial instrumental regressor’ using instruments as artificial regressors with zero coefficients, and (vi) ‘control function’ adding an extra term as a regressor to control for the endogeneity source. We then check if these approaches are applicable to LDV models using conditional mean/quantiles instead of linear projection. The six approaches provide a convenient forum on which semiparametric estimators in the literature can be categorized, although there are a few exceptions. The pros and cons of the approaches are discussed, and a small-scale simulation study is provided for some reviewed estimators. Journal: Econometric Reviews Pages: 171-214 Issue: 2 Volume: 31 Year: 2012 X-DOI: 10.1080/07474938.2011.607101 File-URL: http://hdl.handle.net/10.1080/07474938.2011.607101 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:31:y:2012:i:2:p:171-214 Template-Type: ReDIF-Article 1.0 Author-Name: Ron Smith Author-X-Name-First: Ron Author-X-Name-Last: Smith Title: Review of Microfit5 Journal: Econometric Reviews Pages: 241-244 Issue: 2 Volume: 31 Year: 2012 X-DOI: 10.1080/07474938.2011.607102 File-URL: http://hdl.handle.net/10.1080/07474938.2011.607102 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:31:y:2012:i:2:p:241-244 Template-Type: ReDIF-Article 1.0 Author-Name: James A. Duffy Author-X-Name-First: James A. Author-X-Name-Last: Duffy Author-Name: David F. Hendry Author-X-Name-First: David F. Author-X-Name-Last: Hendry Title: The impact of integrated measurement errors on modeling long-run macroeconomic time series Abstract: Data spanning long time periods, such as that over 1860–2012 for the UK, seem likely to have substantial errors of measurement that may even be integrated of order one, but which are probably cointegrated for cognate variables. We analyze and simulate the impacts of such measurement errors on parameter estimates and tests in a bivariate cointegrated system with trends and location shifts which reflect the many major turbulent events that have occurred historically. When trends or shifts therein are large, cointegration analysis is not much affected by such measurement errors, leading to conventional stationary attenuation biases dependent on the measurement error variance, unlike the outcome when there are no offsetting shifts or trends. Journal: Econometric Reviews Pages: 568-587 Issue: 6-9 Volume: 36 Year: 2017 Month: 10 X-DOI: 10.1080/07474938.2017.1307177 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1307177 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:6-9:p:568-587 Template-Type: ReDIF-Article 1.0 Author-Name: Francis X. Diebold Author-X-Name-First: Francis X. Author-X-Name-Last: Diebold Author-Name: Minchul Shin Author-X-Name-First: Minchul Author-X-Name-Last: Shin Title: Assessing point forecast accuracy by stochastic error distance Abstract: We propose point forecast accuracy measures based directly on distance of the forecast-error c.d.f. from the unit step function at 0 (“stochastic error distance,” or SED). We provide a precise characterization of the relationship between SED and standard predictive loss functions, and we show that all such loss functions can be written as weighted SEDs. The leading case is absolute error loss. Among other things, this suggests shifting attention away from conditional-mean forecasts and toward conditional-median forecasts. Journal: Econometric Reviews Pages: 588-598 Issue: 6-9 Volume: 36 Year: 2017 Month: 10 X-DOI: 10.1080/07474938.2017.1307247 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1307247 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:6-9:p:588-598 Template-Type: ReDIF-Article 1.0 Author-Name: Paul Catani Author-X-Name-First: Paul Author-X-Name-Last: Catani Author-Name: Timo Teräsvirta Author-X-Name-First: Timo Author-X-Name-Last: Teräsvirta Author-Name: Meiqun Yin Author-X-Name-First: Meiqun Author-X-Name-Last: Yin Title: A Lagrange multiplier test for testing the adequacy of constant conditional correlation GARCH model Abstract: A Lagrange multiplier test for testing the parametric structure of a constant conditional correlation-generalized autoregressive conditional heteroskedasticity (CCC-GARCH) model is proposed. The test is based on decomposing the CCC-GARCH model multiplicatively into two components, one of which represents the null model, whereas the other one describes the misspecification. A simulation study shows that the test has good finite sample properties. We compare the test with other tests for misspecification of multivariate GARCH models. The test has high power against alternatives where the misspecification is in the GARCH parameters and is superior to other tests. The test is not greatly affected by misspecification in the conditional correlations and is therefore well suited for considering misspecification of GARCH equations. Journal: Econometric Reviews Pages: 599-621 Issue: 6-9 Volume: 36 Year: 2017 Month: 10 X-DOI: 10.1080/07474938.2017.1307311 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1307311 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:6-9:p:599-621 Template-Type: ReDIF-Article 1.0 Author-Name: Marcelo C. Medeiros Author-X-Name-First: Marcelo C. Author-X-Name-Last: Medeiros Author-Name: Eduardo F. Mendes Author-X-Name-First: Eduardo F. Author-X-Name-Last: Mendes Title: Adaptive LASSO estimation for ARDL models with GARCH innovations Abstract: In this paper, we show the validity of the adaptive least absolute shrinkage and selection operator (LASSO) procedure in estimating stationary autoregressive distributed lag(p,q) models with innovations in a broad class of conditionally heteroskedastic models. We show that the adaptive LASSO selects the relevant variables with probability converging to one and that the estimator is oracle efficient, meaning that its distribution converges to the same distribution of the oracle-assisted least squares, i.e., the least square estimator calculated as if we knew the set of relevant variables beforehand. Finally, we show that the LASSO estimator can be used to construct the initial weights. The performance of the method in finite samples is illustrated using Monte Carlo simulation. Journal: Econometric Reviews Pages: 622-637 Issue: 6-9 Volume: 36 Year: 2017 Month: 10 X-DOI: 10.1080/07474938.2017.1307319 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1307319 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:6-9:p:622-637 Template-Type: ReDIF-Article 1.0 Author-Name: Manabu Asai Author-X-Name-First: Manabu Author-X-Name-Last: Asai Author-Name: Michael McAleer Author-X-Name-First: Michael Author-X-Name-Last: McAleer Title: The impact of jumps and leverage in forecasting covolatility Abstract: The paper investigates the impact of jumps in forecasting covolatility, accommodating leverage effects. We modify the preaveraged truncated covariance estimator of Koike (2016) such that the estimated matrix is positive definite. Using this approach, we can disentangle the estimates of the integrated covolatility matrix and jump variations from the quadratic covariation matrix. Empirical results for three stocks traded on the New York Stock Exchange indicate that the cojumps of two assets have a significant impact on future covolatility, but the impact is negligible for forecasting weekly and monthly horizons. Journal: Econometric Reviews Pages: 638-650 Issue: 6-9 Volume: 36 Year: 2017 Month: 10 X-DOI: 10.1080/07474938.2017.1307326 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1307326 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:6-9:p:638-650 Template-Type: ReDIF-Article 1.0 Author-Name: Sam Astill Author-X-Name-First: Sam Author-X-Name-Last: Astill Author-Name: David I. Harvey Author-X-Name-First: David I. Author-X-Name-Last: Harvey Author-Name: Stephen J. Leybourne Author-X-Name-First: Stephen J. Author-X-Name-Last: Leybourne Author-Name: A. M. Robert Taylor Author-X-Name-First: A. M. Robert Author-X-Name-Last: Taylor Title: Tests for an end-of-sample bubble in financial time series Abstract: In this paper, we examine the issue of detecting explosive behavior in economic and financial time series when an explosive episode is both ongoing at the end of the sample and of finite length. We propose a testing strategy based on a subsampling method in which a suitable test statistic is calculated on a finite number of end-of-sample observations, with a critical value obtained using subsample test statistics calculated on the remaining observations. This approach also has the practical advantage that, by virtue of how the critical values are obtained, it can deliver tests which are robust to, among other things, conditional heteroskedasticity and serial correlation in the driving shocks. We also explore modifications of the raw statistics to account for unconditional heteroskedasticity using studentization and a White-type correction. We evaluate the finite sample size and power properties of our proposed procedures and find that they offer promising levels of power, suggesting the possibility for earlier detection of end-of-sample bubble episodes compared to existing procedures. Journal: Econometric Reviews Pages: 651-666 Issue: 6-9 Volume: 36 Year: 2017 Month: 10 X-DOI: 10.1080/07474938.2017.1307490 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1307490 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:6-9:p:651-666 Template-Type: ReDIF-Article 1.0 Author-Name: Alastair R. Hall Author-X-Name-First: Alastair R. Author-X-Name-Last: Hall Author-Name: Denise R. Osborn Author-X-Name-First: Denise R. Author-X-Name-Last: Osborn Author-Name: Nikolaos Sakkas Author-X-Name-First: Nikolaos Author-X-Name-Last: Sakkas Title: The asymptotic behaviour of the residual sum of squares in models with multiple break points Abstract: Models with multiple discrete breaks in parameters are usually estimated via least squares. This paper, first, derives the asymptotic expectation of the residual sum of squares and shows that the number of estimated break points and the number of regression parameters affect the expectation differently. Second, we propose a statistic for testing the joint hypothesis that the breaks occur at specified points in the sample. Our analytical results cover models estimated by the ordinary, nonlinear, and two-stage least squares. An application to U.S. monetary policy rejects the assumption that breaks are associated with changes in the chair of the Fed. Journal: Econometric Reviews Pages: 667-698 Issue: 6-9 Volume: 36 Year: 2017 Month: 10 X-DOI: 10.1080/07474938.2017.1307523 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1307523 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:6-9:p:667-698 Template-Type: ReDIF-Article 1.0 Author-Name: Nicholas M. Kiefer Author-X-Name-First: Nicholas M. Author-X-Name-Last: Kiefer Title: Correlated defaults, temporal correlation, expert information and predictability of default rates Abstract: Dependence among defaults both across assets and over time is an important characteristic of financial risk. A Bayesian approach to default rate estimation is proposed and illustrated using prior distributions assessed from an experienced industry expert. Two extensions of the binomial model are proposed. The first allows correlated defaults yet remains consistent with Basel II’s asymptotic single-factor model. The second adds temporal correlation in default rates through autocorrelation in the systemic factor. Implications for the predictability of default rates are considered. The single-factor model generates more forecast uncertainty than does the parameter uncertainty. A robustness exercise illustrates that the correlation indicated by the data is much smaller than that specified in the Basel II regulations. Journal: Econometric Reviews Pages: 699-712 Issue: 6-9 Volume: 36 Year: 2017 Month: 10 X-DOI: 10.1080/07474938.2017.1307547 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1307547 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:6-9:p:699-712 Template-Type: ReDIF-Article 1.0 Author-Name: Jean-Marie Dufour Author-X-Name-First: Jean-Marie Author-X-Name-Last: Dufour Author-Name: Richard Luger Author-X-Name-First: Richard Author-X-Name-Last: Luger Title: Identification-robust moment-based tests for Markov switching in autoregressive models Abstract: This paper develops tests of the null hypothesis of linearity in the context of autoregressive models with Markov-switching means and variances. These tests are robust to the identification failures that plague conventional likelihood-based inference methods. The approach exploits the moments of normal mixtures implied by the regime-switching process and uses Monte Carlo test techniques to deal with the presence of an autoregressive component in the model specification. The proposed tests have very respectable power in comparison with the optimal tests for Markov-switching parameters of Carrasco et al. (2014), and they are also quite attractive owing to their computational simplicity. The new tests are illustrated with an empirical application to an autoregressive model of USA output growth. Journal: Econometric Reviews Pages: 713-727 Issue: 6-9 Volume: 36 Year: 2017 Month: 10 X-DOI: 10.1080/07474938.2017.1307548 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1307548 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:6-9:p:713-727 Template-Type: ReDIF-Article 1.0 Author-Name: Yongmiao Hong Author-X-Name-First: Yongmiao Author-X-Name-Last: Hong Author-Name: Xia Wang Author-X-Name-First: Xia Author-X-Name-Last: Wang Author-Name: Wenjie Zhang Author-X-Name-First: Wenjie Author-X-Name-Last: Zhang Author-Name: Shouyang Wang Author-X-Name-First: Shouyang Author-X-Name-Last: Wang Title: An efficient integrated nonparametric entropy estimator of serial dependence Abstract: We propose an efficient numerical integration-based nonparametric entropy estimator for serial dependence and show that the new entropy estimator has a smaller asymptotic variance than Hong and White’s (2005) sample average-based estimator. This delivers an asymptotically more efficient test for serial dependence. In particular, the uniform kernel gives the smallest asymptotic variance for the numerical integration-based entropy estimator over a class of positive kernel functions. Moreover, the naive bootstrap can be used to obtain accurate inferences for our test, whereas it is not applicable to Hong and White’s (2005) sample averaging approach. A simulation study confirms the merits of our approach. Journal: Econometric Reviews Pages: 728-780 Issue: 6-9 Volume: 36 Year: 2017 Month: 10 X-DOI: 10.1080/07474938.2017.1307564 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1307564 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:6-9:p:728-780 Template-Type: ReDIF-Article 1.0 Author-Name: Amos Golan Author-X-Name-First: Amos Author-X-Name-Last: Golan Author-Name: Aman Ullah Author-X-Name-First: Aman Author-X-Name-Last: Ullah Title: Interval estimation: An information theoretic approach Abstract: We develop here an alternative information theoretic method of inference of problems in which all of the observed information is in terms of intervals. We focus on the unconditional case in which the observed information is in terms the minimal and maximal values at each period. Given interval data, we infer the joint and marginal distributions of the interval variable and its range. Our inferential procedure is based on entropy maximization subject to multidimensional moment conditions and normalization in which the entropy is defined over discretized intervals. The discretization is based on theory or empirically observed quantities. The number of estimated parameters is independent of the discretization so the level of discretization does not change the fundamental level of complexity of our model. As an example, we apply our method to study the weather pattern for Los Angeles and New York City across the last century. Journal: Econometric Reviews Pages: 781-795 Issue: 6-9 Volume: 36 Year: 2017 Month: 10 X-DOI: 10.1080/07474938.2017.1307573 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1307573 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:6-9:p:781-795 Template-Type: ReDIF-Article 1.0 Author-Name: Mehdi Shoja Author-X-Name-First: Mehdi Author-X-Name-Last: Shoja Author-Name: Ehsan S. Soofi Author-X-Name-First: Ehsan S. Author-X-Name-Last: Soofi Title: Uncertainty, information, and disagreement of economic forecasters Abstract: An information framework is proposed for studying uncertainty and disagreement of economic forecasters. This framework builds upon the mixture model of combining density forecasts through a systematic application of the information theory. The framework encompasses the measures used in the literature and leads to their generalizations. The focal measure is the Jensen–Shannon divergence of the mixture which admits Kullback–Leibler and mutual information representations. Illustrations include exploring the dynamics of the individual and aggregate uncertainty about the US inflation rate using the survey of professional forecasters (SPF). We show that the normalized entropy index corrects some of the distortions caused by changes of the design of the SPF over time. Bayesian hierarchical models are used to examine the association of the inflation uncertainty with the anticipated inflation and the dispersion of point forecasts. Implementation of the information framework based on the variance and Dirichlet model for capturing uncertainty about the probability distribution of the economic variable are briefly discussed. Journal: Econometric Reviews Pages: 796-817 Issue: 6-9 Volume: 36 Year: 2017 Month: 10 X-DOI: 10.1080/07474938.2017.1307577 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1307577 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:6-9:p:796-817 Template-Type: ReDIF-Article 1.0 Author-Name: Peter C. B. Phillips Author-X-Name-First: Peter C. B. Author-X-Name-Last: Phillips Title: Reduced forms and weak instrumentation Abstract: This paper develops exact finite sample and asymptotic distributions for a class of reduced form estimators and predictors, allowing for the presence of unidentified or weakly identified structural equations. Weak instrument asymptotic theory is developed directly from finite sample results, unifying earlier findings and showing the usefulness of structural information in making predictions from reduced form systems in applications. Asymptotic results are reported for predictions from models with many weak instruments. Of particular interest is the finding that, in unidentified and weakly identified structural models, partially restricted reduced form predictors have considerably smaller forecast mean square errors than unrestricted reduced forms. These results are related to the use of shrinkage methods in system-wide reduced form estimation. Journal: Econometric Reviews Pages: 818-839 Issue: 6-9 Volume: 36 Year: 2017 Month: 10 X-DOI: 10.1080/07474938.2017.1307578 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1307578 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:6-9:p:818-839 Template-Type: ReDIF-Article 1.0 Author-Name: Bruce E. Hansen Author-X-Name-First: Bruce E. Author-X-Name-Last: Hansen Title: Stein-like 2SLS estimator Abstract: Maasoumi (1978) proposed a Stein-like estimator for simultaneous equations and showed that his Stein shrinkage estimator has bounded finite sample risk, unlike the three-stage least square estimator. We revisit his proposal by investigating Stein-like shrinkage in the context of two-stage least square (2SLS) estimation of a structural parameter. Our estimator follows Maasoumi (1978) in taking a weighted average of the 2SLS and ordinary least square estimators, with the weight depending inversely on the Hausman (1978) statistic for exogeneity. Using a local-to-exogenous asymptotic theory, we derive the asymptotic distribution of the Stein estimator and calculate its asymptotic risk. We find that if the number of endogenous variables exceeds 2, then the shrinkage estimator has strictly smaller risk than the 2SLS estimator, extending the classic result of James and Stein (1961). In a simple simulation experiment, we show that the shrinkage estimator has substantially reduced finite sample median squared error relative to the standard 2SLS estimator. Journal: Econometric Reviews Pages: 840-852 Issue: 6-9 Volume: 36 Year: 2017 Month: 10 X-DOI: 10.1080/07474938.2017.1307579 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1307579 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:6-9:p:840-852 Template-Type: ReDIF-Article 1.0 Author-Name: Badi H. Baltagi Author-X-Name-First: Badi H. Author-X-Name-Last: Baltagi Author-Name: Chihwa Kao Author-X-Name-First: Chihwa Author-X-Name-Last: Kao Author-Name: Fa Wang Author-X-Name-First: Fa Author-X-Name-Last: Wang Title: Asymptotic power of the sphericity test under weak and strong factors in a fixed effects panel data model Abstract: This paper studies the asymptotic power for the sphericity test in a fixed effect panel data model proposed by Baltagi et al. (2011), (JBFK). This is done under the alternative hypotheses of weak and strong factors. By weak factors, we mean that the Euclidean norm of the vector of the factor loadings is O(1). By strong factors, we mean that the Euclidean norm of the vector of factor loadings is \begin{equation}O(\sqrt{n})\end{equation}O(n), where n is the number of individuals in the panel. To derive the limiting distribution of JBFK under the alternative, we first derive the limiting distribution of its raw data counterpart. Our results show that, when the factor is strong, the test statistic diverges in probability to infinity as fast as Op(nT). However, when the factor is weak, its limiting distribution is a rightward mean shift of the limit distribution under the null. Second, we derive the asymptotic behavior of the difference between JBFK and its raw data counterpart. Our results show that when the factor is strong, this difference is as large as Op(n). In contrast, when the factor is weak, this difference converges in probability to a constant. Taken together, these results imply that when the factor is strong, JBFK is consistent, but when the factor is weak, JBFK is inconsistent even though its asymptotic power is nontrivial. Journal: Econometric Reviews Pages: 853-882 Issue: 6-9 Volume: 36 Year: 2017 Month: 10 X-DOI: 10.1080/07474938.2017.1307580 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1307580 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:6-9:p:853-882 Template-Type: ReDIF-Article 1.0 Author-Name: Cheng Hsiao Author-X-Name-First: Cheng Author-X-Name-Last: Hsiao Author-Name: Qiankun Zhou Author-X-Name-First: Qiankun Author-X-Name-Last: Zhou Title: First difference or forward demeaning: Implications for the method of moments estimators Abstract: In this paper, we consider the method of moment estimation for dynamic panel models based on either forward demeaning (FOD) or first difference (FD) transformations to eliminate the individual-specific effects, using either all lags or one lag as instruments. We show that the Arellano–Bond-type generalized method of moment (GMM) based on FD is asymptotically biased of order \begin{equation}\sqrt{c}\end{equation}c using all lags or one lag as instruments where \begin{equation}c={{T} \over {N}}\lte{}\infty \end{equation}c=TN<∞ as N,T→∞. For GMM based on FOD, it is asymptotically biased of order \begin{equation}\sqrt{c}\end{equation}c when using all lags, but it is asymptotically unbiased when using only fixed number of lags as instruments. We also discuss these findings in light of the simple IV estimator. Monte Carlo simulations confirm our findings in this paper. Journal: Econometric Reviews Pages: 883-897 Issue: 6-9 Volume: 36 Year: 2017 Month: 10 X-DOI: 10.1080/07474938.2017.1307594 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1307594 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:6-9:p:883-897 Template-Type: ReDIF-Article 1.0 Author-Name: Majid M. Al-Sadoon Author-X-Name-First: Majid M. Author-X-Name-Last: Al-Sadoon Author-Name: Tong Li Author-X-Name-First: Tong Author-X-Name-Last: Li Author-Name: M. Hashem Pesaran Author-X-Name-First: M. Hashem Author-X-Name-Last: Pesaran Title: Exponential class of dynamic binary choice panel data models with fixed effects Abstract: This paper proposes an exponential class of dynamic binary choice panel data models for the analysis of short T (time dimension) large N (cross section dimension) panel data sets that allow for unobserved heterogeneity (fixed effects) to be arbitrarily correlated with the covariates. The paper derives moment conditions that are invariant to the fixed effects which are then used to identify and estimate the parameters of the model. Accordingly, generalized method of moments (GMM) estimators are proposed that are consistent and asymptotically normally distributed at the root-N rate. We also study the conditional likelihood approach and show that under exponential specification, it can identify the effect of state dependence but not the effects of other covariates. Monte Carlo experiments show satisfactory finite sample performance for the proposed estimators and investigate their robustness to misspecification. Journal: Econometric Reviews Pages: 898-927 Issue: 6-9 Volume: 36 Year: 2017 Month: 10 X-DOI: 10.1080/07474938.2017.1307597 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1307597 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:6-9:p:898-927 Template-Type: ReDIF-Article 1.0 Author-Name: Bertille Antoine Author-X-Name-First: Bertille Author-X-Name-Last: Antoine Author-Name: Eric Renault Author-X-Name-First: Eric Author-X-Name-Last: Renault Title: On the relevance of weaker instruments Abstract: We study the asymptotic properties of the standard GMM estimator when additional moment restrictions, weaker than the original ones, are available. We provide conditions under which these additional weaker restrictions improve the efficiency of the GMM estimator. To detect “spurious” identification that may come from invalid moments, we rely on the Hansen J-test that assesses the compatibility between existing restrictions and additional ones. Our simulations reveal that the J-test has good power properties and that its power increases with the weakness of the additional restrictions. Our theoretical characterization of the J-test provides some intuition for why that is. Journal: Econometric Reviews Pages: 928-945 Issue: 6-9 Volume: 36 Year: 2017 Month: 10 X-DOI: 10.1080/07474938.2017.1307598 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1307598 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:6-9:p:928-945 Template-Type: ReDIF-Article 1.0 Author-Name: Xu Han Author-X-Name-First: Xu Author-X-Name-Last: Han Author-Name: Mehmet Caner Author-X-Name-First: Mehmet Author-X-Name-Last: Caner Title: Determining the number of factors with potentially strong within-block correlations in error terms Abstract: We develop methods to estimate the number of factors when error terms have potentially strong correlations in the cross-sectional dimension. The information criteria proposed by Bai and Ng (2002) require the cross-sectional correlations between the error terms to be weak. Violation of this weak correlation assumption may lead to inconsistent estimates of the number of factors. We establish two data-dependent estimators that are consistent whether the error terms are weakly or strongly correlated in the cross-sectional dimension. To handle potentially strong cross-sectional correlations between the error terms, we use a block structure in which the within-block correlation may either be weak or strong, but the between-block correlation is limited. Our estimators allow imperfect knowledge and a moderate misspecification of the block structure. Monte-Carlo simulation results show that our estimators perform similarly to existing methods for cases in which the conventional weak correlation assumption is satisfied. When the error terms have a strong cross-sectional correlation, our estimators outperform the existing methods. Journal: Econometric Reviews Pages: 946-969 Issue: 6-9 Volume: 36 Year: 2017 Month: 10 X-DOI: 10.1080/07474938.2017.1307599 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1307599 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:6-9:p:946-969 Template-Type: ReDIF-Article 1.0 Author-Name: Cong Li Author-X-Name-First: Cong Author-X-Name-Last: Li Author-Name: Hongjun Li Author-X-Name-First: Hongjun Author-X-Name-Last: Li Author-Name: Jeffrey S. Racine Author-X-Name-First: Jeffrey S. Author-X-Name-Last: Racine Title: Cross-validated mixed-datatype bandwidth selection for nonparametric cumulative distribution/survivor functions Abstract: We propose a computationally efficient data-driven least square cross-validation method to optimally select smoothing parameters for the nonparametric estimation of cumulative distribution/survivor functions. We allow for general multivariate covariates that can be continuous, discrete/ordered categorical or a mix of either. We provide asymptotic analysis, examine finite-sample properties through Monte Carlo simulation, and consider an illustration involving nonparametric copula modeling. We also demonstrate how the approach can also be used to construct a smooth Kolmogorov–Smirnov test that has a slightly better power profile than its nonsmooth counterpart. Journal: Econometric Reviews Pages: 970-987 Issue: 6-9 Volume: 36 Year: 2017 Month: 10 X-DOI: 10.1080/07474938.2017.1307900 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1307900 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:6-9:p:970-987 Template-Type: ReDIF-Article 1.0 Author-Name: Zheng Li Author-X-Name-First: Zheng Author-X-Name-Last: Li Author-Name: Guannan Liu Author-X-Name-First: Guannan Author-X-Name-Last: Liu Author-Name: Qi Li Author-X-Name-First: Qi Author-X-Name-Last: Li Title: Nonparametric Knn estimation with monotone constraints Abstract: The K-nearest-neighbor (Knn) method is known to be more suitable in fitting nonparametrically specified curves than the kernel method (with a globally fixed smoothing parameter) when data sets are highly unevenly distributed. In this paper, we propose to estimate a nonparametric regression function subject to a monotonicity restriction using the Knn method. We also propose using a new convergence criterion to measure the closeness between an unconstrained and the (monotone) constrained Knn-estimated curves. This method is an alternative to the monotone kernel methods proposed by Hall and Huang (2001), and Du et al. (2013). We use a bootstrap procedure for testing the validity of the monotone restriction. We apply our method to the “Job Market Matching” data taken from Gan and Li (2016) and find that the unconstrained/constrained Knn estimators work better than kernel estimators for this type of highly unevenly distributed data. Journal: Econometric Reviews Pages: 988-1006 Issue: 6-9 Volume: 36 Year: 2017 Month: 10 X-DOI: 10.1080/07474938.2017.1307904 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1307904 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:6-9:p:988-1006 Template-Type: ReDIF-Article 1.0 Author-Name: Russell Davidson Author-X-Name-First: Russell Author-X-Name-Last: Davidson Title: Diagnostics for the bootstrap and fast double bootstrap Abstract: The bootstrap is typically less reliable in the context of time-series models with serial correlation of unknown form than when regularity conditions for the conventional IID bootstrap apply. It is, therefore, useful to have diagnostic techniques capable of evaluating bootstrap performance in specific cases. Those suggested in this paper are closely related to the fast double bootstrap (FDB) and are not computationally intensive. They can also be used to gauge the performance of the FDB itself. Examples of bootstrapping time series are presented, which illustrate the diagnostic procedures, and show how the results can cast light on bootstrap performance. Journal: Econometric Reviews Pages: 1021-1038 Issue: 6-9 Volume: 36 Year: 2017 Month: 10 X-DOI: 10.1080/07474938.2017.1307918 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1307918 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:6-9:p:1021-1038 Template-Type: ReDIF-Article 1.0 Author-Name: Yong Bao Author-X-Name-First: Yong Author-X-Name-Last: Bao Author-Name: Aman Ullah Author-X-Name-First: Aman Author-X-Name-Last: Ullah Author-Name: Yun Wang Author-X-Name-First: Yun Author-X-Name-Last: Wang Title: Distribution of the mean reversion estimator in the Ornstein–Uhlenbeck process Abstract: We derive the exact distribution of the maximum likelihood estimator of the mean reversion parameter (κ) in the Ornstein–Uhlenbeck process using numerical integration through analytical evaluation of a joint characteristic function. Different scenarios are considered: known or unknown drift term, fixed or random start-up value, and zero or positive κ. Monte Carlo results demonstrate the remarkably reliable performance of our exact approach across all the scenarios. In comparison, misleading results may arise under the asymptotic distributions, including the advocated infill asymptotic distribution, which performs poorly in the tails when there is no intercept in the regression and the starting value of the process is nonzero. Journal: Econometric Reviews Pages: 1039-1056 Issue: 6-9 Volume: 36 Year: 2017 Month: 10 X-DOI: 10.1080/07474938.2017.1307977 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1307977 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:6-9:p:1039-1056 Template-Type: ReDIF-Article 1.0 Author-Name: Yanqin Fan Author-X-Name-First: Yanqin Author-X-Name-Last: Fan Author-Name: Carlos A. Manzanares Author-X-Name-First: Carlos A. Author-X-Name-Last: Manzanares Title: Partial identification of average treatment effects on the treated through difference-in-differences Abstract: The difference-in-differences (DID) method is widely used as a tool for identifying causal effects of treatments in program evaluation. When panel data sets are available, it is well-known that the average treatment effect on the treated (ATT) is point-identified under the DID setup. If a panel data set is not available, repeated cross sections (pretreatment and posttreatment) may be used, but may not point-identify the ATT. This paper systematically studies the identification of the ATT under the DID setup when posttreatment treatment status is unknown for the pretreatment sample. This is done through a novel application of an extension of a continuous version of the classical monotone rearrangement inequality which allows for general copula bounds. The identifying power of an instrumental variable and of a ‘matched subsample’ is also explored. Finally, we illustrate our approach by estimating the effect of the Americans with Disabilities Act of 1991 on employment outcomes of the disabled. Journal: Econometric Reviews Pages: 1057-1080 Issue: 6-9 Volume: 36 Year: 2017 Month: 10 X-DOI: 10.1080/07474938.2017.1308036 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1308036 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:6-9:p:1057-1080 Template-Type: ReDIF-Article 1.0 Author-Name: Christine Amsler Author-X-Name-First: Christine Author-X-Name-Last: Amsler Author-Name: Christopher J. O’Donnell Author-X-Name-First: Christopher J. Author-X-Name-Last: O’Donnell Author-Name: Peter Schmidt Author-X-Name-First: Peter Author-X-Name-Last: Schmidt Title: Stochastic metafrontiers Abstract: We consider the case of production units arranged into a number of groups. All units within a group choose output–input combinations from the same production possibilities set that is represented by a stochastic frontier model. The metafrontier is the envelope of the group-specific frontiers. We are interested in the metafrontier distance, which is the amount by which the group-specific frontier lies below the metafrontier.Previous work has measured the metafrontier distance using the deterministic portion of the frontier. In a stochastic frontier model, this is not appropriate. We show how to evaluate the metafrontier distance, and we demonstrate the empirical relevance of this issue. Journal: Econometric Reviews Pages: 1007-1020 Issue: 6-9 Volume: 36 Year: 2017 Month: 10 X-DOI: 10.1080/07474938.2017.1308345 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1308345 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:6-9:p:1007-1020 Template-Type: ReDIF-Article 1.0 Author-Name: Peter C. B. Phillips Author-X-Name-First: Peter C. B. Author-X-Name-Last: Phillips Author-Name: Aman Ullah Author-X-Name-First: Aman Author-X-Name-Last: Ullah Title: Econometric Reviews honors Esfandiar Maasoumi Journal: Econometric Reviews Pages: 563-567 Issue: 6-9 Volume: 36 Year: 2017 Month: 10 X-DOI: 10.1080/07474938.2017.1312074 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1312074 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:6-9:p:563-567 Template-Type: ReDIF-Article 1.0 Author-Name: Joshua C. C. Chan Author-X-Name-First: Joshua C. C. Author-X-Name-Last: Chan Title: Specification tests for time-varying parameter models with stochastic volatility Abstract: We propose an easy technique to test for time-variation in coefficients and volatilities. Specifically, by using a noncentered parameterization for state space models, we develop a method to directly calculate the relevant Bayes factor using the Savage–Dickey density ratio—thus avoiding the computation of the marginal likelihood altogether. The proposed methodology is illustrated via two empirical applications. In the first application, we test for time-variation in the volatility of inflation in the G7 countries. The second application investigates if there is substantial time-variation in the nonaccelerating inflation rate of unemployment (NAIRU) in the United States. Journal: Econometric Reviews Pages: 807-823 Issue: 8 Volume: 37 Year: 2018 Month: 9 X-DOI: 10.1080/07474938.2016.1167948 File-URL: http://hdl.handle.net/10.1080/07474938.2016.1167948 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:8:p:807-823 Template-Type: ReDIF-Article 1.0 Author-Name: Guillaume Gaetan Martinet Author-X-Name-First: Guillaume Gaetan Author-X-Name-Last: Martinet Author-Name: Michael McAleer Author-X-Name-First: Michael Author-X-Name-Last: McAleer Title: On the invertibility of EGARCH(p, q) Abstract: Of the two most widely estimated univariate asymmetric conditional volatility models, the exponential GARCH (or EGARCH) specification is said to be able to capture asymmetry, which refers to the different effects on conditional volatility of positive and negative effects of equal magnitude, and leverage, which refers to the negative correlation between the returns shocks and subsequent shocks to volatility. However, the statistical properties of the (quasi-)maximum likelihood estimator (QMLE) of the EGARCH(p, q) parameters are not available under general conditions, but only for special cases under highly restrictive and unverifiable sufficient conditions, such as EGARCH(1,0) or EGARCH(1,1), and possibly only under simulation. A limitation in the development of asymptotic properties of the QMLE for the EGARCH(p, q) model is the lack of an invertibility condition for the returns shocks underlying the model. It is shown in this article that the EGARCH(p, q) model can be derived from a stochastic process, for which sufficient invertibility conditions can be stated simply and explicitly when the parameters respect a simple condition.11Using the notation introduced in part 2, this refers to the cases where α ≥ |γ| or α ≤ − |γ|. The first inequality is generally assumed in the literature related to the invertibility of EGARCH. This article provides (in the Appendix) an argument for the possible lack of invertibility when these conditions are not met. This will be useful in reinterpreting the existing properties of the QMLE of the EGARCH(p, q) parameters. Journal: Econometric Reviews Pages: 824-849 Issue: 8 Volume: 37 Year: 2018 Month: 9 X-DOI: 10.1080/07474938.2016.1167994 File-URL: http://hdl.handle.net/10.1080/07474938.2016.1167994 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:8:p:824-849 Template-Type: ReDIF-Article 1.0 Author-Name: Victor Troster Author-X-Name-First: Victor Author-X-Name-Last: Troster Title: Testing for Granger-causality in quantiles Abstract: This paper proposes a consistent parametric test of Granger-causality in quantiles. Although the concept of Granger-causality is defined in terms of the conditional distribution, most articles have tested Granger-causality using conditional mean regression models in which the causal relations are linear. Rather than focusing on a single part of the conditional distribution, we develop a test that evaluates nonlinear causalities and possible causal relations in all conditional quantiles, which provides a sufficient condition for Granger-causality when all quantiles are considered. The proposed test statistic has correct asymptotic size, is consistent against fixed alternatives, and has power against Pitman deviations from the null hypothesis. As the proposed test statistic is asymptotically nonpivotal, we tabulate critical values via a subsampling approach. We present Monte Carlo evidence and an application considering the causal relation between the gold price, the USD/GBP exchange rate, and the oil price. Journal: Econometric Reviews Pages: 850-866 Issue: 8 Volume: 37 Year: 2018 Month: 9 X-DOI: 10.1080/07474938.2016.1172400 File-URL: http://hdl.handle.net/10.1080/07474938.2016.1172400 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:8:p:850-866 Template-Type: ReDIF-Article 1.0 Author-Name: Haiqi Li Author-X-Name-First: Haiqi Author-X-Name-Last: Li Author-Name: Sung Y. Park Author-X-Name-First: Sung Y. Author-X-Name-Last: Park Title: Testing for a unit root in a nonlinear quantile autoregression framework Abstract: The nonlinear unit root test of Kapetanios, Shin, and Snell (2003) (KSS) has attracted much recent attention. However, the KSS test relies on the ordinary least squares (OLS) estimator, which is not robust to a heavy-tailed distribution and, in practice, the test suffers from a large power loss. This study develops three kinds of quantile nonlinear unit root tests: the quantile t-ratio test; the quantile Kolmogorov–Smirnov test; and the quantile Cramer–von Mises test. A Monte Carlo simulation shows that these tests have significantly better power when an innovation follows a non-normal distribution. In addition, the quantile t-ratio test can reveal the heterogeneity of the asymmetric dynamics in a time series. In our empirical studies, we investigate the unit root properties of U.S. macroeconomic time series and the real effective exchange rates for 61 countries. The results show that our proposed tests reject the unit roots more often, indicating that the series are likely to be asymmetric nonlinear reverting processes. Journal: Econometric Reviews Pages: 867-892 Issue: 8 Volume: 37 Year: 2018 Month: 9 X-DOI: 10.1080/00927872.2016.1178871 File-URL: http://hdl.handle.net/10.1080/00927872.2016.1178871 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:8:p:867-892 Template-Type: ReDIF-Article 1.0 Author-Name: Artūras Juodis Author-X-Name-First: Artūras Author-X-Name-Last: Juodis Author-Name: Vasilis Sarafidis Author-X-Name-First: Vasilis Author-X-Name-Last: Sarafidis Title: Fixed T dynamic panel data estimators with multifactor errors Abstract: This article analyzes a growing group of fixed T dynamic panel data estimators with a multifactor error structure. We use a unified notational approach to describe these estimators and discuss their properties in terms of deviations from an underlying set of basic assumptions. Furthermore, we consider the extendability of these estimators to practical situations that may frequently arise, such as their ability to accommodate unbalanced panels and common observed factors. Using a large-scale simulation exercise, we consider scenarios that remain largely unexplored in the literature, albeit being of great empirical relevance. In particular, we examine (i) the effect of the presence of weakly exogenous covariates, (ii) the effect of changing the magnitude of the correlation between the factor loadings of the dependent variable and those of the covariates, (iii) the impact of the number of moment conditions on bias and size for GMM estimators, and finally (iv) the effect of sample size. We apply each of these estimators to a crime application using a panel data set of local government authorities in New South Wales, Australia; we find that the results bear substantially different policy implications relative to those potentially derived from standard dynamic panel GMM estimators. Thus, our study may serve as a useful guide to practitioners who wish to allow for multiplicative sources of unobserved heterogeneity in their model. Journal: Econometric Reviews Pages: 893-929 Issue: 8 Volume: 37 Year: 2018 Month: 9 X-DOI: 10.1080/00927872.2016.1178875 File-URL: http://hdl.handle.net/10.1080/00927872.2016.1178875 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:8:p:893-929 Template-Type: ReDIF-Article 1.0 Author-Name: Milan Nedeljkovic Author-X-Name-First: Milan Author-X-Name-Last: Nedeljkovic Title: A Projection-Based Nonparametric Test of Conditional Quantile Independence Abstract: This paper proposes a nonparametric procedure for testing conditional quantile independence using projections. Relative to existing smoothed nonparametric tests, the resulting test statistic: (i) detects the high frequency local alternatives that converge to the null hypothesis in probability at faster rate and, (ii) yields improvements in the finite sample power when a large number of variables are included under the alternative. In addition, it allows the researcher to include qualitative information and, if desired, direct the test against specific subsets of alternatives without imposing any functional form on them. We use the weighted Nadaraya-Watson (WNW) estimator of the conditional quantile function avoiding the boundary problems in estimation and testing and prove weak uniform consistency (with rate) of the WNW estimator for absolutely regular processes. The procedure is applied to a study of risk spillovers among the banks. We show that the methodology generalizes some of the recently proposed measures of systemic risk and we use the quantile framework to assess the intensity of risk spillovers among individual financial institutions. Journal: Econometric Reviews Pages: 1-26 Issue: 1 Volume: 39 Year: 2020 Month: 1 X-DOI: 10.1080/07474938.2019.1690192 File-URL: http://hdl.handle.net/10.1080/07474938.2019.1690192 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:1:p:1-26 Template-Type: ReDIF-Article 1.0 Author-Name: Ruijun Bu Author-X-Name-First: Ruijun Author-X-Name-Last: Bu Author-Name: Fredj Jawadi Author-X-Name-First: Fredj Author-X-Name-Last: Jawadi Author-Name: Yuyi Li Author-X-Name-First: Yuyi Author-X-Name-Last: Li Title: A multifactor transformed diffusion model with applications to VIX and VIX futures Abstract: Transformed diffusions (TDs) have become increasingly popular in financial modeling for their model flexibility and tractability. While existing TD models are predominately one-factor models, empirical evidence often prefers models with multiple factors. We propose a novel distribution-driven nonlinear multifactor TD model with latent components. Our model is a transformation of a underlying multivariate Ornstein–Uhlenbeck (MVOU) process, where the transformation function is endogenously specified by a flexible parametric stationary distribution of the observed variable. Computationally efficient exact likelihood inference can be implemented for our model using a modified Kalman filter algorithm and the transformed affine structure also allows us to price derivatives in semi-closed form. We compare the proposed multifactor model with existing TD models for modeling VIX and pricing VIX futures. Our results show that the proposed model outperforms all existing TD models both in the sample and out of the sample consistently across all categories and scenarios of our comparison. Journal: Econometric Reviews Pages: 27-53 Issue: 1 Volume: 39 Year: 2020 Month: 1 X-DOI: 10.1080/07474938.2019.1690195 File-URL: http://hdl.handle.net/10.1080/07474938.2019.1690195 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:1:p:27-53 Template-Type: ReDIF-Article 1.0 Author-Name: Fredj Jawadi Author-X-Name-First: Fredj Author-X-Name-Last: Jawadi Author-Name: Zied Ftiti Author-X-Name-First: Zied Author-X-Name-Last: Ftiti Author-Name: Waël Louhichi Author-X-Name-First: Waël Author-X-Name-Last: Louhichi Title: Forecasting energy futures volatility with threshold augmented heterogeneous autoregressive jump models Abstract: This study forecasts the volatility of two energy futures markets (oil and gas), using high-frequency data. We, first, disentangle volatility into continuous volatility and jumps. Second, we apply wavelet analysis to study the relationship between volume and the volatility measures for different horizons. Third, we augment the heterogeneous autoregressive (HAR) model by nonlinearly including both jumps and volume. We then propose different empirical extensions of the HAR model. Our study shows that oil and gas volatilities nonlinearly depend on public information (jumps), private information (continuous volatility), and trading volume. Moreover, our threshold augmented HAR model with heterogeneous jumps and continuous volatility outperforms HAR model in forecasting volatility. Journal: Econometric Reviews Pages: 54-70 Issue: 1 Volume: 39 Year: 2020 Month: 1 X-DOI: 10.1080/07474938.2019.1690190 File-URL: http://hdl.handle.net/10.1080/07474938.2019.1690190 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:1:p:54-70 Template-Type: ReDIF-Article 1.0 Author-Name: Cem Çakmaklı Author-X-Name-First: Cem Author-X-Name-Last: Çakmaklı Title: Modeling the density of US yield curve using Bayesian semiparametric dynamic Nelson-Siegel model Abstract: This paper proposes the Bayesian semiparametric dynamic Nelson-Siegel model for estimating the density of bond yields. Specifically, we model the distribution of the yield curve factors according to an infinite Markov mixture (iMM). The model allows for time variation in the mean and covariance matrix of factors in a discrete manner, as opposed to continuous changes in these parameters such as the Time Varying Parameter (TVP) models. Estimating the number of regimes using the iMM structure endogenously leads to an adaptive process that can generate newly emerging regimes over time in response to changing economic conditions in addition to existing regimes. The potential of the proposed framework is examined using US bond yields data. The semiparametric structure of the factors can handle various forms of non-normalities including fat tails and nonlinear dependence between factors using a unified approach by generating new clusters capturing these specific characteristics. We document that modeling parameter changes in a discrete manner increases the model fit as well as forecasting performance at both short and long horizons relative to models with fixed parameters as well as the TVP model with continuous parameter changes. This is mainly due to fact that the discrete changes in parameters suit the typical low frequency monthly bond yields data characteristics better. Journal: Econometric Reviews Pages: 71-91 Issue: 1 Volume: 39 Year: 2020 Month: 1 X-DOI: 10.1080/07474938.2019.1690191 File-URL: http://hdl.handle.net/10.1080/07474938.2019.1690191 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:1:p:71-91 Template-Type: ReDIF-Article 1.0 Author-Name: Benjamin Williams Author-X-Name-First: Benjamin Author-X-Name-Last: Williams Title: Identification of the linear factor model Abstract: This paper provides several new results on identification of the linear factor model. The model allows for correlated latent factors and dependence among the idiosyncratic errors. I also illustrate identification under a dedicated measurement structure and other reduced rank restrictions. I use these results to study identification in a model with both observed covariates and latent factors. The analysis emphasizes the different roles played by restrictions on the error covariance matrix, restrictions on the factor loadings and the factor covariance matrix, and restrictions on the coefficients on covariates. The identification results are simple, intuitive, and directly applicable to many settings. Journal: Econometric Reviews Pages: 92-109 Issue: 1 Volume: 39 Year: 2020 Month: 1 X-DOI: 10.1080/07474938.2018.1550042 File-URL: http://hdl.handle.net/10.1080/07474938.2018.1550042 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:1:p:92-109 Template-Type: ReDIF-Article 1.0 Author-Name: Alastair R. Hall Author-X-Name-First: Alastair R. Author-X-Name-Last: Hall Title: Foundations of info-metrics: modeling, inference and imperfect information Journal: Econometric Reviews Pages: 110-113 Issue: 1 Volume: 39 Year: 2020 Month: 1 X-DOI: 10.1080/07474938.2019.1682315 File-URL: http://hdl.handle.net/10.1080/07474938.2019.1682315 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:1:p:110-113 Template-Type: ReDIF-Article 1.0 Author-Name: Jin-Huei Yeh Author-X-Name-First: Jin-Huei Author-X-Name-Last: Yeh Author-Name: Jying-Nan Wang Author-X-Name-First: Jying-Nan Author-X-Name-Last: Wang Title: Bias-corrected realized variance Abstract: We propose a novel “bias-corrected realized variance” (BCRV) estimator based upon the appropriate re-weighting of two realized variances calculated at different sampling frequencies. Our bias-correction methodology is found to be extremely accurate, with the finite sample variance being significantly minimized. In our Monte Carlo experiments and a finite sample MSE comparison of alternative estimators, the performance of our straightforward BCRV estimator is shown to be comparable to other widely-used integrated variance estimators. Given its simplicity, our BCRV estimator is likely to appeal to researchers and practitioners alike for the estimation of integrated variance. Journal: Econometric Reviews Pages: 170-192 Issue: 2 Volume: 38 Year: 2019 Month: 2 X-DOI: 10.1080/07474938.2016.1222230 File-URL: http://hdl.handle.net/10.1080/07474938.2016.1222230 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:2:p:170-192 Template-Type: ReDIF-Article 1.0 Author-Name: Rongmao Zhang Author-X-Name-First: Rongmao Author-X-Name-Last: Zhang Author-Name: Chenxue Li Author-X-Name-First: Chenxue Author-X-Name-Last: Li Author-Name: Liang Peng Author-X-Name-First: Liang Author-X-Name-Last: Peng Title: Inference for the tail index of a GARCH(1,1) model and an AR(1) model with ARCH(1) errors Abstract: For a GARCH(1,1) sequence or an AR(1) model with ARCH(1) errors, one can estimate the tail index by solving an estimating equation with unknown parameters replaced by the quasi maximum likelihood estimation, and a profile empirical likelihood method can be employed to effectively construct a confidence interval for the tail index. However, this requires that the errors of such a model have at least a finite fourth moment. In this article, we show that the finite fourth moment can be relaxed by employing a least absolute deviations estimate for the unknown parameters by noting that the estimating equation for determining the tail index is invariant to a scale transformation of the underlying model. Journal: Econometric Reviews Pages: 151-169 Issue: 2 Volume: 38 Year: 2019 Month: 2 X-DOI: 10.1080/07474938.2016.1224024 File-URL: http://hdl.handle.net/10.1080/07474938.2016.1224024 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:2:p:151-169 Template-Type: ReDIF-Article 1.0 Author-Name: Chaohua Dong Author-X-Name-First: Chaohua Author-X-Name-Last: Dong Author-Name: Jiti Gao Author-X-Name-First: Jiti Author-X-Name-Last: Gao Title: Expansion and estimation of Lévy process functionals in nonlinear and nonstationary time series regression Abstract: In this article, we develop a series estimation method for unknown time-inhomogeneous functionals of Lévy processes involved in econometric time series models. To obtain an asymptotic distribution for the proposed estimators, we establish a general asymptotic theory for partial sums of bivariate functionals of time and nonstationary variables. These results show that the proposed estimators in different situations converge to quite different random variables. In addition, the rates of convergence depend on various factors rather than just the sample size. Finite sample simulations are provided to evaluate the finite sample performance of the proposed model and estimation method. Journal: Econometric Reviews Pages: 125-150 Issue: 2 Volume: 38 Year: 2019 Month: 2 X-DOI: 10.1080/07474938.2016.1235305 File-URL: http://hdl.handle.net/10.1080/07474938.2016.1235305 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:2:p:125-150 Template-Type: ReDIF-Article 1.0 Author-Name: Zacharias Psaradakis Author-X-Name-First: Zacharias Author-X-Name-Last: Psaradakis Author-Name: Marián Vávra Author-X-Name-First: Marián Author-X-Name-Last: Vávra Title: Portmanteau tests for linearity of stationary time series Abstract: This article considers the problem of testing for linearity of stationary time series. Portmanteau tests are discussed which are based on generalized correlations of residuals from a linear model (that is, autocorrelations and cross-correlations of different powers of the residuals). The finite-sample properties of the tests are assessed by means of Monte Carlo experiments. The tests are applied to 100 time series of stock returns. Journal: Econometric Reviews Pages: 248-262 Issue: 2 Volume: 38 Year: 2019 Month: 2 X-DOI: 10.1080/07474938.2016.1261015 File-URL: http://hdl.handle.net/10.1080/07474938.2016.1261015 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:2:p:248-262 Template-Type: ReDIF-Article 1.0 Author-Name: Giovanni Forchini Author-X-Name-First: Giovanni Author-X-Name-Last: Forchini Author-Name: Bin Jiang Author-X-Name-First: Bin Author-X-Name-Last: Jiang Title: The unconditional distributions of the OLS, TSLS and LIML estimators in a simple structural equations model Abstract: The exact distributions of the standard estimators of the structural coefficients in a linear structural equations model conditional on the exogenous variables have been shown to have some unexpected and quirky features. Since the argument for conditioning on exogenous (ancillary) variables has been weakened over the past 20 years by the discovery of an “ancillarity paradox,” it is natural to wonder whether such finite sample properties are in fact due to conditioning on the exogenous variables. This article studies the exact distributions of the ordinary least squares (OLS), two-stage least squares (TSLS), and limited information maximum likelihood (LIML) estimators of the structural coefficients in a linear structural equation without conditioning on the exogenous variables. Journal: Econometric Reviews Pages: 208-247 Issue: 2 Volume: 38 Year: 2019 Month: 2 X-DOI: 10.1080/07474938.2016.1261072 File-URL: http://hdl.handle.net/10.1080/07474938.2016.1261072 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:2:p:208-247 Template-Type: ReDIF-Article 1.0 Author-Name: Michael Lechner Author-X-Name-First: Michael Author-X-Name-Last: Lechner Author-Name: Anthony Strittmatter Author-X-Name-First: Anthony Author-X-Name-Last: Strittmatter Title: Practical procedures to deal with common support problems in matching estimation Abstract: This paper assesses the performance of common estimators adjusting for differences in covariates, such as matching and regression, when faced with the so-called common support problems. It also shows how different procedures suggested in the literature affect the properties of such estimators. Based on an empirical Monte Carlo simulation design, a lack of common support is found to increase the root-mean-squared error of all investigated parametric and semiparametric estimators. Dropping observations that are off support usually improves their performance, although the magnitude of the improvement depends on the particular method used. Journal: Econometric Reviews Pages: 193-207 Issue: 2 Volume: 38 Year: 2019 Month: 2 X-DOI: 10.1080/07474938.2017.1318509 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1318509 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:2:p:193-207 Template-Type: ReDIF-Article 1.0 Author-Name: Luis F. Martins Author-X-Name-First: Luis F. Author-X-Name-Last: Martins Title: Bootstrap tests for time varying cointegration Abstract: This article proposes wild and the independent and identically distibuted (i.i.d.) parametric bootstrap implementations of the time-varying cointegration test of Bierens and Martins (2010). The bootstrap statistics and the original likelihood ratio test share the same first-order asymptotic null distribution. Monte Carlo results suggest that the bootstrap approximation to the finite-sample distribution is very accurate, in particular for the wild bootstrap case. The tests are applied to study the purchasing power parity hypothesis for twelve Organisation for Economic Cooperation and Development (OECD) countries and we only find evidence of a constant long-term equilibrium for the U.S.–U.K. relationship. Journal: Econometric Reviews Pages: 466-483 Issue: 5 Volume: 37 Year: 2018 Month: 5 X-DOI: 10.1080/07474938.2015.1092830 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1092830 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:5:p:466-483 Template-Type: ReDIF-Article 1.0 Author-Name: Feng Liu Author-X-Name-First: Feng Author-X-Name-Last: Liu Author-Name: Dong Li Author-X-Name-First: Dong Author-X-Name-Last: Li Author-Name: Xinmei Kang Author-X-Name-First: Xinmei Author-X-Name-Last: Kang Title: Sample path properties of an explosive double autoregressive model Abstract: This article studies sample path properties of an explosive double autoregressive (DAR) model. After suitable renormalization, it is shown that the sample path converges weakly to a geometric Brownian motion. This further strengthens our understanding of sample paths of nonstationary DAR processes. The obtained results can be extended to nonstationary random coefficient autoregressive (RCA) models. Simulation studies are carried out to support our results. Journal: Econometric Reviews Pages: 484-490 Issue: 5 Volume: 37 Year: 2018 Month: 5 X-DOI: 10.1080/07474938.2015.1092841 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1092841 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:5:p:484-490 Template-Type: ReDIF-Article 1.0 Author-Name: Guangyu Mao Author-X-Name-First: Guangyu Author-X-Name-Last: Mao Title: Testing for sphericity in a two-way error components panel data model Abstract: This article is concerned with sphericity test for the two-way error components panel data model. It is found that the John statistic and the bias-corrected LM statistic recently developed by Baltagi et al. (2011)Baltagi et al. (2012, which are based on the within residuals, are not helpful under the present circumstances even though they are in the one-way fixed effects model. However, we prove that when the within residuals are properly transformed, the resulting residuals can serve to construct useful statistics that are similar to those of Baltagi et al. (2011)Baltagi et al. (2012). Simulation results show that the newly proposed statistics perform well under the null hypothesis and several typical alternatives. Journal: Econometric Reviews Pages: 491-506 Issue: 5 Volume: 37 Year: 2018 Month: 5 X-DOI: 10.1080/07474938.2015.1092844 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1092844 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:5:p:491-506 Template-Type: ReDIF-Article 1.0 Author-Name: Masayuki Hirukawa Author-X-Name-First: Masayuki Author-X-Name-Last: Hirukawa Author-Name: Mari Sakudo Author-X-Name-First: Mari Author-X-Name-Last: Sakudo Title: Functional-coefficient cointegration models in the presence of deterministic trends Abstract: In this article, we extend the functional-coefficient cointegration model (FCCM) to the cases in which nonstationary regressors contain both stochastic and deterministic trends. A nondegenerate distributional theory on the local linear (LL) regression smoother of the FCCM is explored. It is demonstrated that even when integrated regressors are endogenous, the limiting distribution is the same as if they were exogenous. Finite-sample performance of the LL estimator is investigated via Monte Carlo simulations in comparison with an alternative estimation method. As an application of the FCCM, electricity demand analysis in Illinois is considered. Journal: Econometric Reviews Pages: 507-533 Issue: 5 Volume: 37 Year: 2018 Month: 5 X-DOI: 10.1080/07474938.2015.1092845 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1092845 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:5:p:507-533 Template-Type: ReDIF-Article 1.0 Author-Name: Koen Bel Author-X-Name-First: Koen Author-X-Name-Last: Bel Author-Name: Dennis Fok Author-X-Name-First: Dennis Author-X-Name-Last: Fok Author-Name: Richard Paap Author-X-Name-First: Richard Author-X-Name-Last: Paap Title: Parameter estimation in multivariate logit models with many binary choices Abstract: Multivariate Logit models are convenient to describe multivariate correlated binary choices as they provide closed-form likelihood functions. However, the computation time required for calculating choice probabilities increases exponentially with the number of choices, which makes maximum likelihood-based estimation infeasible when many choices are considered. To solve this, we propose three novel estimation methods: (i) stratified importance sampling, (ii) composite conditional likelihood (CCL), and (iii) generalized method of moments, which yield consistent estimates and still have similar small-sample bias to maximum likelihood. Our simulation study shows that computation times for CCL are much smaller and that its efficiency loss is small. Journal: Econometric Reviews Pages: 534-550 Issue: 5 Volume: 37 Year: 2018 Month: 5 X-DOI: 10.1080/07474938.2015.1093780 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1093780 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:5:p:534-550 Template-Type: ReDIF-Article 1.0 Author-Name: Simon Reese Author-X-Name-First: Simon Author-X-Name-Last: Reese Author-Name: Joakim Westerlund Author-X-Name-First: Joakim Author-X-Name-Last: Westerlund Title: Estimation of factor-augmented panel regressions with weakly influential factors Abstract: The use of factor-augmented panel regressions has become very popular in recent years. Existing methods for such regressions require that the common factors are strong, an assumption that is likely to be mistaken in practice. Motivated by this, the current article offers an analysis of the effect of weak, semi-weak, and semi-strong factors on two of the most popular estimators for factor-augmented regressions, namely, principal components (PC) and common correlated effects (CCE). Journal: Econometric Reviews Pages: 401-465 Issue: 5 Volume: 37 Year: 2018 Month: 5 X-DOI: 10.1080/07474938.2015.1106758 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1106758 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:5:p:401-465 Template-Type: ReDIF-Article 1.0 Author-Name: Filip Žikeš Author-X-Name-First: Filip Author-X-Name-Last: Žikeš Author-Name: Jozef Baruník Author-X-Name-First: Jozef Author-X-Name-Last: Baruník Author-Name: Nikhil Shenai Author-X-Name-First: Nikhil Author-X-Name-Last: Shenai Title: Modeling and forecasting persistent financial durations Abstract: This article introduces the Markov-Switching Multifractal Duration (MSMD) model by adapting the MSM stochastic volatility model of Calvet and Fisher (2004) to the duration setting. Although the MSMD process is exponential β-mixing as we show in the article, it is capable of generating highly persistent autocorrelation. We study, analytically and by simulation, how this feature of durations generated by the MSMD process propagates to counts and realized volatility. We employ a quasi-maximum likelihood estimator of the MSMD parameters based on the Whittle approximation and establish its strong consistency and asymptotic normality for general MSMD specifications. We show that the Whittle estimation is a computationally simple and fast alternative to maximum likelihood. Finally, we compare the performance of the MSMD model with competing short- and long-memory duration models in an out-of-sample forecasting exercise based on price durations of three major foreign exchange futures contracts. The results of the comparison show that the MSMD and the Long Memory Stochastic Duration model perform similarly and are superior to the short-memory Autoregressive Conditional Duration models. Journal: Econometric Reviews Pages: 1081-1110 Issue: 10 Volume: 36 Year: 2017 Month: 11 X-DOI: 10.1080/07474938.2014.977057 File-URL: http://hdl.handle.net/10.1080/07474938.2014.977057 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:10:p:1081-1110 Template-Type: ReDIF-Article 1.0 Author-Name: Apostolos Serletis Author-X-Name-First: Apostolos Author-X-Name-Last: Serletis Author-Name: Maksim Isakin Author-X-Name-First: Maksim Author-X-Name-Last: Isakin Title: Stochastic volatility demand systems Abstract: We address the estimation of stochastic volatility demand systems. In particular, we relax the homoscedasticity assumption and instead assume that the covariance matrix of the errors of demand systems is time-varying. Since most economic and financial time series are nonlinear, we achieve superior modeling using parametric nonlinear demand systems in which the unconditional variance is constant but the conditional variance, like the conditional mean, is also a random variable depending on current and past information. We also prove an important practical result of invariance of the maximum likelihood estimator with respect to the choice of equation eliminated from a singular demand system. An empirical application is provided, using the BEKK specification to model the conditional covariance matrix of the errors of the basic translog demand system. Journal: Econometric Reviews Pages: 1111-1122 Issue: 10 Volume: 36 Year: 2017 Month: 11 X-DOI: 10.1080/07474938.2014.977091 File-URL: http://hdl.handle.net/10.1080/07474938.2014.977091 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:10:p:1111-1122 Template-Type: ReDIF-Article 1.0 Author-Name: Yiannis Karavias Author-X-Name-First: Yiannis Author-X-Name-Last: Karavias Author-Name: Elias Tzavalis Author-X-Name-First: Elias Author-X-Name-Last: Tzavalis Title: Local power of panel unit root tests allowing for structural breaks Abstract: The asymptotic local power of least squares–based fixed-T panel unit root tests allowing for a structural break in their individual effects and/or incidental trends of the AR(1) panel data model is studied. Limiting distributions of these tests are derived under a sequence of local alternatives, and analytic expressions show how their means and variances are functions of the break date and the time dimension of the panel. The considered tests have nontrivial local power in a N−1/2 neighborhood of unity when the panel data model includes individual intercepts. For panel data models with incidental trends, the power of the tests becomes trivial in this neighborhood. However, this problem does not always appear if the tests allow for serial correlation in the error term and completely vanishes in the presence of cross-section correlation. These results show that fixed-T tests have very different theoretical properties than their large-T counterparts. Monte Carlo experiments demonstrate the usefulness of the asymptotic theory in small samples. Journal: Econometric Reviews Pages: 1123-1156 Issue: 10 Volume: 36 Year: 2017 Month: 11 X-DOI: 10.1080/07474938.2015.1059722 File-URL: http://hdl.handle.net/10.1080/07474938.2015.1059722 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:10:p:1123-1156 Template-Type: ReDIF-Article 1.0 Author-Name: Dominik Wied Author-X-Name-First: Dominik Author-X-Name-Last: Wied Title: A nonparametric test for a constant correlation matrix Abstract: We propose a nonparametric procedure to test for changes in correlation matrices at an unknown point in time. The new test requires constant expectations and variances, but only mild assumptions on the serial dependence structure, and has considerable power in finite samples. We derive the asymptotic distribution under the null hypothesis of no change as well as local power results and apply the test to stock returns. Journal: Econometric Reviews Pages: 1157-1172 Issue: 10 Volume: 36 Year: 2017 Month: 11 X-DOI: 10.1080/07474938.2014.998152 File-URL: http://hdl.handle.net/10.1080/07474938.2014.998152 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:10:p:1157-1172 Template-Type: ReDIF-Article 1.0 Author-Name: The Editors Title: List of Referees Journal: Econometric Reviews Pages: 1173-1174 Issue: 10 Volume: 36 Year: 2017 Month: 11 X-DOI: 10.1080/07474938.2017.1329616 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1329616 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:10:p:1173-1174 Template-Type: ReDIF-Article 1.0 Author-Name: The Editors Title: Editorial Board EOV Journal: Econometric Reviews Pages: ebi-ebi Issue: 10 Volume: 36 Year: 2017 Month: 11 X-DOI: 10.1080/07474938.2017.1363147 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1363147 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:36:y:2017:i:10:p:ebi-ebi Template-Type: ReDIF-Article 1.0 Author-Name: Drew Creal Author-X-Name-First: Drew Author-X-Name-Last: Creal Title: A Survey of Sequential Monte Carlo Methods for Economics and Finance Abstract: This article serves as an introduction and survey for economists to the field of sequential Monte Carlo methods which are also known as particle filters. Sequential Monte Carlo methods are simulation-based algorithms used to compute the high-dimensional and/or complex integrals that arise regularly in applied work. These methods are becoming increasingly popular in economics and finance; from dynamic stochastic general equilibrium models in macro-economics to option pricing. The objective of this article is to explain the basics of the methodology, provide references to the literature, and cover some of the theoretical results that justify the methods in practice. Journal: Econometric Reviews Pages: 245-296 Issue: 3 Volume: 31 Year: 2012 X-DOI: 10.1080/07474938.2011.607333 File-URL: http://hdl.handle.net/10.1080/07474938.2011.607333 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:31:y:2012:i:3:p:245-296 Template-Type: ReDIF-Article 1.0 Author-Name: Christian Kascha Author-X-Name-First: Christian Author-X-Name-Last: Kascha Title: A Comparison of Estimation Methods for Vector Autoregressive Moving-Average Models Abstract: Recently, there has been a renewed interest in modeling economic time series by vector autoregressive moving-average models. However, this class of models has been unpopular in practice because of estimation problems and the complexity of the identification stage. These disadvantages could have led to the dominant use of vector autoregressive models in macroeconomic research. In this article, several simple estimation methods for vector autoregressive moving-average models are compared among each other and with pure vector autoregressive modeling using ordinary least squares by means of a Monte Carlo study. Different evaluation criteria are used to judge the relative performances of the algorithms. Journal: Econometric Reviews Pages: 297-324 Issue: 3 Volume: 31 Year: 2012 X-DOI: 10.1080/07474938.2011.607343 File-URL: http://hdl.handle.net/10.1080/07474938.2011.607343 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:31:y:2012:i:3:p:297-324 Template-Type: ReDIF-Article 1.0 Author-Name: Takamitsu Kurita Author-X-Name-First: Takamitsu Author-X-Name-Last: Kurita Title: Likelihood-Based Inference for Weak Exogeneity in (2) Cointegrated VAR Models Abstract: This article develops limit theory for likelihood analysis of weak exogeneity in I(2) cointegrated vector autoregressive (VAR) models incorporating deterministic terms. Conditions for weak exogeneity in I(2) VAR models are reviewed, and the asymptotic properties of conditional maximum likelihood estimators and a likelihood-based weak exogeneity test are then investigated. It is demonstrated that weak exogeneity in I(2) VAR models allows us to conduct asymptotic conditional inference based on mixed Gaussian distributions. It is then proved that a log-likelihood ratio test statistic for weak exogeneity in I(2) VAR models is asymptotically χ2 distributed. The article also presents an empirical illustration of the proposed test for weak exogeneity using Japan's macroeconomic data. Journal: Econometric Reviews Pages: 325-360 Issue: 3 Volume: 31 Year: 2012 X-DOI: 10.1080/07474938.2011.607346 File-URL: http://hdl.handle.net/10.1080/07474938.2011.607346 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:31:y:2012:i:3:p:325-360 Template-Type: ReDIF-Article 1.0 Author-Name: Süleyman Taşpınar Author-X-Name-First: Süleyman Author-X-Name-Last: Taşpınar Author-Name: Osman Doğan Author-X-Name-First: Osman Author-X-Name-Last: Doğan Author-Name: Wim P. M. Vijverberg Author-X-Name-First: Wim P. M. Author-X-Name-Last: Vijverberg Title: GMM inference in spatial autoregressive models Abstract: In this study, we investigate the finite sample properties of the optimal generalized method of moments estimator (OGMME) for a spatial econometric model with a first-order spatial autoregressive process in the dependent variable and the disturbance term (for short SARAR(1, 1)). We show that the estimated asymptotic standard errors for spatial autoregressive parameters can be substantially smaller than their empirical counterparts. Hence, we extend the finite sample variance correction methodology of Windmeijer (2005) to the OGMME for the SARAR(1, 1) model. Results from simulation studies indicate that the correction method improves the variance estimates in small samples and leads to more accurate inference for the spatial autoregressive parameters. For the same model, we compare the finite sample properties of various test statistics for linear restrictions on autoregressive parameters. These tests include the standard asymptotic Wald test based on various GMMEs, a bootstrapped version of the Wald test, two versions of the C(α) test, the standard Lagrange multiplier (LM) test, the minimum chi-square test (MC), and two versions of the generalized method of moments (GMM) criterion test. Finally, we study the finite sample properties of effects estimators that show how changes in explanatory variables impact the dependent variable. Journal: Econometric Reviews Pages: 931-954 Issue: 9 Volume: 37 Year: 2018 Month: 10 X-DOI: 10.1080/00927872.2016.1178885 File-URL: http://hdl.handle.net/10.1080/00927872.2016.1178885 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:9:p:931-954 Template-Type: ReDIF-Article 1.0 Author-Name: Efstathios Paparoditis Author-X-Name-First: Efstathios Author-X-Name-Last: Paparoditis Author-Name: Dimitris N. Politis Author-X-Name-First: Dimitris N. Author-X-Name-Last: Politis Title: The asymptotic size and power of the augmented Dickey–Fuller test for a unit root Abstract: It is shown that the limiting distribution of the augmented Dickey–Fuller (ADF) test under the null hypothesis of a unit root is valid under a very general set of assumptions that goes far beyond the linear AR(∞) process assumption typically imposed. In essence, all that is required is that the error process driving the random walk possesses a continuous spectral density that is strictly positive. Furthermore, under the same weak assumptions, the limiting distribution of the ADF test is derived under the alternative of stationarity, and a theoretical explanation is given for the well-known empirical fact that the test's power is a decreasing function of the chosen autoregressive order p. The intuitive reason for the reduced power of the ADF test is that, as p tends to infinity, the p regressors become asymptotically collinear. Journal: Econometric Reviews Pages: 955-973 Issue: 9 Volume: 37 Year: 2018 Month: 10 X-DOI: 10.1080/00927872.2016.1178887 File-URL: http://hdl.handle.net/10.1080/00927872.2016.1178887 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:9:p:955-973 Template-Type: ReDIF-Article 1.0 Author-Name: Yohei Yamamoto Author-X-Name-First: Yohei Author-X-Name-Last: Yamamoto Title: A modified confidence set for the structural break date in linear regression models Abstract: Elliott and Müller (EM) (2007) provide a method for constructing a confidence set for the structural break date by inverting a variant of the locally best test statistic. Previous studies have shown that the EM method produces a set with an accurate coverage ratio even for a small break; however, the set is often overly lengthy. This study proposes a simple modification to rehabilitate their method through the long-run variance estimation. Following the literature, we provide an asymptotic justification for the improvement of the modified method over the original method under a nonlocal asymptotic framework. A Monte Carlo simulation shows that the modified method achieves a shorter confidence set than the EM method, especially when the break is large or the HAC correction is conducted. The modified method may exhibit minor errors in the coverage rate when the break is small; however, the coverage is more stable than alternative methods when the break is large. We apply our method to a level shift in post-1980s Japanese inflation data. Journal: Econometric Reviews Pages: 974-999 Issue: 9 Volume: 37 Year: 2018 Month: 10 X-DOI: 10.1080/00927872.2016.1178892 File-URL: http://hdl.handle.net/10.1080/00927872.2016.1178892 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:9:p:974-999 Template-Type: ReDIF-Article 1.0 Author-Name: Alain Guay Author-X-Name-First: Alain Author-X-Name-Last: Guay Author-Name: Jean-François Lamarche Author-X-Name-First: Jean-François Author-X-Name-Last: Lamarche Title: Structural change tests for GEL criteria Abstract: This article examines structural change tests based on generalized empirical likelihood methods in the time series context, allowing for dependent data. Standard structural change tests for the Generalized method of moments (GMM) are adapted to the generalized empirical likelihood (GEL) context. We show that when moment conditions are properly smoothed, these test statistics converge to the same asymptotic distribution as in the GMM, in cases with known and unknown breakpoints. New test statistics specific to GEL methods, and that are robust to weak identification, are also introduced. A simulation study examines the small sample properties of the tests and reveals that GEL-based robust tests performed well, both in terms of the presence and location of a structural change and in terms of the nature of identification. Journal: Econometric Reviews Pages: 1000-1032 Issue: 9 Volume: 37 Year: 2018 Month: 10 X-DOI: 10.1080/00927872.2016.1178893 File-URL: http://hdl.handle.net/10.1080/00927872.2016.1178893 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:37:y:2018:i:9:p:1000-1032 Template-Type: ReDIF-Article 1.0 Author-Name: Sven Schreiber Author-X-Name-First: Sven Author-X-Name-Last: Schreiber Title: The estimation uncertainty of permanent-transitory decompositions in co-integrated systems Abstract: The topic of this article is the estimation uncertainty of the Stock–Watson and Gonzalo–Granger permanent-transitory decompositions in the framework of the co-integrated vector autoregression. We suggest an approach to construct the confidence interval of the transitory component estimate in a given period (e.g., the latest observation) by conditioning on the observed data in that period. To calculate asymptotically valid confidence intervals, we use the delta method and two bootstrap variants. As an illustration, we analyze the uncertainty of (U.S.) output gap estimates in a system of output, consumption, and investment. Journal: Econometric Reviews Pages: 279-300 Issue: 3 Volume: 38 Year: 2019 Month: 3 X-DOI: 10.1080/07474938.2016.1235257 File-URL: http://hdl.handle.net/10.1080/07474938.2016.1235257 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:3:p:279-300 Template-Type: ReDIF-Article 1.0 Author-Name: Andrés Ramírez Hassan Author-X-Name-First: Andrés Author-X-Name-Last: Ramírez Hassan Author-Name: Santiago Montoya Blandón Author-X-Name-First: Santiago Author-X-Name-Last: Montoya Blandón Title: Welfare gains of the poor: An endogenous Bayesian approach with spatial random effects Abstract: We introduce a Bayesian instrumental variable procedure with spatial random effects that handles endogeneity, and spatial dependence with unobserved heterogeneity. We find through a limited Monte Carlo experiment that our proposal works well in terms of point estimates and prediction. We apply our method to analyze the welfare effects generated by a process of electricity tariff unification on the poorest households. In particular, we deduce an Equivalent Variation measure where there is a budget constraint for a two-tiered pricing scheme, and find that 10% of the poorest municipalities attained welfare gains above 2% of their initial income. Journal: Econometric Reviews Pages: 301-318 Issue: 3 Volume: 38 Year: 2019 Month: 3 X-DOI: 10.1080/07474938.2016.1261062 File-URL: http://hdl.handle.net/10.1080/07474938.2016.1261062 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:3:p:301-318 Template-Type: ReDIF-Article 1.0 Author-Name: Gabi Gayer Author-X-Name-First: Gabi Author-X-Name-Last: Gayer Author-Name: Offer Lieberman Author-X-Name-First: Offer Author-X-Name-Last: Lieberman Author-Name: Omer Yaffe Author-X-Name-First: Omer Author-X-Name-Last: Yaffe Title: Similarity-based model for ordered categorical data Abstract: In a large variety of applications, the data for a variable we wish to explain are ordered and categorical. In this paper, we present a new similarity-based model for the scenario and investigate its properties. We establish that the process is ψ-mixing and strictly stationary and derive the explicit form of the autocorrelation function in some special cases. Consistency and asymptotic normality of the maximum likelihood estimator of the model’s parameters are proven. A simulation study supports our findings. The results are applied to the Netflix data set, comprised of a survey on users’ grading of movies. Journal: Econometric Reviews Pages: 263-278 Issue: 3 Volume: 38 Year: 2019 Month: 3 X-DOI: 10.1080/07474938.2017.1308054 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1308054 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:3:p:263-278 Template-Type: ReDIF-Article 1.0 Author-Name: Heino Bohn Nielsen Author-X-Name-First: Heino Bohn Author-X-Name-Last: Nielsen Title: Estimation bias and bias correction in reduced rank autoregressions Abstract: This paper characterizes the finite-sample bias of the maximum likelihood estimator (MLE) in a reduced rank vector autoregression and suggests two simulation-based bias corrections. One is a simple bootstrap implementation that approximates the bias at the MLE. The other is an iterative root-finding algorithm implemented using stochastic approximation methods. Both algorithms are shown to be improvements over the MLE, measured in terms of mean square error and mean absolute deviation. An illustration to US macroeconomic time series is given. Journal: Econometric Reviews Pages: 332-349 Issue: 3 Volume: 38 Year: 2019 Month: 3 X-DOI: 10.1080/07474938.2017.1308065 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1308065 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:3:p:332-349 Template-Type: ReDIF-Article 1.0 Author-Name: José Ignacio Cuesta Author-X-Name-First: José Ignacio Author-X-Name-Last: Cuesta Author-Name: Jonathan M. V. Davis Author-X-Name-First: Jonathan M. V. Author-X-Name-Last: Davis Author-Name: Andrew Gianou Author-X-Name-First: Andrew Author-X-Name-Last: Gianou Author-Name: Alejandro Hoyos Author-X-Name-First: Alejandro Author-X-Name-Last: Hoyos Title: Identification of average marginal effects under misspecification when covariates are normal Abstract: A previously known result in the econometrics literature is that when covariates of an underlying data generating process are jointly normally distributed, estimates from a nonlinear model that is misspecified as linear can be interpreted as average marginal effects. This has been shown for models with exogenous covariates and separability between covariates and errors. In this paper, we extend this identification result to a variety of more general cases, in particular for combinations of separable and nonseparable models under both exogeneity and endogeneity. So long as the underlying model belongs to one of these large classes of data generating processes, our results show that nothing else must be known about the true DGP—beyond normality of observable data, a testable assumption—in order for linear estimators to be interpretable as average marginal effects. We use simulation to explore the performance of these estimators using a misspecified linear model and show they perform well when the data are normal but can perform poorly when this is not the case. Journal: Econometric Reviews Pages: 350-357 Issue: 3 Volume: 38 Year: 2019 Month: 3 X-DOI: 10.1080/07474938.2017.1308091 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1308091 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:3:p:350-357 Template-Type: ReDIF-Article 1.0 Author-Name: Dong Li Author-X-Name-First: Dong Author-X-Name-Last: Li Author-Name: Shaojun Guo Author-X-Name-First: Shaojun Author-X-Name-Last: Guo Author-Name: Ke Zhu Author-X-Name-First: Ke Author-X-Name-Last: Zhu Title: Double AR model without intercept: An alternative to modeling nonstationarity and heteroscedasticity Abstract: This paper presents a double AR model without intercept (DARWIN model) and provides us a new way to study the nonstationary heteroscedastic time series. It is shown that the DARWIN model is always nonstationary and heteroscedastic, and its sample properties depend on the Lyapunov exponent. An easy-to-implement estimator is proposed for the Lyapunov exponent, and it is unbiased, strongly consistent, and asymptotically normal. Based on this estimator, a powerful test is constructed for testing the ordinary oscillation of the model. Moreover, this paper proposes the quasi-maximum likelihood estimator (QMLE) for the DARWIN model, which has an explicit form. The strong consistency and asymptotic normality of the QMLE are established regardless of the sign of the Lyapunov exponent. Simulation studies are conducted to assess the performance of the estimation and testing, and an empirical example is given for illustrating the usefulness of the DARWIN model. Journal: Econometric Reviews Pages: 319-331 Issue: 3 Volume: 38 Year: 2019 Month: 3 X-DOI: 10.1080/07474938.2017.1310080 File-URL: http://hdl.handle.net/10.1080/07474938.2017.1310080 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:38:y:2019:i:3:p:319-331 Template-Type: ReDIF-Article 1.0 Author-Name: Stefanos Dimitrakopoulos Author-X-Name-First: Stefanos Author-X-Name-Last: Dimitrakopoulos Author-Name: Michalis Kolossiatis Author-X-Name-First: Michalis Author-X-Name-Last: Kolossiatis Title: Bayesian analysis of moving average stochastic volatility models: modeling in-mean effects and leverage for financial time series Abstract: We propose a moving average stochastic volatility in mean model and a moving average stochastic volatility model with leverage. For parameter estimation, we develop efficient Markov chain Monte Carlo algorithms and illustrate our methods, using simulated and real data sets. We compare the proposed specifications against several competing stochastic volatility models, using marginal likelihoods and the observed-data Deviance information criterion. We also perform a forecasting exercise, using predictive likelihoods, the root mean square forecast error and Kullback-Leibler divergence. We find that the moving average stochastic volatility model with leverage better fits the four empirical data sets used. Journal: Econometric Reviews Pages: 319-343 Issue: 4 Volume: 39 Year: 2020 Month: 4 X-DOI: 10.1080/07474938.2019.1630075 File-URL: http://hdl.handle.net/10.1080/07474938.2019.1630075 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:4:p:319-343 Template-Type: ReDIF-Article 1.0 Author-Name: Gholamreza Hajargasht Author-X-Name-First: Gholamreza Author-X-Name-Last: Hajargasht Author-Name: William E. Griffiths Author-X-Name-First: William E. Author-X-Name-Last: Griffiths Title: Minimum distance estimation of parametric Lorenz curves based on grouped data Abstract: The Lorenz curve, introduced more than 100 years ago, remains as one of the main tools for analysis of inequality. International institutions such as the World Bank collect and publish grouped income data in the form of population and income shares for a large number of countries. These data are often used for estimation of parametric Lorenz curves which in turn form the basis for most inequality analyses. Despite the prevalence of parametric estimation of Lorenz curves from grouped data, and the existence of well-developed nonparametric methods, a formal description of rigorous methodology for estimating parametric Lorenz curves from grouped data is lacking. We fill this gap. Building on two data generating mechanisms, efficient methods of estimation and inference are described; several results useful for comparing the two methods of inference, and aiding computation, are derived. Simulations are used to assess the estimators, and curves are estimated for some example countries. We also show how the proposed methods improve upon World Bank methods and make recommendations for improving current practices. Journal: Econometric Reviews Pages: 344-361 Issue: 4 Volume: 39 Year: 2020 Month: 4 X-DOI: 10.1080/07474938.2019.1630077 File-URL: http://hdl.handle.net/10.1080/07474938.2019.1630077 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:4:p:344-361 Template-Type: ReDIF-Article 1.0 Author-Name: Lorenzo Camponovo Author-X-Name-First: Lorenzo Author-X-Name-Last: Camponovo Title: Bootstrap inference for penalized GMM estimators with oracle properties Abstract: We study the validity of bootstrap methods in approximating the sampling distribution of penalized GMM estimators with oracle properties. More precisely, we focus on bridge estimators with Lq penalty for 0<q<1, and adaptive lasso estimators. We show that the nonparametric bootstrap with recentered moment conditions provides a valid method for approximating the distribution of these estimators. Furthermore, using the bootstrap approach, we also propose a data-driven method for the selection of tuning parameters in the penalization terms. Monte Carlo simulations confirm the reliability and accuracy of the bootstrap procedure. The empirical coverages for the active variables implied by the nonparametric bootstrap are always very close to the nominal coverage probabilities. Journal: Econometric Reviews Pages: 362-372 Issue: 4 Volume: 39 Year: 2020 Month: 4 X-DOI: 10.1080/07474938.2019.1630076 File-URL: http://hdl.handle.net/10.1080/07474938.2019.1630076 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:4:p:362-372 Template-Type: ReDIF-Article 1.0 Author-Name: Ryan Greenaway-McGrevy Author-X-Name-First: Ryan Author-X-Name-Last: Greenaway-McGrevy Title: Multistep forecast selection for panel data Abstract: We develop a new set of model selection methods for direct multistep forecasting of panel data vector autoregressive processes. Model selection is based on minimizing the estimated multistep quadratic forecast risk among candidate models. To attenuate the small sample bias of the least squares estimator, models are fitted using bias-corrected least squares. We provide conditions sufficient for the new selection criteria to be asymptotically efficient as n (cross sections) and T (time series) approach infinity. The new criteria outperform alternative selection methods in an empirical application to forecasting metropolitan statistical area population growth in the US. Journal: Econometric Reviews Pages: 373-406 Issue: 4 Volume: 39 Year: 2020 Month: 4 X-DOI: 10.1080/07474938.2019.1651490 File-URL: http://hdl.handle.net/10.1080/07474938.2019.1651490 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:4:p:373-406 Template-Type: ReDIF-Article 1.0 Author-Name: Igor L. Kheifets Author-X-Name-First: Igor L. Author-X-Name-Last: Kheifets Author-Name: Pentti J. Saikkonen Author-X-Name-First: Pentti J. Author-X-Name-Last: Saikkonen Title: Stationarity and ergodicity of vector STAR models Abstract: Smooth transition autoregressive models are widely used to capture nonlinearities in univariate and multivariate time series. Existence of stationary solution is typically assumed, implicitly or explicitly. In this paper, we describe conditions for stationarity and ergodicity of vector STAR models. The key condition is that the joint spectral radius of certain matrices is below 1. It is not sufficient to assume that separate spectral radii are below 1. Our result allows to use recently introduced toolboxes from computational mathematics to verify the stationarity and ergodicity of vector STAR models. Journal: Econometric Reviews Pages: 407-414 Issue: 4 Volume: 39 Year: 2020 Month: 4 X-DOI: 10.1080/07474938.2019.1651489 File-URL: http://hdl.handle.net/10.1080/07474938.2019.1651489 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:4:p:407-414 Template-Type: ReDIF-Article 1.0 Author-Name: Jiti Gao Author-X-Name-First: Jiti Author-X-Name-Last: Gao Author-Name: Namhyun Kim Author-X-Name-First: Namhyun Author-X-Name-Last: Kim Author-Name: Patrick W. Saart Author-X-Name-First: Patrick W. Author-X-Name-Last: Saart Title: On endogeneity and shape invariance in extended partially linear single index models Abstract: In this article, the usefulness of the extended generalized partially linear single-index (EGPLSI) model introduced by Xia et al. in its ability to model a flexible shape-invariant specification is elaborated. More importantly, a control function approach is proposed to address the potential endogeneity problems in the EGPLSI model to enhance its applicability to empirical studies. In the process, it is shown that the attractive asymptotic features of the single-index type of a semiparametric model are still valid given intrinsic generated covariates. Our newly developed method is then applied to address the endogeneity of expenditure in the semiparametric analysis of a system of empirical Engel curves by using the British data, highlights the convenient applicability of our proposed method. Journal: Econometric Reviews Pages: 415-435 Issue: 4 Volume: 39 Year: 2020 Month: 4 X-DOI: 10.1080/07474938.2019.1682313 File-URL: http://hdl.handle.net/10.1080/07474938.2019.1682313 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:4:p:415-435 Template-Type: ReDIF-Article 1.0 Author-Name: Anna Gloria Billé Author-X-Name-First: Anna Gloria Author-X-Name-Last: Billé Author-Name: Samantha Leorato Author-X-Name-First: Samantha Author-X-Name-Last: Leorato Title: Partial ML estimation for spatial autoregressive nonlinear probit models with autoregressive disturbances Abstract: In this paper, we propose a Partial MLE (PMLE) for a general spatial nonlinear probit model, i.e., SARAR(1,1) probit, defined through a SARAR(1,1) latent linear model. This model encompasses both the SAE(1) probit and the more interesting SAR(1) probit models, already considered in the literature. We provide a complete asymptotic analysis of our PMLE as well as appropriate definitions of the marginal effects. Moreover, we address the issue of the choice of the groups (couples, in our case) by proposing an algorithm based on a minimum KL divergence problem. Finite sample properties of the PMLE are studied through extensive Monte Carlo simulations. In particular, we consider both sparse and dense matrices for the true spatial model specifications, and cases of model misspecification given wrong assumed weighting matrices. In a real data example, we finally also compare our estimator with different MLE–based estimators and with the Bayesian approach. Journal: Econometric Reviews Pages: 437-475 Issue: 5 Volume: 39 Year: 2020 Month: 5 X-DOI: 10.1080/07474938.2019.1682314 File-URL: http://hdl.handle.net/10.1080/07474938.2019.1682314 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:5:p:437-475 Template-Type: ReDIF-Article 1.0 Author-Name: Manuel A. Domínguez Author-X-Name-First: Manuel A. Author-X-Name-Last: Domínguez Author-Name: Ignacio N. Lobato Author-X-Name-First: Ignacio N. Author-X-Name-Last: Lobato Title: Specification testing with estimated variables Abstract: This article proposes specification tests for economic models defined through conditional moments restrictions in which conditioning variables are estimated. There are two main motivations for this situation. First, the case when the conditioning variables are not directly observable, such as economic models, where innovations or latent variables appear as explanatory variables. Second, the case when the set of conditioning variables is too large to derive powerful tests, and hence, the original conditioning set is replaced by a constructed variable that is regarded as a good summary of it. We establish the asymptotic properties of the proposed tests, examine its finite sample behavior, and apply them to different econometric contexts. In some cases, the proposed approach leads to relevant tests that generalize well known specification tests, such as Ramsey’s RESET test. Journal: Econometric Reviews Pages: 476-494 Issue: 5 Volume: 39 Year: 2020 Month: 5 X-DOI: 10.1080/07474938.2019.1687116 File-URL: http://hdl.handle.net/10.1080/07474938.2019.1687116 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:5:p:476-494 Template-Type: ReDIF-Article 1.0 Author-Name: Xuexin Wang Author-X-Name-First: Xuexin Author-X-Name-Last: Wang Title: A new class of tests for overidentifying restrictions in moment condition models Abstract: In this study, we propose a new class of tests for overidentifying restrictions in moment condition models, extending Neyman’s (1959) C(α) test for parameter hypotheses in maximum likelihood to generalized empirical likelihood (GEL). These tests lack the complicated saddle point problem seen in GEL estimation; only a n consistent estimator, where n is the sample size, is needed. In addition to discussing their first-order properties, we establish that under some regularity conditions, these tests share the same higher-order properties as GEL overidentifying tests, given proper consistent estimators. A Monte Carlo simulation study shows that the new class of tests of overidentifying restrictions has better finite sample performance than the two-step GMM overidentification test, and compares well to several potential alternatives in terms of overall performance. Journal: Econometric Reviews Pages: 495-509 Issue: 5 Volume: 39 Year: 2020 Month: 5 X-DOI: 10.1080/07474938.2019.1697085 File-URL: http://hdl.handle.net/10.1080/07474938.2019.1697085 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:5:p:495-509 Template-Type: ReDIF-Article 1.0 Author-Name: Eiji Kurozumi Author-X-Name-First: Eiji Author-X-Name-Last: Kurozumi Title: Asymptotic properties of bubble monitoring tests Abstract: We investigate bubble monitoring tests by extending the existing sup-ADF and generalized sup-ADF tests to the monitoring scheme. We also consider applying the CUSUM detector as proposed in the literature. We derive the limiting distributions of the detecting statistics under the null hypothesis, the moderate deviation alternative, and the local alternative. We find that although the moderate deviation alternative shows the difference in the divergence rates of the ADF- and CUSUM-type detectors, the local asymptotic theory is more useful for understanding their differences in detail. We also conduct finite sample simulations and confirm that the local asymptotic theory approximates the finite sample properties of the tests very well. Journal: Econometric Reviews Pages: 510-538 Issue: 5 Volume: 39 Year: 2020 Month: 5 X-DOI: 10.1080/07474938.2019.1697086 File-URL: http://hdl.handle.net/10.1080/07474938.2019.1697086 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:5:p:510-538 Template-Type: ReDIF-Article 1.0 Author-Name: Esfandiar Maasoumi Author-X-Name-First: Esfandiar Author-X-Name-Last: Maasoumi Title: Best Paper Award Journal: Econometric Reviews Pages: 539-539 Issue: 5 Volume: 39 Year: 2020 Month: 5 X-DOI: 10.1080/07474938.2020.1738623 File-URL: http://hdl.handle.net/10.1080/07474938.2020.1738623 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:5:p:539-539 Template-Type: ReDIF-Article 1.0 Author-Name: Jeremiah Richey Author-X-Name-First: Jeremiah Author-X-Name-Last: Richey Author-Name: Alicia Rosburg Author-X-Name-First: Alicia Author-X-Name-Last: Rosburg Title: Decomposing joint distributions via reweighting functions: an application to intergenerational economic mobility Abstract: We introduce a method that extends the traditional Oaxaca-Blinder decomposition to both the full distribution of an outcome of interest and to settings where group membership varies along a continuum. We achieve this by working directly with the joint distribution of outcome and group membership and comparing it to an independent joint distribution. Like all decompositions, we assume the difference is partially due to differences in characteristics between groups (a composition effect) and partially due to differences in returns to characteristics between groups (a structure effect). We use reweighting functions to estimate a counterfactual joint distribution representing the hypothetical if characteristics did not vary according to group while returns to characteristics did. The counterfactual allows us to decompose differences between the empirical and independent distributions into composition and structure effects. We demonstrate the method by decomposing multiple measures of immobility for white men in the U.S. Journal: Econometric Reviews Pages: 541-558 Issue: 6 Volume: 39 Year: 2020 Month: 7 X-DOI: 10.1080/07474938.2019.1697088 File-URL: http://hdl.handle.net/10.1080/07474938.2019.1697088 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:6:p:541-558 Template-Type: ReDIF-Article 1.0 Author-Name: Francisco Blasques Author-X-Name-First: Francisco Author-X-Name-Last: Blasques Author-Name: Siem Jan Koopman Author-X-Name-First: Siem Jan Author-X-Name-Last: Koopman Author-Name: André Lucas Author-X-Name-First: André Author-X-Name-Last: Lucas Title: Nonlinear autoregressive models with optimality properties Abstract: We introduce a new class of nonlinear autoregressive models from their representation as linear autoregressive models with time-varying coefficients. The parameter updating scheme is subsequently based on the score of the predictive likelihood function at each point in time. We study in detail the information theoretic optimality properties of this updating scheme and establish the asymptotic theory for the maximum likelihood estimator of the static parameters of the model. We compare the dynamic properties of the new model with those of well-known nonlinear dynamic models such as the threshold and smooth transition autoregressive models. Finally, we study the model’s performance in a Monte Carlo study and in an empirical out-of-sample forecasting analysis for U.S. macroeconomic time series. Journal: Econometric Reviews Pages: 559-578 Issue: 6 Volume: 39 Year: 2020 Month: 7 X-DOI: 10.1080/07474938.2019.1701807 File-URL: http://hdl.handle.net/10.1080/07474938.2019.1701807 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:6:p:559-578 Template-Type: ReDIF-Article 1.0 Author-Name: Yannick Hoga Author-X-Name-First: Yannick Author-X-Name-Last: Hoga Title: Where does the tail begin? An approach based on scoring rules Abstract: Learning about the tail shape of time series is important in, e.g., economics, finance, and risk management. However, it is well known that estimates of the tail index can be very sensitive to the choice of the number k of tail observations used for estimation. We propose a procedure that determines where the tail begins by choosing k in a data-driven fashion using scoring rules. So far, scoring rules have mainly been used to compare density forecasts. We also demonstrate how our proposal can be used in multivariate applications in the system risk literature. The advantages of our choice of k are illustrated in simulations and an empirical application to Value-at-Risk forecasts for five U.S. blue-chip stocks. Journal: Econometric Reviews Pages: 579-601 Issue: 6 Volume: 39 Year: 2020 Month: 7 X-DOI: 10.1080/07474938.2019.1697087 File-URL: http://hdl.handle.net/10.1080/07474938.2019.1697087 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:6:p:579-601 Template-Type: ReDIF-Article 1.0 Author-Name: Jon Michel Author-X-Name-First: Jon Author-X-Name-Last: Michel Title: Optimal adaptive sampling for a symmetric two-state continuous time Markov chain Abstract: We consider the optimal sampling times for a symmetric two-state continuous time Markov chain. We first consider sampling times of the form ti=iτ and find the optimal τ to minimize the asymptotic variance of our estimated parameter. This optimal τ depends upon the true unknown parameters and so it is infeasible in practice. To address this, we consider propose an adaptive scheme which we requires no knowledge of the true underlying parameter, we show that this method is asymptotically equivalent to the optimal fixed time design. Journal: Econometric Reviews Pages: 602-611 Issue: 6 Volume: 39 Year: 2020 Month: 7 X-DOI: 10.1080/07474938.2019.1701808 File-URL: http://hdl.handle.net/10.1080/07474938.2019.1701808 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:6:p:602-611 Template-Type: ReDIF-Article 1.0 Author-Name: Prosper Dovonon Author-X-Name-First: Prosper Author-X-Name-Last: Dovonon Author-Name: Yves F. Atchadé Author-X-Name-First: Yves F. Author-X-Name-Last: Atchadé Title: Efficiency bounds for semiparametric models with singular score functions Abstract: This paper is concerned with asymptotic efficiency bounds for the estimation of the finite dimension parameter θ∈Rp of semiparametric models that have singular score function for θ at the true value θ⋆. The resulting singularity of the matrix of Fisher information means that the standard bound for θ−θ⋆ is not defined. We study the case of single rank deficiency of the score and focus on the case where the derivative of the root density in the direction of the last parameter component, θ2, is nil while the derivatives in the p – 1 other directions, θ1, are linearly independent. We then distinguish two cases: (i) The second derivative of the root density in the direction of θ2 and the first derivative in the direction of θ1 are linearly independent and (ii) The second derivative of the root density in the direction of θ2 is also nil but the third derivative in θ2 is linearly independent of the first derivative in the direction of θ1. We show that in both cases, efficiency bounds can be obtained for the estimation of κj(θ)=(θ1−θ⋆1,(θ2−θ⋆2)j), with j = 2 and 3, respectively and argue that an estimator θ̂ is efficient if κj(θ̂) reaches its bound. We provide the bounds in form of convolution and asymptotic minimax theorems. For case (i), we propose a transformation of the Gaussian variable that appears in our convolution theorem to account for the restricted set of values of κ2(θ). This transformation effectively gives the efficiency bound for the estimation of κ2(θ) in the model configuration (i). We apply these results to locally under-identified moment condition models and show that the generalized method of moments (GMM) estimator using V⋆−1 as weighting matrix, where V⋆ is the variance of the estimating function, is optimal even in these non standard settings. Examples of models are provided that fit the two configurations explored. Journal: Econometric Reviews Pages: 612-648 Issue: 6 Volume: 39 Year: 2020 Month: 7 X-DOI: 10.1080/07474938.2019.1701809 File-URL: http://hdl.handle.net/10.1080/07474938.2019.1701809 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:6:p:612-648 Template-Type: ReDIF-Article 1.0 Author-Name: Esfandiar Maasoumi Author-X-Name-First: Esfandiar Author-X-Name-Last: Maasoumi Author-Name: Zhijie Xiao Author-X-Name-First: Zhijie Author-X-Name-Last: Xiao Title: Econometric Reviews Honors Peter Charles Bonest Phillips, the Master Econometrician Journal: Econometric Reviews Pages: 649-654 Issue: 7 Volume: 39 Year: 2020 Month: 8 X-DOI: 10.1080/07474938.2020.1772566 File-URL: http://hdl.handle.net/10.1080/07474938.2020.1772566 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:7:p:649-654 Template-Type: ReDIF-Article 1.0 Author-Name: Dag Tjøstheim Author-X-Name-First: Dag Author-X-Name-Last: Tjøstheim Title: Some notes on nonlinear cointegration: A partial review with some novel perspectives Abstract: Some recent work on the analysis of nonlinear and nonstationary time series models is reviewed. A couple of novel results are obtained in extending nonlinear cointegrating regression models to a time series situation. All through the paper focus is on aspects that could lead to a more well-defined concept of nonlinear cointegration. Journal: Econometric Reviews Pages: 655-673 Issue: 7 Volume: 39 Year: 2020 Month: 8 X-DOI: 10.1080/07474938.2020.1771900 File-URL: http://hdl.handle.net/10.1080/07474938.2020.1771900 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:7:p:655-673 Template-Type: ReDIF-Article 1.0 Author-Name: Ba M. Chu Author-X-Name-First: Ba M. Author-X-Name-Last: Chu Author-Name: David T. Jacho-Chávez Author-X-Name-First: David T. Author-X-Name-Last: Jacho-Chávez Author-Name: Oliver B. Linton Author-X-Name-First: Oliver B. Author-X-Name-Last: Linton Title: Standard Errors for Nonparametric Regression Abstract: This paper proposes five pointwise consistent and asymptotic normal estimators of the asymptotic variance function of the Nadaraya-Watson kernel estimator for nonparametric regression. The proposed estimators are constructed based on the first-stage nonparametric residuals, and their asymptotic properties are established under the assumption that the same bandwidth sequences are used throughout, which mimics what researchers do in practice while making derivations more complicated instead. A limited Monte Carlo experiment demonstrates that the proposed estimators possess smaller pointwise variability in small samples than the pair and wild bootstrap estimators which are commonly used in practice. Journal: Econometric Reviews Pages: 674-690 Issue: 7 Volume: 39 Year: 2020 Month: 8 X-DOI: 10.1080/07474938.2020.1772563 File-URL: http://hdl.handle.net/10.1080/07474938.2020.1772563 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:7:p:674-690 Template-Type: ReDIF-Article 1.0 Author-Name: Hyojin Han Author-X-Name-First: Hyojin Author-X-Name-Last: Han Author-Name: Eric Renault Author-X-Name-First: Eric Author-X-Name-Last: Renault Title: Identification strength with a large number of moments Abstract: This paper studies how identification is affected in GMM estimation as the number of moment conditions increases. We develop a general asymptotic theory extending the set up of Chao and Swanson and Antoine and Renault to the case where moment conditions have heterogeneous identification strengths and the number of them may diverge to infinity with the sample size. We also allow the models to be locally misspecified and examine how the asymptotic theory is affected by the degree of misspecification. The theory encompasses many cases including GMM models with many moments (Han and Phillips), partially linear models, and local GMM via kernel smoothing with a large number of conditional moment restrictions. We provide an understanding of the benefits of a large number of moments that compensate the weakness of individual moments by explicitly showing how an increasing number of moments improves the rate of convergence in GMM. Journal: Econometric Reviews Pages: 691-714 Issue: 7 Volume: 39 Year: 2020 Month: 8 X-DOI: 10.1080/07474938.2020.1771903 File-URL: http://hdl.handle.net/10.1080/07474938.2020.1771903 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:7:p:691-714 Template-Type: ReDIF-Article 1.0 Author-Name: Chuanliang Jiang Author-X-Name-First: Chuanliang Author-X-Name-Last: Jiang Author-Name: Esfandiar Maasoumi Author-X-Name-First: Esfandiar Author-X-Name-Last: Maasoumi Author-Name: Zhijie Xiao Author-X-Name-First: Zhijie Author-X-Name-Last: Xiao Title: Quantile aggregation and combination for stock return prediction Abstract: Model averaging for forecasting and mixed estimation is a recognized improved statistical approach. This paper is a first report on: (1). aggregate information from different conditional quantiles within a given model and, (2). model averaging with quantile averaging. Based on a subset of possible methods, we show that aggregating information over different quantiles, with and without combining information across different models, can produce superior forecasts, outperforming forecasts based on conditional mean regressions. We observe a variety of quantile aggregation schemes within a model can significantly improve over forecasts obtained from model combination alone. We provide simulation and empirical evidence. In addition economic value of our proposals is demonstrated within an optimal portfolio decision setting. Higher values of average utility are observed with no exception when an investor employs forecasts which aggregate both within and across model information. Journal: Econometric Reviews Pages: 715-743 Issue: 7 Volume: 39 Year: 2020 Month: 8 X-DOI: 10.1080/07474938.2020.1771902 File-URL: http://hdl.handle.net/10.1080/07474938.2020.1771902 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:7:p:715-743 Template-Type: ReDIF-Article 1.0 Author-Name: Badi H. Baltagi Author-X-Name-First: Badi H. Author-X-Name-Last: Baltagi Author-Name: Chihwa Kao Author-X-Name-First: Chihwa Author-X-Name-Last: Kao Author-Name: Long Liu Author-X-Name-First: Long Author-X-Name-Last: Liu Title: Testing for shifts in a time trend panel data model with serially correlated error component disturbances Abstract: This paper studies testing of shifts in a time trend panel data model with serially correlated error component disturbances, without any prior knowledge of whether the error term is stationary or nonstationary. This is done in case the shift is known as well as unknown. Following the time series literature, we propose a Wald type test statistic that uses a fixed effects feasible generalized least squares (FE-FGLS) estimator. The proposed test has a chi-square limiting distribution and is valid for both I(0) and I(1) errors. The finite sample size and power of this Wald test is investigated using Monte Carlo simulations Journal: Econometric Reviews Pages: 745-762 Issue: 8 Volume: 39 Year: 2020 Month: 9 X-DOI: 10.1080/07474938.2020.1772567 File-URL: http://hdl.handle.net/10.1080/07474938.2020.1772567 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:8:p:745-762 Template-Type: ReDIF-Article 1.0 Author-Name: Elise Coudin Author-X-Name-First: Elise Author-X-Name-Last: Coudin Author-Name: Jean-Marie Dufour Author-X-Name-First: Jean-Marie Author-X-Name-Last: Dufour Title: Finite-sample generalized confidence distributions and sign-based robust estimators in median regressions with heterogeneous dependent errors Abstract: We study the problem of estimating the parameters of a linear median regression without any assumption on the shape of the error distribution – including no condition on the existence of moments – allowing for heterogeneity (or heteroskedasticity) of unknown form, noncontinuous distributions, and very general serial dependence (linear and nonlinear). This is done through a reverse inference approach, based on a distribution-free sign-based testing theory, from which confidence sets and point estimators are subsequently generated. We propose point estimators, which have a natural association with confidence distributions. These estimators are based on maximizing test p-values and inherit robustness properties from the generating distribution-free tests. Both finite-sample and large-sample properties of the proposed estimators are established under weak regularity conditions. We show that they are median-unbiased (under symmetry and estimator unicity) and possess equivariance properties. Consistency and asymptotic normality are established without any moment existence assumption on the errors. A Monte Carlo study of bias and RMSE shows sign-based estimators perform better than LAD-type estimators in various heteroskedastic settings. We illustrate the use of sign-based estimators on an example of β-convergence of output levels across U.S. states. Journal: Econometric Reviews Pages: 763-791 Issue: 8 Volume: 39 Year: 2020 Month: 9 X-DOI: 10.1080/07474938.2020.1772568 File-URL: http://hdl.handle.net/10.1080/07474938.2020.1772568 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:8:p:763-791 Template-Type: ReDIF-Article 1.0 Author-Name: Shujie Ma Author-X-Name-First: Shujie Author-X-Name-Last: Ma Author-Name: Jeffrey S. Racine Author-X-Name-First: Jeffrey S. Author-X-Name-Last: Racine Author-Name: Aman Ullah Author-X-Name-First: Aman Author-X-Name-Last: Ullah Title: Nonparametric estimation of marginal effects in regression-spline random effects models Abstract: We consider a B-spline regression approach toward nonparametric modeling of a random effects (error component) model. We focus our attention on the estimation of marginal effects (derivatives) and their asymptotic properties. Theoretical underpinnings are provided, finite-sample performance is evaluated via Monte–Carlo simulation, and an application that examines the contribution of different types of public infrastructure on private production is investigated using panel data comprising the 48 contiguous states in the United States over the period 1970–1986. Journal: Econometric Reviews Pages: 792-825 Issue: 8 Volume: 39 Year: 2020 Month: 9 X-DOI: 10.1080/07474938.2020.1772569 File-URL: http://hdl.handle.net/10.1080/07474938.2020.1772569 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:8:p:792-825 Template-Type: ReDIF-Article 1.0 Author-Name: Yi-Ting Chen Author-X-Name-First: Yi-Ting Author-X-Name-Last: Chen Author-Name: Ruey S. Tsay Author-X-Name-First: Ruey S. Author-X-Name-Last: Tsay Title: Time evolution of income distributions with subgroup decompositions Abstract: In this paper, we propose a two-step decomposition procedure for studying the functional time series of income distribution (ID) of a population under a subgroup classification. Using the law of total probability, we first decompose the overall ID as a linear combination of the subgroup IDs weighted by the subgroup shares. In the second step, we use a functional principle component analysis to decompose the subgroup ID as a class of orthonormal functions with time-varying coefficients. We then apply this two-step decomposition to develop a class of models for exploring the ID evolution, the ID change, and the dynamics of various distributional features at different levels ranging from broad to specific. For empirical illustration, we apply the proposed methods to explore Taiwan’s family ID evolution from 1981 to 2014. Journal: Econometric Reviews Pages: 826-857 Issue: 8 Volume: 39 Year: 2020 Month: 9 X-DOI: 10.1080/07474938.2020.1772570 File-URL: http://hdl.handle.net/10.1080/07474938.2020.1772570 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:8:p:826-857 Template-Type: ReDIF-Article 1.0 Author-Name: Cheng Hsiao Author-X-Name-First: Cheng Author-X-Name-Last: Hsiao Title: Estimation of fixed effects dynamic panel data models: linear differencing or conditional expectation Abstract: This note discusses the pros and cons of using the conditional mean approach of Mundlak and Chamberlain and the linear difference approach to deal with the incidental parameters issue in estimating fixed effects dynamic panel data models. The importance of the data generating process of the explanatory variables and the proper treatment of initial values for either approach to get asymptotically unbiased estimators are demonstrated both analytically and through Monte Carlo studies. Journal: Econometric Reviews Pages: 858-874 Issue: 8 Volume: 39 Year: 2020 Month: 9 X-DOI: 10.1080/07474938.2020.1772571 File-URL: http://hdl.handle.net/10.1080/07474938.2020.1772571 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:8:p:858-874 Template-Type: ReDIF-Article 1.0 Author-Name: Mikkel Bennedsen Author-X-Name-First: Mikkel Author-X-Name-Last: Bennedsen Title: Semiparametric estimation and inference on the fractal index of Gaussian and conditionally Gaussian time series data Abstract: This paper studies the properties of a particular estimator of the fractal index of a time series with a view to applications in financial econometrics and mathematical finance. We show how measurement noise (e.g., microstructure noise) in the observations will bias the estimator, potentially resulting in the econometrician erroneously finding evidence of fractal characteristics in a time series. We propose a new estimator which is robust to such noise and construct a formal hypothesis test for the presence of noise in the observations. A number of simulation exercises are carried out, providing guidance for implementation of the theory. Finally, the methods are illustrated on two empirical data sets; one of turbulent velocity flows and one of financial prices. Journal: Econometric Reviews Pages: 875-903 Issue: 9 Volume: 39 Year: 2020 Month: 10 X-DOI: 10.1080/07474938.2020.1721832 File-URL: http://hdl.handle.net/10.1080/07474938.2020.1721832 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:9:p:875-903 Template-Type: ReDIF-Article 1.0 Author-Name: Yundong Tu Author-X-Name-First: Yundong Author-X-Name-Last: Tu Author-Name: Nigel Chan Author-X-Name-First: Nigel Author-X-Name-Last: Chan Author-Name: Qiying Wang Author-X-Name-First: Qiying Author-X-Name-Last: Wang Title: Testing for a unit root with nonstationary nonlinear heteroskedasticity Abstract: We provide a large sample theory for the Dickey-Fuller unit root test when the volatility process is driven by a nonlinear transformation of nonstationary time series. Our theory allows the dynamics of future volatilities being affected by the current shock, and involves replacing the nuisance nonlinear function by its consistent kernel estimator. This improves the existing literature for unit root testing with heteroskedasticity by using external data explicitly. We further propose a valid bootstrap procedure to implement the test, which is found to perform well in finite samples. A real data example is also provided Journal: Econometric Reviews Pages: 904-929 Issue: 9 Volume: 39 Year: 2020 Month: 10 X-DOI: 10.1080/07474938.2020.1721833 File-URL: http://hdl.handle.net/10.1080/07474938.2020.1721833 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:9:p:904-929 Template-Type: ReDIF-Article 1.0 Author-Name: Juan Lin Author-X-Name-First: Juan Author-X-Name-Last: Lin Author-Name: Ximing Wu Author-X-Name-First: Ximing Author-X-Name-Last: Wu Title: A diagnostic test for specification of copulas under censorship Abstract: We propose a copula specification test for copula-based multivariate survival models under censorship. This flexible test is applicable to both Archimedean and non-Archimedean copulas and provides useful pointers for alternative copula construction when a null distribution is rejected. It is shown to be consistent and asymptotically distribution free. We demonstrate its good finite sample performance via Monte Carlo simulations. We apply this test to an insurance dataset on losses and expenses. Our test rejects the hypothesis of Gaussian copula. Furthermore, its diagnostic information suggests an alternative copula specification that captures the extreme-value dependence exhibited in the data. Journal: Econometric Reviews Pages: 930-946 Issue: 9 Volume: 39 Year: 2020 Month: 10 X-DOI: 10.1080/07474938.2020.1721834 File-URL: http://hdl.handle.net/10.1080/07474938.2020.1721834 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:9:p:930-946 Template-Type: ReDIF-Article 1.0 Author-Name: Martina Danielova Zaharieva Author-X-Name-First: Martina Danielova Author-X-Name-Last: Zaharieva Author-Name: Mark Trede Author-X-Name-First: Mark Author-X-Name-Last: Trede Author-Name: Bernd Wilfling Author-X-Name-First: Bernd Author-X-Name-Last: Wilfling Title: Bayesian semiparametric multivariate stochastic volatility with application Abstract: In this article, we establish a Cholesky-type multivariate stochastic volatility estimation framework, in which we let the innovation vector follow a Dirichlet process mixture (DPM), thus enabling us to model highly flexible return distributions. The Cholesky decomposition allows parallel univariate process modeling and creates potential for estimating high-dimensional specifications. We use Markov chain Monte Carlo methods for posterior simulation and predictive density computation. We apply our framework to a five-dimensional stock-return data set and analyze international stock-market co-movements among the largest stock markets. The empirical results show that our DPM modeling of the innovation vector yields substantial gains in out-of-sample density forecast accuracy when compared with the prevalent benchmark models. Journal: Econometric Reviews Pages: 947-970 Issue: 9 Volume: 39 Year: 2020 Month: 10 X-DOI: 10.1080/07474938.2020.1761152 File-URL: http://hdl.handle.net/10.1080/07474938.2020.1761152 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:9:p:947-970 Template-Type: ReDIF-Article 1.0 Author-Name: João Henrique G. Mazzeu Author-X-Name-First: João Henrique G. Author-X-Name-Last: Mazzeu Author-Name: Gloria González-Rivera Author-X-Name-First: Gloria Author-X-Name-Last: González-Rivera Author-Name: Esther Ruiz Author-X-Name-First: Esther Author-X-Name-Last: Ruiz Author-Name: Helena Veiga Author-X-Name-First: Helena Author-X-Name-Last: Veiga Title: A bootstrap approach for generalized Autocontour testing Implications for VIX forecast densities Abstract: We propose an extension of the Generalized Autocontour tests for dynamic specification (evaluation) of in-sample (out-of-sample) conditional densities. The new tests are based on probability integral transforms computed from bootstrap conditional densities that incorporate parameter uncertainty without relying on parametric assumptions of the error distribution. Their finite sample distributions are well approximated using standard asymptotic distributions while they are easy to implement and provide information about potential sources of misspecification. We apply the new tests to the Heterogeneous Autoregressive and the Multiplicative Error models of the VIX index and find strong evidence against the parametric assumptions of the conditional densities. Journal: Econometric Reviews Pages: 971-990 Issue: 10 Volume: 39 Year: 2020 Month: 11 X-DOI: 10.1080/07474938.2020.1761150 File-URL: http://hdl.handle.net/10.1080/07474938.2020.1761150 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:10:p:971-990 Template-Type: ReDIF-Article 1.0 Author-Name: Christian Brownlees Author-X-Name-First: Christian Author-X-Name-Last: Brownlees Author-Name: Eulalia Nualart Author-X-Name-First: Eulalia Author-X-Name-Last: Nualart Author-Name: Yucheng Sun Author-X-Name-First: Yucheng Author-X-Name-Last: Sun Title: On the estimation of integrated volatility in the presence of jumps and microstructure noise Abstract: This paper is concerned with the problem of the estimation of the integrated volatility of log-prices based on high frequency data when both price jumps and market microstructure noise are present. We begin by providing a survey of the leading estimators introduced in the literature to tackle volatility estimation in this setting. We then introduce novel integrated volatility estimators based on a truncation technique and establish their properties. Finally, we carry out a simulation study to compare the performance of the different estimation techniques. Journal: Econometric Reviews Pages: 991-1013 Issue: 10 Volume: 39 Year: 2020 Month: 11 X-DOI: 10.1080/07474938.2020.1735751 File-URL: http://hdl.handle.net/10.1080/07474938.2020.1735751 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:10:p:991-1013 Template-Type: ReDIF-Article 1.0 Author-Name: John Gardner Author-X-Name-First: John Author-X-Name-Last: Gardner Title: Identification and estimation of average causal effects when treatment status is ignorable within unobserved strata Abstract: This paper extends matching and propensity-score reweighting methods to settings in which unobserved variables influence both treatment assignment and counterfactual outcomes. Identification proceeds under the assumption that counterfactual outcomes are independent of treatment status conditional on observed covariates and membership in one of a finite set of latent classes. Individuals are first assigned to latent classes according to posterior probabilities of class membership derived from a finite-mixture model that relates a set of auxiliary variables to latent class membership. Average causal effects are then identified by comparing outcomes among treated and untreated individuals assigned to the same class, correcting for misclassifications arising in the first step. The identification procedure suggests computationally attractive latent-class matching and propensity-score reweighting estimators that obviate the need to directly estimate the distributions of counterfactual outcomes. In Monte Carlo studies, the resulting estimates are centered around the correct average causal effects with minimal loss of precision compared to competing estimators that misstate those effects. I apply the methods to estimate the effect of gang membership on violent delinquency. Journal: Econometric Reviews Pages: 1014-1041 Issue: 10 Volume: 39 Year: 2020 Month: 11 X-DOI: 10.1080/07474938.2020.1735748 File-URL: http://hdl.handle.net/10.1080/07474938.2020.1735748 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:10:p:1014-1041 Template-Type: ReDIF-Article 1.0 Author-Name: Maurice J. G. Bun Author-X-Name-First: Maurice J. G. Author-X-Name-Last: Bun Author-Name: Helmut Farbmacher Author-X-Name-First: Helmut Author-X-Name-Last: Farbmacher Author-Name: Rutger W. Poldermans Author-X-Name-First: Rutger W. Author-X-Name-Last: Poldermans Title: Finite sample properties of the GMM Anderson–Rubin test Abstract: In the construction of the GMM version of the Anderson and Rubin (AR) test statistic there is the choice to use either uncentered or centered moment conditions to form the weighting matrix. We show that, when the number of moment conditions is moderately large, the centered GMM-AR test is oversized. At the same time, the uncentered version becomes conservative at conventional significance levels. Using an asymptotic expansion, we point to a missing degrees-of-freedom correction in the centered version of the GMM-AR test, which implicitly incorporates an Edgeworth correction. Monte Carlo experiments corroborate our theoretical findings and illustrate the accuracy of the degrees-of-freedom corrected, centered GMM-AR statistic in finite samples. Journal: Econometric Reviews Pages: 1042-1056 Issue: 10 Volume: 39 Year: 2020 Month: 11 X-DOI: 10.1080/07474938.2020.1761149 File-URL: http://hdl.handle.net/10.1080/07474938.2020.1761149 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:10:p:1042-1056 Template-Type: ReDIF-Article 1.0 Author-Name: P. de Zea Bermudez Author-X-Name-First: P. Author-X-Name-Last: de Zea Bermudez Author-Name: J. Miguel Marín Author-X-Name-First: J. Miguel Author-X-Name-Last: Marín Author-Name: Helena Veiga Author-X-Name-First: Helena Author-X-Name-Last: Veiga Title: Data cloning estimation for asymmetric stochastic volatility models Abstract: The paper proposes the use of data cloning (DC) to the estimation of general univariate asymmetric stochastic volatility (ASV) models with flexible distributions for the standardized returns. These models are able to capture the asymmetric volatility, the leptokurtosis and the skewness of the distribution of returns. Data cloning is a general technique to compute maximum likelihood estimators, along with their asymptotic variances, by means of a Markov chain Monte Carlo (MCMC) methodology. The main aim of this paper is to illustrate how easily general univariate ASV models can be estimated and consequently studied via data cloning. Changes of specifications, priors and sampling error distributions are done with minor modifications of the code. Using an intensive simulation study, the finite sample properties of the estimators of the parameters are evaluated and compared to those of a benchmark estimator that is also user-friendly. The results show that the proposed estimator is computationally efficient, and can be an effective alternative to the existing estimation methods applied to ASV models. Finally, we use data cloning to estimate the parameters of general ASV models and forecast the one-step-ahead volatility of S&P 500 and FTSE-100 daily returns. Journal: Econometric Reviews Pages: 1057-1074 Issue: 10 Volume: 39 Year: 2020 Month: 11 X-DOI: 10.1080/07474938.2020.1770997 File-URL: http://hdl.handle.net/10.1080/07474938.2020.1770997 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:10:p:1057-1074 Template-Type: ReDIF-Article 1.0 Author-Name: Xingwei Hu Author-X-Name-First: Xingwei Author-X-Name-Last: Hu Title: A theory of dichotomous valuation with applications to variable selection Abstract: An econometric or statistical model may undergo a marginal gain if we admit a new variable to the model, and a marginal loss if we remove an existing variable from the model. Assuming equality of opportunity among all candidate variables, we derive a valuation framework by the expected marginal gain and marginal loss in all potential modeling scenarios. However, marginal gain and loss are not symmetric; thus, we introduce three unbiased solutions. When used in variable selection, our new approaches significantly outperform several popular methods used in practice. The results also explore some novel traits of the Shapley value. Journal: Econometric Reviews Pages: 1075-1099 Issue: 10 Volume: 39 Year: 2020 Month: 11 X-DOI: 10.1080/07474938.2020.1735750 File-URL: http://hdl.handle.net/10.1080/07474938.2020.1735750 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:10:p:1075-1099 Template-Type: ReDIF-Article 1.0 Author-Name: Shangwei Zhao Author-X-Name-First: Shangwei Author-X-Name-Last: Zhao Author-Name: Yanyuan Ma Author-X-Name-First: Yanyuan Author-X-Name-Last: Ma Author-Name: Alan T. K. Wan Author-X-Name-First: Alan T. K. Author-X-Name-Last: Wan Author-Name: Xinyu Zhang Author-X-Name-First: Xinyu Author-X-Name-Last: Zhang Author-Name: Shouyang Wang Author-X-Name-First: Shouyang Author-X-Name-Last: Wang Title: Model averaging in a multiplicative heteroscedastic model Abstract: In recent years, the body of literature on frequentist model averaging in econometrics has grown significantly. Most of this work focuses on models with different mean structures but leaves out the variance consideration. In this article, we consider a regression model with multiplicative heteroscedasticity and develop a model averaging method that combines maximum likelihood estimators of unknown parameters in both the mean and variance functions of the model. Our weight choice criterion is based on a minimization of a plug-in estimator of the model average estimator’s squared prediction risk. We prove that the new estimator possesses an asymptotic optimality property. Our investigation of finite-sample performance by simulations demonstrates that the new estimator frequently exhibits very favorable properties compared with some existing heteroscedasticity-robust model average estimators. The model averaging method hedges against the selection of very bad models and serves as a remedy to variance function mis-specification, which often discourages practitioners from modeling heteroscedasticity altogether. The proposed model average estimator is applied to the analysis of two data sets on housing and economic growth. Journal: Econometric Reviews Pages: 1100-1124 Issue: 10 Volume: 39 Year: 2020 Month: 11 X-DOI: 10.1080/07474938.2020.1770995 File-URL: http://hdl.handle.net/10.1080/07474938.2020.1770995 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:10:p:1100-1124 Template-Type: ReDIF-Article 1.0 Author-Name: The Editors Title: List of referees Journal: Econometric Reviews Pages: 1125-1126 Issue: 10 Volume: 39 Year: 2020 Month: 11 X-DOI: 10.1080/07474938.2020.1835290 File-URL: http://hdl.handle.net/10.1080/07474938.2020.1835290 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2020:i:10:p:1125-1126 Template-Type: ReDIF-Article 1.0 Author-Name: Mehmet Caner Author-X-Name-First: Mehmet Author-X-Name-Last: Caner Author-Name: Xu Han Author-X-Name-First: Xu Author-X-Name-Last: Han Title: An upper bound for functions of estimators in high dimensions Abstract: We provide an upper bound as a random variable for the functions of estimators in high dimensions. This upper bound may help establish the rate of convergence of functions in high dimensions. The upper bound random variable may converge faster, slower, or at the same rate as estimators depending on the behavior of the partial derivative of the function. We illustrate this via three examples. The first two examples use the upper bound for testing in high dimensions, and third example derives the estimated out-of-sample variance of large portfolios. All our results allow for a larger number of parameters, p, than the sample size, n. Journal: Econometric Reviews Pages: 1-13 Issue: 1 Volume: 40 Year: 2021 Month: 1 X-DOI: 10.1080/07474938.2020.1808370 File-URL: http://hdl.handle.net/10.1080/07474938.2020.1808370 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:40:y:2021:i:1:p:1-13 Template-Type: ReDIF-Article 1.0 Author-Name: Cynthia Fan Yang Author-X-Name-First: Cynthia Fan Author-X-Name-Last: Yang Title: Common factors and spatial dependence: an application to US house prices Abstract: This article considers panel data models with cross-sectional dependence arising from both spatial autocorrelation and unobserved common factors. It proposes estimation methods that employ cross-sectional averages as factor proxies, including the 2SLS, Best 2SLS, and GMM estimations. The proposed estimators are robust to unknown heteroskedasticity and serial correlation in the disturbances, unrequired to estimate the number of unknown factors, and computationally tractable. The article establishes the asymptotic distributions of these estimators and compares their consistency and efficiency properties. Extensive Monte Carlo experiments lend support to the theoretical findings and demonstrate the satisfactory finite sample performance of the proposed estimators. The empirical section of the article finds strong evidence of spatial dependence of real house price changes across 377 Metropolitan Statistical Areas in the US from 1975Q1 to 2014Q4. Journal: Econometric Reviews Pages: 14-50 Issue: 1 Volume: 40 Year: 2021 Month: 1 X-DOI: 10.1080/07474938.2020.1741785 File-URL: http://hdl.handle.net/10.1080/07474938.2020.1741785 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:40:y:2021:i:1:p:14-50 Template-Type: ReDIF-Article 1.0 Author-Name: Vanessa Berenguer-Rico Author-X-Name-First: Vanessa Author-X-Name-Last: Berenguer-Rico Author-Name: Ines Wilms Author-X-Name-First: Ines Author-X-Name-Last: Wilms Title: Heteroscedasticity testing after outlier removal Abstract: Given the effect that outliers can have on regression and specification testing, a vastly used robustification strategy by practitioners consists in: (i) starting the empirical analysis with an outlier detection procedure to deselect atypical data values; then (ii) continuing the analysis with the selected non-outlying observations. The repercussions of such robustifying procedure on the asymptotic properties of subsequent inferential procedures are, however, underexplored. We study the effects of such a strategy on testing for heteroscedasticity. Specifically, using weighted and marked empirical processes of residuals theory, we show that the White test implemented after the outlier detection and removal is asymptotically chi-square if the underlying errors are symmetric. In a simulation study, we show that—depending on the type of outliers—the standard White test can be either severely undersized or oversized, as well as have trivial power. The statistic applied after deselecting outliers has good finite sample properties under symmetry but can suffer from size distortions under asymmetric errors. Given these results, we devise an empirical modeling strategy to guide practitioners whose preferred approach is to remove outliers from the sample. Journal: Econometric Reviews Pages: 51-85 Issue: 1 Volume: 40 Year: 2021 Month: 1 X-DOI: 10.1080/07474938.2020.1735749 File-URL: http://hdl.handle.net/10.1080/07474938.2020.1735749 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:40:y:2021:i:1:p:51-85 Template-Type: ReDIF-Article 1.0 Author-Name: Benjamin Poignard Author-X-Name-First: Benjamin Author-X-Name-Last: Poignard Author-Name: Jean-David Fermanian Author-X-Name-First: Jean-David Author-X-Name-Last: Fermanian Title: High-dimensional penalized arch processes Abstract: We introduce a general methodology to consistently estimate multidimensional ARCH models equation-by-equation, possibly with a very large number of parameters through penalization (Sparse Group Lasso). Some families of multidimensional ARCH models are proposed to tackle homogeneous or heterogeneous portfolios of assets. The corresponding conditions of stationarity and of positive definiteness are studied. We evaluate the relevance of such a strategy by simulation. The relative forecasting performances of our models are compared through the management of financial portfolios. Journal: Econometric Reviews Pages: 86-107 Issue: 1 Volume: 40 Year: 2021 Month: 1 X-DOI: 10.1080/07474938.2020.1761153 File-URL: http://hdl.handle.net/10.1080/07474938.2020.1761153 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:40:y:2021:i:1:p:86-107 Template-Type: ReDIF-Article 1.0 Author-Name: Victor Troster Author-X-Name-First: Victor Author-X-Name-Last: Troster Author-Name: Dominik Wied Author-X-Name-First: Dominik Author-X-Name-Last: Wied Title: A specification test for dynamic conditional distribution models with function-valued parameters Abstract: This paper proposes a practical and consistent specification test of conditional distribution models for dependent data in a general setting. Our approach covers conditional distribution models indexed by function-valued parameters, allowing for a wide range of useful models for risk management and forecasting, such as the quantile autoregressive model, the CAViaR model, and the distributional regression model. The new specification test (i) is valid for general linear and nonlinear conditional quantile models under dependent data, (ii) allows for dynamic misspecification of the past information set, (iii) is consistent against fixed alternatives, and (iv) has nontrivial power against Pitman deviations from the null hypothesis. As the test statistic is non-pivotal, we propose and theoretically justify a subsampling approach to obtain valid inference. Finally, we illustrate the applicability of our approach by analyzing models of the returns distribution and Value-at-Risk (VaR) of two major stock indexes. Journal: Econometric Reviews Pages: 109-127 Issue: 2 Volume: 40 Year: 2021 Month: 2 X-DOI: 10.1080/07474938.2020.1761151 File-URL: http://hdl.handle.net/10.1080/07474938.2020.1761151 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:40:y:2021:i:2:p:109-127 Template-Type: ReDIF-Article 1.0 Author-Name: Yu-Chin Hsu Author-X-Name-First: Yu-Chin Author-X-Name-Last: Hsu Author-Name: Kamhon Kan Author-X-Name-First: Kamhon Author-X-Name-Last: Kan Author-Name: Tsung-Chih Lai Author-X-Name-First: Tsung-Chih Author-X-Name-Last: Lai Title: Quantile structural treatment effects: application to smoking wage penalty and its determinants Abstract: We propose a new treatment effect parameter called the quantile structural treatment effect (QSTE) to distinguish between observed and unobserved treatment heterogeneity in the semiparametric additive potential outcome framework. The QSTE is defined as the quantile treatment effect if the observed covariates were exogenously set to a fixed value while keeping unobserved heterogeneity unchanged. We show the QSTE is identified under unconfoundedness and propose a semiparametric inverse probability weighted-type estimator that converges weakly to a Gaussian process. A multiplier bootstrap procedure is also carried out to construct uniform confidence bands. Using data from the Panel Study of Income Dynamics and focusing on the female group for the plausibility of the unconfoundedness assumption, we examine observed and unobserved determinants of the adverse effects of smoking on wages known as the smoking wage penalty. Our findings suggest that different levels of observable human capital may partly explain the smoking heterogeneity on wages. However, no evidence is found to support unobservable explanations such as discrimination against smokers, especially in the upper tail of the unobserved heterogeneity distribution. Journal: Econometric Reviews Pages: 128-147 Issue: 2 Volume: 40 Year: 2021 Month: 2 X-DOI: 10.1080/07474938.2020.1770994 File-URL: http://hdl.handle.net/10.1080/07474938.2020.1770994 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:40:y:2021:i:2:p:128-147 Template-Type: ReDIF-Article 1.0 Author-Name: Antonio Pacifico Author-X-Name-First: Antonio Author-X-Name-Last: Pacifico Title: Robust open Bayesian analysis: Overfitting, model uncertainty, and endogeneity issues in multiple regression models Abstract: The paper develops a computational method to deal with some open issues related to Bayesian model averaging for multiple linear models: overfitting, model uncertainty, endogeneity issues, and misspecified dynamics. The methodology takes the name of Robust Open Bayesian procedure. It is robust because the Bayesian inference is performed with a set of priors rather than a single prior and open because the model class is not fully known in advance, but rather is defined iteratively by MCMC algorithm. Conjugate informative priors are used to compute exact posterior probabilities. Empirical and simulated examples describe the functioning and performance of the procedure. Discussions with related works are also accounted for. Journal: Econometric Reviews Pages: 148-176 Issue: 2 Volume: 40 Year: 2021 Month: 2 X-DOI: 10.1080/07474938.2020.1770996 File-URL: http://hdl.handle.net/10.1080/07474938.2020.1770996 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:40:y:2021:i:2:p:148-176 Template-Type: ReDIF-Article 1.0 Author-Name: Matei Demetrescu Author-X-Name-First: Matei Author-X-Name-Last: Demetrescu Author-Name: Julian S. Leppin Author-X-Name-First: Julian S. Author-X-Name-Last: Leppin Author-Name: Stefan Reitz Author-X-Name-First: Stefan Author-X-Name-Last: Reitz Title: Homogeneous vs. heterogeneous transition functions in panel smooth transition regressions Abstract: (Panel) Smooth Transition Regressions substantially gained in popularity due to their flexibility in modeling regression coefficients as homogeneous or heterogeneous functions of various transition variables. In the estimation process, however, researchers typically face a tradeoff in the sense that a single (homogeneous) transition function may yield biased estimates if the true model is heterogeneous, while the latter specification is accompanied by convergence problems and longer estimation time, rendering their application less appealing. This paper proposes a Lagrange multiplier test indicating whether the homogeneous smooth transition regression model is appropriate or not. We provide time series and panel versions of the test and discuss the joint N, T limiting behavior of the test statistic under cross-sectional dependence and heteroskedasticity. The empirical size and power of the test are evaluated by Monte Carlo simulations. An application to US stock return predictability illustrates the practical usefulness of the proposed procedure. Journal: Econometric Reviews Pages: 177-196 Issue: 2 Volume: 40 Year: 2021 Month: 2 X-DOI: 10.1080/07474938.2020.1773666 File-URL: http://hdl.handle.net/10.1080/07474938.2020.1773666 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:40:y:2021:i:2:p:177-196 Template-Type: ReDIF-Article 1.0 Author-Name: Carol Alexander Author-X-Name-First: Carol Author-X-Name-Last: Alexander Author-Name: Emese Lazar Author-X-Name-First: Emese Author-X-Name-Last: Lazar Title: The continuous limit of weak GARCH Abstract: GARCH models are called ‘strong’ or ‘weak’ depending on the presence of parametric distributional assumptions for the innovations. The symmetric weak GARCH(1, 1) is the only model in the GARCH class that has been proved to be closed under the temporal aggregation property . This property is fundamental in two respects: (a) for a time-series model to be invariant to the data frequency; and (b) for a unique option-pricing model to exist as a continuous-time limit. While the symmetric weak GARCH(1, 1) is temporally aggregating precisely because it makes no parametric distributional assumptions, the lack of these also makes it harder to derive theoretical results. Rising to this challenge, we prove that its continuous-time limit is a geometric mean-reverting stochastic volatility process with diffusion coefficient governed by a time-varying kurtosis of log returns. When log returns are normal the limit coincides with Nelson’s strong GARCH(1, 1) limit. But unlike strong GARCH models, the weak GARCH(1, 1) has a unique limit because it makes no assumptions about the convergence of model parameters. The convergence of each parameter is uniquely determined by the temporal aggregation property. Empirical results show that the additional time-varying kurtosis parameter enhances both term-structure and smile effects in implied volatilities, thereby affording greater flexibility for the weak GARCH limit to fit real-world data from option prices. Journal: Econometric Reviews Pages: 197-216 Issue: 2 Volume: 40 Year: 2021 Month: 2 X-DOI: 10.1080/07474938.2020.1799592 File-URL: http://hdl.handle.net/10.1080/07474938.2020.1799592 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:40:y:2021:i:2:p:197-216 Template-Type: ReDIF-Article 1.0 Author-Name: Esfandiar Maasoumi Author-X-Name-First: Esfandiar Author-X-Name-Last: Maasoumi Title: “Fellows and Scholars of Econometric Reviews” Journal: Econometric Reviews Pages: 217-219 Issue: 3 Volume: 40 Year: 2021 Month: 4 X-DOI: 10.1080/07474938.2021.1899607 File-URL: http://hdl.handle.net/10.1080/07474938.2021.1899607 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:40:y:2021:i:3:p:217-219 Template-Type: ReDIF-Article 1.0 Author-Name: Lorenzo Trapani Author-X-Name-First: Lorenzo Author-X-Name-Last: Trapani Title: Testing for strict stationarity in a random coefficient autoregressive model Abstract: We propose a procedure to decide between the null hypothesis of (strict) stationarity and the alternative of nonstationarity, in the context of a random coefficient autoregression (RCAR). The procedure is based on randomizing a diagnostic which diverges to positive infinity under the null, and drifts to zero under the alternative. Thence, we propose a randomized test which can be used directly and—building on it—a decision rule to discern between the null and the alternative. The procedure can be applied under very general circumstances: albeit developed for an RCAR model, it can be used in the case of a standard AR(1) model, without requiring any modifications or prior knowledge. Also, the test works (again with no modification or prior knowledge being required) in the presence of infinite variance, and in general requires minimal assumptions on the existence of moments. Journal: Econometric Reviews Pages: 220-256 Issue: 3 Volume: 40 Year: 2021 Month: 4 X-DOI: 10.1080/07474938.2020.1773667 File-URL: http://hdl.handle.net/10.1080/07474938.2020.1773667 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:40:y:2021:i:3:p:220-256 Template-Type: ReDIF-Article 1.0 Author-Name: Daisuke Yamazaki Author-X-Name-First: Daisuke Author-X-Name-Last: Yamazaki Title: Improved confidence sets for the date of a structural break Abstract: Prior studies have proposed constructing confidence sets for the break date by inverting a sequence of tests for the date of a structural break. In this study, we improve these confidence sets by taking the direction of the break into account. Even when the break direction is unknown, we can consistently estimate it, enabling us to use the proposed method. Simulation results show that the proposed method effectively reduces the length of the confidence sets, while maintaining a good coverage rate. An empirical example illustrates the usefulness of the proposed method. Journal: Econometric Reviews Pages: 257-289 Issue: 3 Volume: 40 Year: 2021 Month: 4 X-DOI: 10.1080/07474938.2020.1780730 File-URL: http://hdl.handle.net/10.1080/07474938.2020.1780730 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:40:y:2021:i:3:p:257-289 Template-Type: ReDIF-Article 1.0 Author-Name: Abootaleb Shirvani Author-X-Name-First: Abootaleb Author-X-Name-Last: Shirvani Author-Name: Svetlozar T. Rachev Author-X-Name-First: Svetlozar T. Author-X-Name-Last: Rachev Author-Name: Frank J. Fabozzi Author-X-Name-First: Frank J. Author-X-Name-Last: Fabozzi Title: Multiple subordinated modeling of asset returns: Implications for option pricing Abstract: Motivated by behavioral finance, we introduce multiple embedded financial time clocks. Consistent with asset pricing theory in analyzing equity returns, the investors’ view is considered by introducing a behavioral subordinator. Subordinating to the Brownian motion process in the log-normal model results in a new log-price process whose parameter is as important as the mean and variance. We describe new distributions, demonstrating their use to model tail behavior. The models are applied to S&P 500 returns, treating the Chicago Board Options Exchange (CBOE) volatility index (VIX) as intrinsic-time change and CBOE Volatility-of-Volatility Index as the volatility subordinator. We find these volatility indexes fail as time-change subordinators. We employ a double subordinator model to explain the equity premium puzzle and the excess volatility puzzle. The results indicate the puzzles can be explained by fitting a double subordinator model to the historical data. Journal: Econometric Reviews Pages: 290-319 Issue: 3 Volume: 40 Year: 2021 Month: 4 X-DOI: 10.1080/07474938.2020.1781404 File-URL: http://hdl.handle.net/10.1080/07474938.2020.1781404 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:40:y:2021:i:3:p:290-319 Template-Type: ReDIF-Article 1.0 Author-Name: Ruohao Zhang Author-X-Name-First: Ruohao Author-X-Name-Last: Zhang Author-Name: Subal C. Kumbhakar Author-X-Name-First: Subal C. Author-X-Name-Last: Kumbhakar Author-Name: Hung-pin Lai Author-X-Name-First: Hung-pin Author-X-Name-Last: Lai Title: Estimation of panel model with heteroskedasticity in both idiosyncratic and individual specific errors Abstract: In this paper we consider adaptive estimation of a panel data model with unknown heteroskedasticity in both the idiosyncratic and the individual specific random components. We use the kernel estimator for the unknown variances first and then implement the GLS estimator. We also examine the finite sample performance of the adaptive estimators and compare them with several widely used estimators via Monte Carlo experiments. We find that with a proper bandwidth, our adaptive estimator performs much better than other estimators in terms of both estimation efficiency and test size. Besides, a larger bandwidth yields better estimation efficiency and lower test size. Journal: Econometric Reviews Pages: 415-432 Issue: 4 Volume: 40 Year: 2020 Month: 8 X-DOI: 10.1080/07474938.2020.1808372 File-URL: http://hdl.handle.net/10.1080/07474938.2020.1808372 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:40:y:2020:i:4:p:415-432 Template-Type: ReDIF-Article 1.0 Author-Name: Anders Isaksson Author-X-Name-First: Anders Author-X-Name-Last: Isaksson Author-Name: Chenjun Shang Author-X-Name-First: Chenjun Author-X-Name-Last: Shang Author-Name: Robin C. Sickles Author-X-Name-First: Robin C. Author-X-Name-Last: Sickles Title: Nonstructural analysis of productivity growth for the industrialized countries: a jackknife model averaging approach Abstract: Various nonstructural models of productivity growth have been proposed in the literature. In either class of models, predictive measurements of productivity and efficiency are obtained. The different approaches to productivity and efficiency measurement all have their merits. However, they generate different results and it is in principle impossible to know which of them produces ”true” estimates. We argue that instead of choosing between approaches, the analyst can average across the results generated by them. Unfortunately, this begs the question which averaging method to use? This paper examines the model averaging approaches of Hansen and Racine (2012), which can provide a vehicle to weight predictions (in the form of productivity and efficiency measurements) from different nonstructural methods. We first describe the jackknife model averaging estimator proposed by Hansen and Racine (2012) and illustrate how to apply the technique to a set of competing stochastic frontier estimators. The derived method is then used to analyze productivity and efficiency dynamics in 25 high-industrialized countries over the period 1990 to 2014. Through the empirical application, we show that the model averaging method provides relatively stable estimates, in comparison to standard model selection methods that simply select one model with the highest measure of goodness of fit. Journal: Econometric Reviews Pages: 321-358 Issue: 4 Volume: 40 Year: 2020 Month: 8 X-DOI: 10.1080/07474938.2020.1788820 File-URL: http://hdl.handle.net/10.1080/07474938.2020.1788820 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:40:y:2020:i:4:p:321-358 Template-Type: ReDIF-Article 1.0 Author-Name: Liang Jiang Author-X-Name-First: Liang Author-X-Name-Last: Jiang Author-Name: Xiaohu Wang Author-X-Name-First: Xiaohu Author-X-Name-Last: Wang Author-Name: Jun Yu Author-X-Name-First: Jun Author-X-Name-Last: Yu Title: In-fill asymptotic theory for structural break point in autoregressions Abstract: This article obtains the exact distribution of the maximum likelihood estimator of structural break point in the Ornstein–Uhlenbeck process when a continuous record is available. The exact distribution is asymmetric, tri-modal, dependent on the initial condition. These three properties are also found in the finite sample distribution of the least squares (LS) estimator of structural break point in autoregressive (AR) models. Motivated by these observations, the article then develops an in-fill asymptotic theory for the LS estimator of structural break point in the AR(1) coefficient. The in-fill asymptotic distribution is also asymmetric, tri-modal, dependent on the initial condition, and delivers excellent approximations to the finite sample distribution. Unlike the long-span asymptotic theory, which depends on the underlying AR roots and hence is tailor-made but is only available in a rather limited number of cases, the in-fill asymptotic theory is continuous in the underlying roots. Monte Carlo studies show that the in-fill asymptotic theory performs better than the long-span asymptotic theory for cases where the long-span theory is available and performs very well for cases where no long-span theory is available. The article also proposes to use the highest density region to construct confidence intervals for structural break point. Journal: Econometric Reviews Pages: 359-386 Issue: 4 Volume: 40 Year: 2020 Month: 7 X-DOI: 10.1080/07474938.2020.1788822 File-URL: http://hdl.handle.net/10.1080/07474938.2020.1788822 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:40:y:2020:i:4:p:359-386 Template-Type: ReDIF-Article 1.0 Author-Name: Shu-Hui Yu Author-X-Name-First: Shu-Hui Author-X-Name-Last: Yu Author-Name: Chor-yiu (CY) Sin Author-X-Name-First: Chor-yiu (CY) Author-X-Name-Last: Sin Title: On asymptotic risk of selecting models for possibly nonstationary time-series Abstract: Model selection criteria are often assessed by the so-called asymptotic risk. Asymptotic risk is defined either with the mean-squared error of estimated parameters; or with the mean-squared error of prediction. The literature focuses on i.i.d. or stationary time-series data though. Using the latter definition of asymptotic risk, this paper assesses the conventional AIC-type and BIC-type information criteria, which are arguably most suitable for univariate time series in which the lags are naturally ordered. Throughout we consider a univariate AR process in which the AR order and the order of integratedness are finite but unknown. We prove the BIC-type information criterion, whose penalty goes to infinity, attains zero asymptotic excess risk. In contrast, the AIC-type information criterion, whose penalty goes to a finite number, renders a strictly positive asymptotic excess risk. Further, the asymptotic excess risk increases with the admissible number of lags. The last result gives a warning on possible over-fitting of certain high-dimensional analyses, should the underlying data generating process be strongly sparse, that is, the true dimension be finite. In sum, we extend the existing asymptotic risk results in threefold: (i) a general I(d) process; (ii) same-realization prediction; and (iii) an information criterion more general than AIC. A simulation study and a small-scale empirical application compare the excess risk of AIC with those of AIC3, HQIC, BIC, Lasso as well as adaptive Lasso. Journal: Econometric Reviews Pages: 387-414 Issue: 4 Volume: 40 Year: 2021 Month: 4 X-DOI: 10.1080/07474938.2020.1777709 File-URL: http://hdl.handle.net/10.1080/07474938.2020.1777709 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:40:y:2021:i:4:p:387-414 Template-Type: ReDIF-Article 1.0 Author-Name: Akanksha Negi Author-X-Name-First: Akanksha Author-X-Name-Last: Negi Author-Name: Jeffrey M. Wooldridge Author-X-Name-First: Jeffrey M. Author-X-Name-Last: Wooldridge Title: Revisiting regression adjustment in experiments with heterogeneous treatment effects Abstract: In the context of random sampling, we show that linear full (separate) regression adjustment (FRA) on the control and treatment groups is, asymptotically, no less efficient than both the simple difference-in-means estimator and the pooled regression adjustment estimator; with heterogeneous treatment effects, FRA is usually strictly more efficient. We also propose a class of nonlinear regression adjustment estimators where consistency is ensured despite arbitrary misspecification of the conditional mean function. A simulation study confirms that nontrivial efficiency gains are possible with linear FRA, and that further gains are possible, even under severe mean misspecification, using nonlinear FRA. Journal: Econometric Reviews Pages: 504-534 Issue: 5 Volume: 40 Year: 2021 Month: 4 X-DOI: 10.1080/07474938.2020.1824732 File-URL: http://hdl.handle.net/10.1080/07474938.2020.1824732 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:40:y:2021:i:5:p:504-534 Template-Type: ReDIF-Article 1.0 Author-Name: Yingyao Hu Author-X-Name-First: Yingyao Author-X-Name-Last: Hu Author-Name: Ruli Xiao Author-X-Name-First: Ruli Author-X-Name-Last: Xiao Title: Global estimation of finite mixture and misclassification models with an application to multiple equilibria Abstract: We show that the identification results of finite mixture and misclassification models are equivalent in a widely used scenario except for an extra ordering assumption. In the misclassification model, an ordering condition is imposed to pin down the precise values of the latent variable, which are also of interest to researchers and need to be identified. In contrast, finite mixture models are usually identified up to permutations of a latent index, which results in local identification. This local identification is satisfactory because the latent index does not convey any economic meaning. However, reaching global identification is important for estimation, especially when researchers use bootstrap to estimate standard errors. This is because standard errors approximated by bootstrap may be incorrect without a global estimator. We demonstrate that games with multiple equilibria fit in our framework and the global estimator with ordering conditions provides more reliable estimates. Journal: Econometric Reviews Pages: 455-469 Issue: 5 Volume: 40 Year: 2021 Month: 4 X-DOI: 10.1080/07474938.2020.1797302 File-URL: http://hdl.handle.net/10.1080/07474938.2020.1797302 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:40:y:2021:i:5:p:455-469 Template-Type: ReDIF-Article 1.0 Author-Name: Antoine A. Djogbenou Author-X-Name-First: Antoine A. Author-X-Name-Last: Djogbenou Title: Model selection in factor-augmented regressions with estimated factors Abstract: This paper proposes two consistent model selection procedures for factor-augmented regressions (FAR) in finite samples. We first demonstrate that the usual cross-validation is inconsistent, but that a generalization, leave-d-out cross-validation, is consistent. The second proposed criterion is a generalization of the bootstrap approximation of the squared error of prediction to FARs. The paper provides the validity results and documents their finite sample performance through simulations. An illustrative empirical application that analyzes the relationship between the equity premium and factors extracted from a large panel of U.S. macroeconomic data is conducted. Journal: Econometric Reviews Pages: 470-503 Issue: 5 Volume: 40 Year: 2021 Month: 4 X-DOI: 10.1080/07474938.2020.1808371 File-URL: http://hdl.handle.net/10.1080/07474938.2020.1808371 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:40:y:2021:i:5:p:470-503 Template-Type: ReDIF-Article 1.0 Author-Name: Tommaso Proietti Author-X-Name-First: Tommaso Author-X-Name-Last: Proietti Title: Predictability, real time estimation, and the formulation of unobserved components models Abstract: The formulation of unobserved components models raises some relevant interpretative issues, owing to the existence of alternative observationally equivalent specifications, differing for the timing of the disturbances and their covariance matrix. We illustrate them with reference to unobserved components models with ARMA(m, m) reduced form, performing the decomposition of the series into an ARMA(m, q) signal, q≤m, and a noise component. We provide a characterization of the set of covariance structures that are observationally equivalent, when the models are formulated both in the future and the contemporaneous forms. Hence, we show that, while the point predictions and the contemporaneous real time estimates are invariant to the specification of the disturbances covariance matrix, the reliability cannot be identified, except for special cases requiring q<m−1. Journal: Econometric Reviews Pages: 433-454 Issue: 5 Volume: 40 Year: 2021 Month: 4 X-DOI: 10.1080/07474938.2020.1793508 File-URL: http://hdl.handle.net/10.1080/07474938.2020.1793508 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:40:y:2021:i:5:p:433-454 Template-Type: ReDIF-Article 1.0 Author-Name: The Editors Title: List of referees Journal: Econometric Reviews Pages: 1038-1039 Issue: 10 Volume: 40 Year: 2021 Month: 11 X-DOI: 10.1080/07474938.2021.1907093 File-URL: http://hdl.handle.net/10.1080/07474938.2021.1907093 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:40:y:2021:i:10:p:1038-1039 Template-Type: ReDIF-Article 1.0 Author-Name: Yonghui Zhang Author-X-Name-First: Yonghui Author-X-Name-Last: Zhang Author-Name: Qiankun Zhou Author-X-Name-First: Qiankun Author-X-Name-Last: Zhou Title: Partially linear functional-coefficient dynamic panel data models: sieve estimation and specification testing Abstract: We study the nonparametric estimation and specification testing for partially linear functional-coefficient dynamic panel data models, where the effects of some covariates on the dependent variable vary nonparametrically according to a set of low-dimensional variables. Based on the sieve approximation of unknown slope functions, we propose a sieve 2SLS procedure to estimate the model. The asymptotic properties of the estimators of both parametric and nonparametric components are established when sample size N and T tend to infinity jointly. A nonparametric specification test for the constancy of slopes is also proposed. We show that after being appropriately standardized, the test is asymptotically normally distributed under the null hypothesis. The asymptotic properties of the test is also studied under a sequence of local Pitman alternatives and global alternatives. A set of Monte Carlo simulations show that our sieve 2SLS estimators and specification test perform remarkably well in finite samples. We apply our method to study the impact of income on democracy, and find strong evidence of nonlinear/nonconstant effect of income on democracy. Journal: Econometric Reviews Pages: 983-1006 Issue: 10 Volume: 40 Year: 2021 Month: 11 X-DOI: 10.1080/07474938.2021.1889175 File-URL: http://hdl.handle.net/10.1080/07474938.2021.1889175 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:40:y:2021:i:10:p:983-1006 Template-Type: ReDIF-Article 1.0 Author-Name: Qiuhua Xu Author-X-Name-First: Qiuhua Author-X-Name-Last: Xu Author-Name: Zongwu Cai Author-X-Name-First: Zongwu Author-X-Name-Last: Cai Author-Name: Ying Fang Author-X-Name-First: Ying Author-X-Name-Last: Fang Title: Semiparametric inferences for panel data models with fixed effects via nearest neighbor difference transformation Abstract: In this paper, we propose a simple method to estimate a partially varying-coefficient panel data model with fixed effects. By taking difference upon the nearest neighbor of the smoothing variables to remove the fixed effects, we employ the profile least squares method and local linear fitting to estimate the parametric and nonparametric parts, respectively. Moreover, a functional form specification test and a nonparametric Hausman type test are constructed and their asymptotic properties are derived. Monte Carlo simulations are conducted to examine the finite sample performance of our estimators and test statistics. Journal: Econometric Reviews Pages: 919-943 Issue: 10 Volume: 40 Year: 2021 Month: 2 X-DOI: 10.1080/07474938.2021.1889197 File-URL: http://hdl.handle.net/10.1080/07474938.2021.1889197 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:40:y:2021:i:10:p:919-943 Template-Type: ReDIF-Article 1.0 Author-Name: Fei Jin Author-X-Name-First: Fei Author-X-Name-Last: Jin Author-Name: Lung-fei Lee Author-X-Name-First: Lung-fei Author-X-Name-Last: Lee Author-Name: Jihai Yu Author-X-Name-First: Jihai Author-X-Name-Last: Yu Title: Sequential and efficient GMM estimation of dynamic short panel data models Abstract: This paper considers generalized method of moments (GMM) and sequential GMM (SGMM) estimation of dynamic short panel data models. The efficient GMM motivated from the quasi maximum likelihood (QML) can avoid the use of many instrument variables (IV) for estimation. It can be asymptotically efficient as maximum likelihood estimators (MLE) when disturbances are normal, and can be more efficient than QML estimators when disturbances are not normal. The SGMM, which also incorporates many IVs, generalizes the minimum distance estimation originated in Hsiao et al. . By focusing on the estimation of parameters of interest, the SGMM saves computational burden caused by nuisance parameters such as variances of disturbances. It is asymptotically as efficient as the corresponding GMM. In particular, the SGMM based on QML scores can generate a closed-form root estimator for the dynamic parameter, which is asymptotically as efficient as the QML estimator. Nuisance parameters can also be estimated efficiently by an additional SGMM step if they are of interest. Journal: Econometric Reviews Pages: 1007-1037 Issue: 10 Volume: 40 Year: 2021 Month: 2 X-DOI: 10.1080/07474938.2021.1889178 File-URL: http://hdl.handle.net/10.1080/07474938.2021.1889178 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:40:y:2021:i:10:p:1007-1037 Template-Type: ReDIF-Article 1.0 Author-Name: Tae-Hwy Lee Author-X-Name-First: Tae-Hwy Author-X-Name-Last: Lee Author-Name: Millie Yi Mao Author-X-Name-First: Millie Yi Author-X-Name-Last: Mao Author-Name: Aman Ullah Author-X-Name-First: Aman Author-X-Name-Last: Ullah Title: Estimation of high-dimensional dynamic conditional precision matrices with an application to forecast combination Abstract: The estimation of a large covariance matrix is challenging when the dimension p is large relative to the sample size n. Common approaches to deal with the challenge have been based on thresholding or shrinkage methods in estimating covariance matrices. However, in many applications (e.g., regression, forecast combination, portfolio selection), what we need is not the covariance matrix but its inverse (the precision matrix). In this paper we introduce a method of estimating the high-dimensional “dynamic conditional precision” (DCP) matrices. The proposed DCP algorithm is based on the estimator of a large unconditional precision matrix to deal with the high-dimension and the dynamic conditional correlation (DCC) model to embed a dynamic structure to the conditional precision matrix. The simulation results show that the DCP method performs substantially better than the methods of estimating covariance matrices based on thresholding or shrinkage methods. Finally, we examine the “forecast combination puzzle” using the DCP, thresholding, and shrinkage methods. Journal: Econometric Reviews Pages: 905-918 Issue: 10 Volume: 40 Year: 2021 Month: 11 X-DOI: 10.1080/07474938.2021.1889208 File-URL: http://hdl.handle.net/10.1080/07474938.2021.1889208 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:40:y:2021:i:10:p:905-918 Template-Type: ReDIF-Article 1.0 Author-Name: Jun Ma Author-X-Name-First: Jun Author-X-Name-Last: Ma Author-Name: Vadim Marmer Author-X-Name-First: Vadim Author-X-Name-Last: Marmer Author-Name: Artyom Shneyerov Author-X-Name-First: Artyom Author-X-Name-Last: Shneyerov Author-Name: Pai Xu Author-X-Name-First: Pai Author-X-Name-Last: Xu Title: Monotonicity-constrained nonparametric estimation and inference for first-price auctions Abstract: In the independent private values framework for first-price auctions, we propose a new nonparametric estimator of the probability density of latent valuations that imposes the monotonicity constraint on the estimated inverse bidding strategy. We show that our estimator has a smaller asymptotic variance than that of Guerre, Perrigne and Vuong’s estimator. In addition to establishing pointwise asymptotic normality of our estimator, we provide a bootstrap-based approach to constructing uniform confidence bands for the density function. Journal: Econometric Reviews Pages: 944-982 Issue: 10 Volume: 40 Year: 2021 Month: 11 X-DOI: 10.1080/07474938.2021.1889198 File-URL: http://hdl.handle.net/10.1080/07474938.2021.1889198 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:40:y:2021:i:10:p:944-982 Template-Type: ReDIF-Article 1.0 Author-Name: Tong Li Author-X-Name-First: Tong Author-X-Name-Last: Li Author-Name: Esfandiar Maasoumi Author-X-Name-First: Esfandiar Author-X-Name-Last: Maasoumi Author-Name: Zhijie Xiao Author-X-Name-First: Zhijie Author-X-Name-Last: Xiao Title: Econometric Reviews Honors Cheng Hsiao Journal: Econometric Reviews Pages: 535-539 Issue: 6 Volume: 40 Year: 2021 Month: 2 X-DOI: 10.1080/07474938.2021.1889180 File-URL: http://hdl.handle.net/10.1080/07474938.2021.1889180 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:40:y:2021:i:6:p:535-539 Template-Type: ReDIF-Article 1.0 Author-Name: Arie Beresteanu Author-X-Name-First: Arie Author-X-Name-Last: Beresteanu Author-Name: Yuya Sasaki Author-X-Name-First: Yuya Author-X-Name-Last: Sasaki Title: Quantile regression with interval data Abstract: This paper investigates the identification of quantiles and quantile regression parameters when observations are set valued. We define the identification set of quantiles of random sets in a way that extends the definition of quantiles for regular random variables. We then give sharp characterization of this set by extending concepts from random set theory. Applying the identification set of quantiles and its sharpness to parametric quantile regression models yields the identification set of the parameters and its sharpness. We apply our methods to data on localized environmental benefits and their impact on house values. Journal: Econometric Reviews Pages: 562-583 Issue: 6 Volume: 40 Year: 2021 Month: 7 X-DOI: 10.1080/07474938.2021.1889201 File-URL: http://hdl.handle.net/10.1080/07474938.2021.1889201 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:40:y:2021:i:6:p:562-583 Template-Type: ReDIF-Article 1.0 Author-Name: Roger Klein Author-X-Name-First: Roger Author-X-Name-Last: Klein Author-Name: Chan Shen Author-X-Name-First: Chan Author-X-Name-Last: Shen Title: An IV estimator for a functional coefficient model with endogenous discrete treatments Abstract: We propose instrumental variables (IV) estimators for averaged conditional treatment effects and the parameters upon which they depend in the context of a semiparametric outcome model with endogenous discrete treatment variables. For this model, the treatment impacts are unknown functions of a vector of indices that depend on a finite dimensional parameter vector. We develop the theory for an estimator of these impacts when they are averaged over regions of interest. We prove identification, consistency and N-asymptotic normality of the estimators. We also show that they are efficient under correct model specification. Further, we show that they are robust to misspecification of the propensity score model. In the Monte Carlo study, the estimators perform well over a wide variety of designs covering both correct and incorrect propensity score model specification. Journal: Econometric Reviews Pages: 540-561 Issue: 6 Volume: 40 Year: 2021 Month: 7 X-DOI: 10.1080/07474938.2021.1889200 File-URL: http://hdl.handle.net/10.1080/07474938.2021.1889200 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:40:y:2021:i:6:p:540-561 Template-Type: ReDIF-Article 1.0 Author-Name: Yanan He Author-X-Name-First: Yanan Author-X-Name-Last: He Author-Name: Ai Han Author-X-Name-First: Ai Author-X-Name-Last: Han Author-Name: Yongmiao Hong Author-X-Name-First: Yongmiao Author-X-Name-Last: Hong Author-Name: Yuying Sun Author-X-Name-First: Yuying Author-X-Name-Last: Sun Author-Name: Shouyang Wang Author-X-Name-First: Shouyang Author-X-Name-Last: Wang Title: Forecasting crude oil price intervals and return volatility via autoregressive conditional interval models Abstract: Crude oil prices are of vital importance for market participants and governments to make energy policies and decisions. In this paper, we apply a newly proposed autoregressive conditional interval (ACI) model to forecast crude oil prices. Compared with the existing point-based forecasting models, the interval-based ACI model can capture the dynamics of oil prices in both level and range of variation in a unified framework. Rich information contained in interval-valued observations can be simultaneously utilized, thus enhancing parameter estimation efficiency and model forecasting accuracy. In forecasting the monthly West Texas Intermediate (WTI) crude oil prices, we document that the ACI models outperform the popular point-based time series models. In particular, ACI models deliver better forecasts than univariate ARMA models and the vector error correction model (VECM). The gain of ACI models is found in out-of-sample monthly price interval forecasts as well as forecasts for point-valued highs, lows, and ranges. Compared with GARCH and conditional autoregressive range (CARR) models, ACI models are also superior in volatility (conditional variance) forecasts of oil prices. A trading strategy that makes use of the monthly high and low forecasts is further developed. This trading strategy generally yields more profitable trading returns under the ACI models than the point-based VECM. Journal: Econometric Reviews Pages: 584-606 Issue: 6 Volume: 40 Year: 2021 Month: 7 X-DOI: 10.1080/07474938.2021.1889202 File-URL: http://hdl.handle.net/10.1080/07474938.2021.1889202 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:40:y:2021:i:6:p:584-606 Template-Type: ReDIF-Article 1.0 Author-Name: Moonhee Cho Author-X-Name-First: Moonhee Author-X-Name-Last: Cho Author-Name: Xiaoyong Zheng Author-X-Name-First: Xiaoyong Author-X-Name-Last: Zheng Title: Bayesian estimation of dynamic panel data gravity model Abstract: In this paper, we develop Bayesian estimation method for inference of dynamic panel data gravity model. Our method deals with the many zeros problem and at the same time, allows for lagged dependent variables and multiple sets of unobserved effects. We apply our Bayesian estimation algorithm to reexamine the contemporaneous effect of GATT/WTO membership on trade. We find that our dynamic gravity model fits the data better than the same model without the lagged dependent variables that is often used in the literature and trade flow in the previous period has a large and positive effect on trade flow in the current period. We also find that the GATT/WTO membership does not appear to have a contemporaneous effect on trade flow. This result is consistent with the findings ofsome studies in the literature, but not with those of others. These results show the importance of including lagged dependent variables and multiple sets of unobserved effects in gravity model estimation. Journal: Econometric Reviews Pages: 607-634 Issue: 7 Volume: 40 Year: 2021 Month: 8 X-DOI: 10.1080/07474938.2021.1889203 File-URL: http://hdl.handle.net/10.1080/07474938.2021.1889203 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:40:y:2021:i:7:p:607-634 Template-Type: ReDIF-Article 1.0 Author-Name: Yan Meng Author-X-Name-First: Yan Author-X-Name-Last: Meng Author-Name: Jiti Gao Author-X-Name-First: Jiti Author-X-Name-Last: Gao Author-Name: Xibin Zhang Author-X-Name-First: Xibin Author-X-Name-Last: Zhang Author-Name: Xueyan Zhao Author-X-Name-First: Xueyan Author-X-Name-Last: Zhao Title: A panel data model of length of stay in hospitals for hip replacements Abstract: Inequality between private and public patients in Australia has been an ongoing concern due to its two tiered insurance system. This article investigates the variations in hospital length of stay for hip replacements using the Victorian Admitted Episodes Dataset from 2003/2004 to 2014/2015, employing a Bayesian hierarchical random coefficients model with trend. We find systematic differences in the length of stay between public and private hospitals, after observable patient complexity is controlled. This suggests shorter stays in public hospitals due to pressure from the Activity-based funding scheme, and longer stays in private system due to potential moral hazard. Our counterfactual analysis shows that public patients stay 1.8 days shorter than private patients in 2014, which leads to the “quicker but sicker” concern that is commonly voiced by the public. We also identify widespread variations among individual hospitals. Sources for such variation warrant closer investigation by policy makers. Journal: Econometric Reviews Pages: 688-707 Issue: 7 Volume: 40 Year: 2021 Month: 8 X-DOI: 10.1080/07474938.2021.1889196 File-URL: http://hdl.handle.net/10.1080/07474938.2021.1889196 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:40:y:2021:i:7:p:688-707 Template-Type: ReDIF-Article 1.0 Author-Name: Zhengfei Yu Author-X-Name-First: Zhengfei Author-X-Name-Last: Yu Title: Detecting multiple equilibria for continuous dependent variables Abstract: This article considers structural equations where continuous dependent variables are related to independent variables and unobservables through a nonparametric function. Multiple equilibria may arise when the structural equations admit multiple solutions. This article proposes a detecting criterion for the existence of multiple equilibria. The main finding is that multiple equilibria would reveal itself in the form of jump(s) in the density function of the dependent variables. When there is a unique equilibrium, the density function of dependent variables will be continuous, whereas when there are multiple equilibria, the density will have jump(s) under reasonable conditions. Journal: Econometric Reviews Pages: 635-656 Issue: 7 Volume: 40 Year: 2021 Month: 8 X-DOI: 10.1080/07474938.2021.1889204 File-URL: http://hdl.handle.net/10.1080/07474938.2021.1889204 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:40:y:2021:i:7:p:635-656 Template-Type: ReDIF-Article 1.0 Author-Name: Byunguk Kang Author-X-Name-First: Byunguk Author-X-Name-Last: Kang Author-Name: Jean-Marie Dufour Author-X-Name-First: Jean-Marie Author-X-Name-Last: Dufour Title: Exact and asymptotic identification-robust inference for dynamic structural equations with an application to New Keynesian Phillips Curves Abstract: Many models in econometrics involve endogeneity and lagged dependent variables. We start by observing that usual identification-robust (IR) tests are unreliable when model variables are nonstationary or nearly nonstationary. We propose IR methods which are also robust to nonstationarity: one Anderson-Rubin type procedure and two split-sample procedures. Our procedures are also robust to missing instruments. For distributional theory, three different sets of assumptions are considered. First, on assuming Gaussian structural errors, we show that two of the proposed statistics follow the standard F distribution. Second, for more general cases, we assume that the distribution of errors is completely specified up to an unknown scale factor, allowing the Monte Carlo test method to be applied. This assumption enables one to deal with non-Gaussian error distributions. For example, even when errors follow heavy-tailed distribution, such as the Cauchy distribution or more generally the family of stable distributions—which may not have moments and thus make inference difficult—our procedures provide simple and exact solutions. Third, we establish the asymptotic validity of our procedures under quite general distributional assumptions. We present simulation results showing that our procedures control their level correctly and have good power properties. The methods are applied to an empirical example, the New Keynesian Phillips curve, in which both weak identification and nonstationarity present challenges. The results of this empirical study suggest forward-looking behavior of U.S. inflation. Journal: Econometric Reviews Pages: 657-687 Issue: 7 Volume: 40 Year: 2021 Month: 8 X-DOI: 10.1080/07474938.2021.1889199 File-URL: http://hdl.handle.net/10.1080/07474938.2021.1889199 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:40:y:2021:i:7:p:657-687 Template-Type: ReDIF-Article 1.0 Author-Name: Qiuling Hua Author-X-Name-First: Qiuling Author-X-Name-Last: Hua Author-Name: Zhijie Xiao Author-X-Name-First: Zhijie Author-X-Name-Last: Xiao Author-Name: Hongtao Zhou Author-X-Name-First: Hongtao Author-X-Name-Last: Zhou Title: Right tail information and asset pricing Abstract: The right tail of the distribution of financial variables provides important information to investors and decision-makers. In this paper, we study the role of the right tail distributional information in finance. First, we propose semiparametric estimators for the right tail mean (RTM) and right tail variance (RTV). The proposed estimators use parsimonious parametric models to capture the dynamics of the data, and also allow for nonparametric flexibility in the distribution. These estimators can be estimated at the rate of root-T and are asymptotically normal. We then conduct a comparative study on the dynamics and empirical feature of the RTM and RTV in two international equity markets: The US and The Chinese stock markets. Third, we study the effect of right tail measures in the cross-sectional pricing of stock returns. Our empirical investigation indicates that the right tail information plays a significant role in explaining the cross-section pricing of stock returns. In addition, the RTV and left tail variance (LTV) have opposite impacts on asset prices. Finally, we use simulation based analysis to examine the impact of RTM on the optimal investment strategy. Our results have important implications for portfolio management in financial market. Journal: Econometric Reviews Pages: 728-749 Issue: 8 Volume: 40 Year: 2021 Month: 9 X-DOI: 10.1080/07474938.2021.1889179 File-URL: http://hdl.handle.net/10.1080/07474938.2021.1889179 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:40:y:2021:i:8:p:728-749 Template-Type: ReDIF-Article 1.0 Author-Name: Xiaoyong Cao Author-X-Name-First: Xiaoyong Author-X-Name-Last: Cao Author-Name: Xirong Chen Author-X-Name-First: Xirong Author-X-Name-Last: Chen Author-Name: Wenzheng Gao Author-X-Name-First: Wenzheng Author-X-Name-Last: Gao Author-Name: Cheng Hsiao Author-X-Name-First: Cheng Author-X-Name-Last: Hsiao Title: Smoothed maximum score estimation with nonparametrically generated covariates Abstract: This paper develops a two-stage semiparametric procedure to estimate the preference parameters of a binary choice model under uncertainty. In the model, the agent’s decision rule is affected by the conditional expectation. We nonparametrically estimate the conditional expectation in the first stage. Then, in the second stage, the preference parameters are estimated by the smoothed maximum score method. We establish the consistency and asymptotic distribution of the two-stage estimator. Furthermore, we also characterize the conditions under which the first-stage nonparametric estimation will not affect the asymptotic distribution of the smoothed maximum score estimator. Monte Carlo simulation results demonstrate that our proposed estimator performs well in finite samples. Journal: Econometric Reviews Pages: 796-813 Issue: 8 Volume: 40 Year: 2021 Month: 9 X-DOI: 10.1080/07474938.2021.1889205 File-URL: http://hdl.handle.net/10.1080/07474938.2021.1889205 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:40:y:2021:i:8:p:796-813 Template-Type: ReDIF-Article 1.0 Author-Name: Cindy S.H. Wang Author-X-Name-First: Cindy S.H. Author-X-Name-Last: Wang Author-Name: Cheng Hsiao Author-X-Name-First: Cheng Author-X-Name-Last: Hsiao Author-Name: Hao-Hsiang Yang Author-X-Name-First: Hao-Hsiang Author-X-Name-Last: Yang Title: Market integration, systemic risk and diagnostic tests in large mixed panels Abstract: This study investigates an AR (autoregressive)-filtered version of several conventional diagnostic tests for cross-sectional dependence in large mixed panels when both N and T are large, including the adjusted Lagrangian Multiplier test (LM), the cross-section dependence test (CD), and the Schott test. We show that conventional tests of cross-sectional dependence based on Pearson correlation coefficients could diverge if the components are not all I(0) processes and the modified tests possess the asymptotical normality property. The distinctive feature of these new tests is their ease of implementation, even though the exact time series properties of each component of a mixed panel are unknown or unobservable in practice. Simulations show that the AR-filtered version of the CD test (CDAR) performs well relative to the other testing procedures in the finite sample and computation time, especially for those cases with a large cross-sectional dimension. Given the good statistical properties of CDAR test, we also propose to use it as an early warning indicator for market risk or crisis. Journal: Econometric Reviews Pages: 750-795 Issue: 8 Volume: 40 Year: 2021 Month: 9 X-DOI: 10.1080/07474938.2021.1889209 File-URL: http://hdl.handle.net/10.1080/07474938.2021.1889209 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:40:y:2021:i:8:p:750-795 Template-Type: ReDIF-Article 1.0 Author-Name: Oliver Linton Author-X-Name-First: Oliver Author-X-Name-Last: Linton Author-Name: Yoon Jae Whang Author-X-Name-First: Yoon Jae Author-X-Name-Last: Whang Author-Name: Yu-Min Yen Author-X-Name-First: Yu-Min Author-X-Name-Last: Yen Title: The lower regression function and testing expectation dependence dominance hypotheses Abstract: We provide an estimator of the lower regression function and provide large sample properties for inference. We also propose a test of the hypothesis of positive expectation dependence and derive its limiting distribution under the null hypothesis and provide consistent critical values. We apply our methodology to the question of portfolio choice and to the question of the relation of growth to public debt. Journal: Econometric Reviews Pages: 709-727 Issue: 8 Volume: 40 Year: 2021 Month: 9 X-DOI: 10.1080/07474938.2021.1889177 File-URL: http://hdl.handle.net/10.1080/07474938.2021.1889177 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:40:y:2021:i:8:p:709-727 Template-Type: ReDIF-Article 1.0 Author-Name: Xun Lu Author-X-Name-First: Xun Author-X-Name-Last: Lu Author-Name: Ke Miao Author-X-Name-First: Ke Author-X-Name-Last: Miao Author-Name: Liangjun Su Author-X-Name-First: Liangjun Author-X-Name-Last: Su Title: Determination of different types of fixed effects in three-dimensional panels* Abstract: In this paper, we propose a jackknife method to determine the type of fixed effects in three-dimensional panel data models. We show that with probability approaching 1, the method can select the correct type of fixed effects in the presence of only weak serial or cross-sectional dependence among the error terms. In the presence of strong serial correlation, we propose a modified jackknife method and justify its selection consistency. Monte Carlo simulations demonstrate the excellent finite sample performance of our method. Applications to two datasets in macroeconomics and international trade reveal the usefulness of our method. Journal: Econometric Reviews Pages: 867-898 Issue: 9 Volume: 40 Year: 2021 Month: 10 X-DOI: 10.1080/07474938.2021.1889176 File-URL: http://hdl.handle.net/10.1080/07474938.2021.1889176 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:40:y:2021:i:9:p:867-898 Template-Type: ReDIF-Article 1.0 Author-Name: Qian Wang Author-X-Name-First: Qian Author-X-Name-Last: Wang Author-Name: Songnian Chen Author-X-Name-First: Songnian Author-X-Name-Last: Chen Title: Moment estimation for censored quantile regression Abstract: In influential articles Powell (Journal of Econometrics 25(3):303–325, 1984; Journal of Econometrics 32(1):143–155, 1986) proposed optimization-based censored least absolute deviations estimator (CLAD) and general censored quantile regression estimator (CQR). It has been recognized, however, that this optimization-based estimator may perform poorly in finite samples (e.g., Khan and Powell, Journal of Econometrics 103(1–2):73–110, 2001; Fitzenberger, Handbook of Statistics. Elsevier, 1996; Fitzenberger and Winker, Computational Statistics & Data Analysis 52(1):88–108, 2007; Koenker, Journal of Statistical Software 27(6), 2008). In this paper we propose a moment-based censored quantile regression estimator (MCQR). While both the CQR and MCQR estimators have the same large sample properties, our simulation results suggest certain advantage of our moment-based estimator (MCQR). In addition, the empirical likelihood methods for the uncensored model (e.g., Whang 2006; Otsu, Journal of Econometrics 142(1):508–538, 2008) can readily be adapted to the censored model within our method of moment estimation framework. When both censoring and endogeneity are present, we develop an instrumental variable censored quantile regression estimator (IVCQR) by combining the insights of Chernozhukov and Hansen’s (Journal of Econometrics 132(2):491–525, 2006; Journal of Econometrics 142(1):379–398, 2008) instrumental variables quantile regression estimator (IVQR) and the MCQR. Simulation results indicate that the IVCQR estimator performs well. Journal: Econometric Reviews Pages: 815-829 Issue: 9 Volume: 40 Year: 2021 Month: 10 X-DOI: 10.1080/07474938.2021.1889207 File-URL: http://hdl.handle.net/10.1080/07474938.2021.1889207 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:40:y:2021:i:9:p:815-829 Template-Type: ReDIF-Article 1.0 Author-Name: Lidan Tan Author-X-Name-First: Lidan Author-X-Name-Last: Tan Author-Name: Khai Xiang Chiong Author-X-Name-First: Khai Xiang Author-X-Name-Last: Chiong Author-Name: Hyungsik Roger Moon Author-X-Name-First: Hyungsik Roger Author-X-Name-Last: Moon Title: Estimation of high-dimensional seemingly unrelated regression models Abstract: In this article, we investigate seemingly unrelated regression (SUR) models that allow the number of equations (N) to be large and comparable to the number of the observations in each equation (T). It is well known that conventional SUR estimators, for example, the feasible generalized least squares estimator from Zellner (1962) does not perform well in a high-dimensional setting. We propose a new feasible GLS estimator called the feasible graphical lasso (FGLasso) estimator. For a feasible implementation of the GLS estimator, we use the graphical lasso estimation of the precision matrix (the inverse of the covariance matrix of the equation system errors) assuming that the underlying unknown precision matrix is sparse. We show that under certain conditions, FGLasso converges uniformly to GLS even when T < N, and it shares the same asymptotic distribution with the efficient GLS estimator when T>N log N. We confirm these results through finite sample Monte-Carlo simulations. Journal: Econometric Reviews Pages: 830-851 Issue: 9 Volume: 40 Year: 2021 Month: 10 X-DOI: 10.1080/07474938.2021.1889195 File-URL: http://hdl.handle.net/10.1080/07474938.2021.1889195 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:40:y:2021:i:9:p:830-851 Template-Type: ReDIF-Article 1.0 Author-Name: Yu Sun Author-X-Name-First: Yu Author-X-Name-Last: Sun Author-Name: Karen X. Yan Author-X-Name-First: Karen X. Author-X-Name-Last: Yan Author-Name: Qi Li Author-X-Name-First: Qi Author-X-Name-Last: Li Title: Estimation of average treatment effect based on a semiparametric propensity score Abstract: This paper considers the estimation of average treatment effect using propensity score method. We propose to use a semiparametric single-index model to estimate the propensity score. This avoids the curse of dimensionality problem with the nonparametric method based propensity score estimator. We establish the asymptotic distribution of the average treatment effect estimator. Monte Carlo simulation results show that the proposed method works well in finite samples and outperforms the conventional nonparametric kernel approach. We apply the proposed method to an empirical data examining the efficacy of right heart catheterization on medical outcomes. Journal: Econometric Reviews Pages: 852-866 Issue: 9 Volume: 40 Year: 2021 Month: 10 X-DOI: 10.1080/07474938.2021.1889206 File-URL: http://hdl.handle.net/10.1080/07474938.2021.1889206 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:40:y:2021:i:9:p:852-866 Template-Type: ReDIF-Article 1.0 Author-Name: Burak Alparslan Eroğlu Author-X-Name-First: Burak Alparslan Author-X-Name-Last: Eroğlu Author-Name: J. Isaac Miller Author-X-Name-First: J. Isaac Author-X-Name-Last: Miller Author-Name: Taner Yiğit Author-X-Name-First: Taner Author-X-Name-Last: Yiğit Title: Time-varying cointegration and the Kalman filter Abstract: We show that time-varying parameter state-space models estimated using the Kalman filter are particularly vulnerable to the problem of spurious regression, because the integrated error is transferred to the estimated state equation. We offer a simple yet effective methodology to reliably recover the instability in cointegrating vectors. In the process, the proposed methodology successfully distinguishes between the cases of no cointegration, fixed cointegration, and time-varying cointegration. We apply these proposed tests to elucidate the relationship between concentrations of greenhouse gases and global temperatures, an important relationship to both climate scientists and economists. Journal: Econometric Reviews Pages: 1-21 Issue: 1 Volume: 41 Year: 2022 Month: 1 X-DOI: 10.1080/07474938.2020.1861776 File-URL: http://hdl.handle.net/10.1080/07474938.2020.1861776 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:1:p:1-21 Template-Type: ReDIF-Article 1.0 Author-Name: Alecos Papadopoulos Author-X-Name-First: Alecos Author-X-Name-Last: Papadopoulos Author-Name: Mike G. Tsionas Author-X-Name-First: Mike G. Author-X-Name-Last: Tsionas Title: Efficiency gains in least squares estimation: A new approach Abstract: In pursuit of efficiency, we propose a new way to construct least squares estimators, as the minimizers of an augmented objective function that takes explicitly into account the variability of the error term and the resulting uncertainty, as well as the possible existence of heteroskedasticity. We initially derive an infeasible estimator which we then approximate using Ordinary Least Squares (OLS) residuals from a first-step regression to obtain the feasible “HOLS” estimator. This estimator has negligible bias, is consistent and outperforms OLS in terms of finite-sample Mean Squared Error, but also in terms of asymptotic efficiency, under all skedastic scenarios, including homoskedasticity. Analogous efficiency gains are obtained for the case of Instrumental Variables estimation. Theoretical results are accompanied by simulations that support them. Journal: Econometric Reviews Pages: 51-74 Issue: 1 Volume: 41 Year: 2022 Month: 1 X-DOI: 10.1080/07474938.2020.1824731 File-URL: http://hdl.handle.net/10.1080/07474938.2020.1824731 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:1:p:51-74 Template-Type: ReDIF-Article 1.0 Author-Name: Tobias Hartl Author-X-Name-First: Tobias Author-X-Name-Last: Hartl Author-Name: Roland Jucknewitz Author-X-Name-First: Roland Author-X-Name-Last: Jucknewitz Title: Approximate state space modelling of unobserved fractional components Abstract: We propose convenient inferential methods for potentially nonstationary multivariate unobserved components models with fractional integration and cointegration. Based on finite-order ARMA approximations in the state space representation, maximum likelihood estimation can make use of the EM algorithm and related techniques. The approximation outperforms the frequently used autoregressive or moving average truncation, both in terms of computational costs and with respect to approximation quality. Monte Carlo simulations reveal good estimation properties of the proposed methods for processes of different complexity and dimension. Journal: Econometric Reviews Pages: 75-98 Issue: 1 Volume: 41 Year: 2022 Month: 1 X-DOI: 10.1080/07474938.2020.1841444 File-URL: http://hdl.handle.net/10.1080/07474938.2020.1841444 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:1:p:75-98 Template-Type: ReDIF-Article 1.0 Author-Name: Yu-Chin Hsu Author-X-Name-First: Yu-Chin Author-X-Name-Last: Hsu Author-Name: Tsung-Chih Lai Author-X-Name-First: Tsung-Chih Author-X-Name-Last: Lai Author-Name: Robert P. Lieli Author-X-Name-First: Robert P. Author-X-Name-Last: Lieli Title: Estimation and inference for distribution and quantile functions in endogenous treatment effect models Abstract: Given a standard endogenous treatment effect model, we propose nonparametric estimation and inference procedures for the distribution and quantile functions of the potential outcomes among compliers, as well as the local quantile treatment effect function. The preliminary distribution function estimator is a weighted average of indicator functions, but is not monotonically increasing in general. We therefore propose a simple monotonizing method for proper distribution function estimation, and obtain the quantile function estimator by inversion. Our monotonizing method is an alternative to Chernozhukov et al. (2010) and is arguably preferable when the outcome has unbounded support. We show that all the estimators converge weakly to Gaussian processes at the parametric rate, and propose a multiplier bootstrap for uniform inference. Our uniform results thus generalize the pointwise theory developed by Frölich and Melly (2013). Monte Carlo simulations and an application to the effect of fertility on family income distribution illustrate the use of the methods. All results extend to the subpopulation of treated compliers as well. Journal: Econometric Reviews Pages: 22-50 Issue: 1 Volume: 41 Year: 2022 Month: 1 X-DOI: 10.1080/07474938.2020.1847479 File-URL: http://hdl.handle.net/10.1080/07474938.2020.1847479 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:1:p:22-50 Template-Type: ReDIF-Article 1.0 Author-Name: Esfandiar Maasoumi Author-X-Name-First: Esfandiar Author-X-Name-Last: Maasoumi Title: Best Paper Award Econometric Reviews, 2017–2018 Journal: Econometric Reviews Pages: 115-115 Issue: 1 Volume: 41 Year: 2022 Month: 1 X-DOI: 10.1080/07474938.2022.2035112 File-URL: http://hdl.handle.net/10.1080/07474938.2022.2035112 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:1:p:115-115 Template-Type: ReDIF-Article 1.0 Author-Name: Collin S. Philipps Author-X-Name-First: Collin S. Author-X-Name-Last: Philipps Title: The MLE of Aigner, Amemiya, and Poirier is not the expectile MLE Abstract: This article compares two asymmetric Gaussian likelihood models and their corresponding estimators. Recently, there has been confusion in the literature regarding these models and (1) whether they are the same, or (2) whether both of them can be used to estimate expectiles. After the comparison, it becomes clear that they are not the same and only one of these models is appropriate for that purpose. The similarity between these models is purely superficial. The historical origin of expectiles has also been disputed: some degree of credit can be shared between two papers. Journal: Econometric Reviews Pages: 99-114 Issue: 1 Volume: 41 Year: 2022 Month: 1 X-DOI: 10.1080/07474938.2021.1899505 File-URL: http://hdl.handle.net/10.1080/07474938.2021.1899505 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:1:p:99-114 Template-Type: ReDIF-Article 1.0 Author-Name: Esfandiar Maasoumi Author-X-Name-First: Esfandiar Author-X-Name-Last: Maasoumi Title: Best Paper Award Econometric Reviews, 2019–2020 Journal: Econometric Reviews Pages: 116-116 Issue: 1 Volume: 41 Year: 2022 Month: 1 X-DOI: 10.1080/07474938.2022.2035113 File-URL: http://hdl.handle.net/10.1080/07474938.2022.2035113 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:1:p:116-116 Template-Type: ReDIF-Article 1.0 Author-Name: Laszlo Balazsi Author-X-Name-First: Laszlo Author-X-Name-Last: Balazsi Author-Name: Felix Chan Author-X-Name-First: Felix Author-X-Name-Last: Chan Author-Name: Laszlo Matyas Author-X-Name-First: Laszlo Author-X-Name-Last: Matyas Title: Event count estimation Abstract: This paper proposes a new estimation procedure called Event Count Estimator (ECE). The estimator is straightforward to implement and is robust against outliers, censoring and ‘excess zeros’ in the data. The paper establishes asymptotic properties of the new estimator and the theoretical results are supported by several Monte Carlo experiments. Monte Carlo experiments also show that the estimator has reasonable properties in moderate to large samples. As such, the cost of trading efficiency for robustness here is negligible from an applied viewpoint. The practical usefulness of the new estimator is demonstrated via an empirical application of the Gravity Model of trade. Journal: Econometric Reviews Pages: 147-176 Issue: 2 Volume: 41 Year: 2022 Month: 2 X-DOI: 10.1080/07474938.2020.1862505 File-URL: http://hdl.handle.net/10.1080/07474938.2020.1862505 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:2:p:147-176 Template-Type: ReDIF-Article 1.0 Author-Name: Marta Regis Author-X-Name-First: Marta Author-X-Name-Last: Regis Author-Name: Paulo Serra Author-X-Name-First: Paulo Author-X-Name-Last: Serra Author-Name: Edwin R. van den Heuvel Author-X-Name-First: Edwin R. Author-X-Name-Last: van den Heuvel Title: Random autoregressive models: A structured overview Abstract: Models characterized by autoregressive structure and random coefficients are powerful tools for the analysis of high-frequency, high-dimensional and volatile time series. The available literature on such models is broad, but also sector-specific, overlapping, and confusing. Most models focus on one property of the data, while much can be gained by combining the strength of various models and their sources of heterogeneity. We present a structured overview of the literature on autoregressive models with random coefficients. We describe hierarchy and analogies among models, and for each we systematically list properties, estimation methods, tests, software packages and typical applications. Journal: Econometric Reviews Pages: 207-230 Issue: 2 Volume: 41 Year: 2022 Month: 2 X-DOI: 10.1080/07474938.2021.1899504 File-URL: http://hdl.handle.net/10.1080/07474938.2021.1899504 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:2:p:207-230 Template-Type: ReDIF-Article 1.0 Author-Name: Kyoo il Kim Author-X-Name-First: Kyoo il Author-X-Name-Last: Kim Title: Semiparametric estimation of signaling games with equilibrium refinement Abstract: We study an econometric modeling of a signaling game where one informed player may have multiple types. For this game, the problem of multiple equilibria arises and we achieve the uniqueness of equilibrium using an equilibrium refinement, which enables us to identify the model parameters. We then develop an estimation strategy that identifies the payoffs structure and the distribution of types from the observed actions. In this game, the type distribution is nonparametrically specified and we estimate the model using a sieve conditional MLE. We achieve the consistency and the asymptotic normality for the structural parameter estimates. Journal: Econometric Reviews Pages: 231-267 Issue: 2 Volume: 41 Year: 2022 Month: 2 X-DOI: 10.1080/07474938.2021.1899506 File-URL: http://hdl.handle.net/10.1080/07474938.2021.1899506 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:2:p:231-267 Template-Type: ReDIF-Article 1.0 Author-Name: Yixiao Sun Author-X-Name-First: Yixiao Author-X-Name-Last: Sun Author-Name: Xuexin Wang Author-X-Name-First: Xuexin Author-X-Name-Last: Wang Title: An asymptotically F-distributed Chow test in the presence of heteroscedasticity and autocorrelation Abstract: This study proposes a simple, trustworthy Chow test in the presence of heteroscedasticity and autocorrelation. The test is based on a series heteroscedasticity and autocorrelation robust variance estimator with judiciously crafted basis functions. Like the Chow test in a classical normal linear regression, the proposed test employs the standard F distribution as the reference distribution, which is justified under fixed-smoothing asymptotics. Monte Carlo simulations show that the null rejection probability of the asymptotic F test is closer to the nominal level than that of the chi-square test. Journal: Econometric Reviews Pages: 177-206 Issue: 2 Volume: 41 Year: 2022 Month: 2 X-DOI: 10.1080/07474938.2021.1874703 File-URL: http://hdl.handle.net/10.1080/07474938.2021.1874703 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:2:p:177-206 Template-Type: ReDIF-Article 1.0 Author-Name: Hugo Kruiniger Author-X-Name-First: Hugo Author-X-Name-Last: Kruiniger Title: Estimation of dynamic panel data models with a lot of heterogeneity Abstract: The commonly used 1-step and 2-step System GMM estimators for the panel AR(1) model are inconsistent under mean stationarity when the ratio of the variance of the individual effects to the variance of the idiosyncratic errors is unbounded when N→∞. The reason for their inconsistency is that their weight matrices select moment conditions that do not identify the autoregressive parameter. This paper proposes a new 2-step System estimator that is still consistent in this case provided that T>3. Unlike the commonly used 2-step System estimator, the new estimator uses an estimator of the optimal weight matrix that remains consistent in this case. We also show that the commonly used 1-step and 2-step Arellano-Bond GMM estimators and the Random Effects Quasi MLE remain consistent under the same conditions. To illustrate the usefulness of our new System estimator we revisit the growth study of Levine et al. (2000). Journal: Econometric Reviews Pages: 117-146 Issue: 2 Volume: 41 Year: 2022 Month: 2 X-DOI: 10.1080/07474938.2021.1899507 File-URL: http://hdl.handle.net/10.1080/07474938.2021.1899507 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:2:p:117-146 Template-Type: ReDIF-Article 1.0 Author-Name: Hande Karabiyik Author-X-Name-First: Hande Author-X-Name-Last: Karabiyik Author-Name: Joakim Westerlund Author-X-Name-First: Joakim Author-X-Name-Last: Westerlund Author-Name: Paresh Narayan Author-X-Name-First: Paresh Author-X-Name-Last: Narayan Title: Panel data measures of price discovery Abstract: This paper considers disaggregated price data that are observed not only for multiple markets over extended periods of time, but also for a large number of assets. The previous literature has argued that in such data rich environments, which arise frequently in applied work, the analysis of price discovery can be made more precise by accounting for the panel structure of the data. Moreover, since the individual assets are not that interesting anyways, little is lost by taking the overall panel perspective. These arguments are, however, mainly based on empirical observations, and there is little in terms of econometric support. The purpose of the present study is to fill this gap in the literature. This is done by offering a full-blown econometric analysis of panel analogs of the information share and permanent–transitory measures of price discovery, which are the workhorses of the time series literature. Both measures are shown to be consistent and they support standard normal inference, which is in contrast to the time series case, where such inference is only possible for the permanent–transitory measure. Journal: Econometric Reviews Pages: 269-290 Issue: 3 Volume: 41 Year: 2022 Month: 5 X-DOI: 10.1080/07474938.2021.1912973 File-URL: http://hdl.handle.net/10.1080/07474938.2021.1912973 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:3:p:269-290 Template-Type: ReDIF-Article 1.0 Author-Name: Daniel J. Henderson Author-X-Name-First: Daniel J. Author-X-Name-Last: Henderson Author-Name: Alexandra Soberon Author-X-Name-First: Alexandra Author-X-Name-Last: Soberon Author-Name: Juan M. Rodriguez-Poo Author-X-Name-First: Juan M. Author-X-Name-Last: Rodriguez-Poo Title: Nonparametric multidimensional fixed effects panel data models Abstract: Multidimensional panel datasets are routinely employed to identify marginal effects in empirical research. Fixed effects estimators are typically used to deal with potential correlation between unobserved effects and regressors. Nonparametric estimators for one-way fixed effects models exist, but are cumbersome to employ in practice as they typically require iteration, marginal integration or profile estimation. We develop a nonparametric estimator that works for essentially any dimension fixed effects model, has a closed form solution and can be estimated in a single step. A cross-validation bandwidth selection procedure is proposed and asymptotic properties (for either a fixed or large time dimension) are given. Finite sample properties are shown via simulations, as well as with an empirical application, which further extends our model to the partially linear setting. Journal: Econometric Reviews Pages: 321-358 Issue: 3 Volume: 41 Year: 2022 Month: 5 X-DOI: 10.1080/07474938.2021.1957283 File-URL: http://hdl.handle.net/10.1080/07474938.2021.1957283 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:3:p:321-358 Template-Type: ReDIF-Article 1.0 Author-Name: Minyu Han Author-X-Name-First: Minyu Author-X-Name-Last: Han Author-Name: Jihun Kwak Author-X-Name-First: Jihun Author-X-Name-Last: Kwak Author-Name: Donggyu Sul Author-X-Name-First: Donggyu Author-X-Name-Last: Sul Title: Two-way fixed effects versus panel factor-augmented estimators: asymptotic comparison among pretesting procedures Abstract: Empirical researchers may wonder whether or not a two-way fixed effects estimator (with individual and period fixed effects) is sufficiently sophisticated to isolate the influence of common shocks on the estimation of slope coefficients. If it is not, practitioners need to run the so-called panel factor augmented regression instead. There are two pretesting procedures available in the literature: the use of the estimated number of factors and the direct test of estimated factor loading coefficients. This article compares the two pretesting methods asymptotically. Under the presence of the heterogeneous factor loadings, both pretesting procedures suggest using the common correlated effects (CCE) estimator. Meanwhile, when factor loadings are homogeneous, the pretesting method utilizing the estimated number of factors always suggests more efficient estimation methods. By comparing asymptotic variances, this article finds that when the slope coefficients are homogeneous with homogeneous factor loadings, the two-way fixed effects estimation is more efficient than the CCE estimation. However, when the slope coefficients are heterogeneous with homogeneous factor loadings, the CCE estimation is, surprisingly, more efficient than the two-way fixed effects estimation. By means of Monte Carlo simulations, we verify the asymptotic claims. We demonstrate how to use the two pretesting methods through the use of an empirical example. Journal: Econometric Reviews Pages: 291-320 Issue: 3 Volume: 41 Year: 2022 Month: 5 X-DOI: 10.1080/07474938.2021.1957282 File-URL: http://hdl.handle.net/10.1080/07474938.2021.1957282 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:3:p:291-320 Template-Type: ReDIF-Article 1.0 Author-Name: Giacomo Benini Author-X-Name-First: Giacomo Author-X-Name-Last: Benini Author-Name: Stefan Sperlich Author-X-Name-First: Stefan Author-X-Name-Last: Sperlich Title: Modeling heterogeneous treatment effects in the presence of endogeneity Abstract: An inappropriate handling of cross-sectional heterogeneity renders estimates of causal effects inaccurate and uninformative. The present paper discusses how the direct modeling of cross-sectional differences via semiparametric models represents a useful bridge between a statistical approach, where the conditional distribution of the dependent variable returns any value of the outcome given any value of the explanatory variables, and an econometric analysis, where functions and parameters have direct policy implications. The explicit modeling of heterogeneity across different groups improves the quality of the estimates, mitigates their dependence upon the chosen instrumental variable, diminishes the self-selection problem, and fosters the acquisition of useful information for the entire sample. Journal: Econometric Reviews Pages: 359-372 Issue: 3 Volume: 41 Year: 2022 Month: 5 X-DOI: 10.1080/07474938.2021.1927548 File-URL: http://hdl.handle.net/10.1080/07474938.2021.1927548 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:3:p:359-372 Template-Type: ReDIF-Article 1.0 Author-Name: Kyoo il Kim Author-X-Name-First: Kyoo il Author-X-Name-Last: Kim Author-Name: Suyong Song Author-X-Name-First: Suyong Author-X-Name-Last: Song Title: Control variables approach to estimate semiparametric models of mismeasured endogenous regressors with an application to U.K. twin data Abstract: We study the identification and estimation of semiparametric models with mismeasured endogenous regressors using control variables that ensure the conditional covariance restriction on endogenous regressors and unobserved causes. We provide a set of sufficient conditions for identification, which control for both endogeneity and measurement error. We propose a sieve-based estimator and derive its asymptotic properties. Given the sieve approximation, our proposed estimator is easy to implement as weighted least squares. Monte Carlo simulations illustrate that our proposed estimator performs well in the finite samples. In an empirical application, we estimate the return to education on earnings using U.K. twin data, in which self-reported education is potentially measured with error and is also correlated with unobserved factors. Our approach utilizes the twin’s reported education as a control variable to obtain consistent estimates. We find that a one-year increase in education leads to an 11% increase in hourly wage. The estimate is significantly higher than those from OLS and IV approaches which are potentially biased. The application underscores that our proposed estimator is useful to correct for both endogeneity and measurement error in estimating returns to education. Journal: Econometric Reviews Pages: 448-483 Issue: 4 Volume: 41 Year: 2022 Month: 4 X-DOI: 10.1080/07474938.2021.1960752 File-URL: http://hdl.handle.net/10.1080/07474938.2021.1960752 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:4:p:448-483 Template-Type: ReDIF-Article 1.0 Author-Name: Yingyao Hu Author-X-Name-First: Yingyao Author-X-Name-Last: Hu Author-Name: Ji-Liang Shiu Author-X-Name-First: Ji-Liang Author-X-Name-Last: Shiu Title: A simple test of completeness in a class of nonparametric specification Abstract: This paper provides a test for completeness in a class of nonparametric specification with an additive and independent error term. It is known that such a nonparametric location family of functions is complete if and only if the characteristic function of the error term has no zeros on the real line. Because a zero of the error characteristic function implies that of an observed marginal distribution, we propose a simple test for zeros of characteristic function of the observed distribution, in which rejection of the null hypothesis implies the completeness. This test is applicable to many popular settings, such as nonparametric regression models with instrumental variables, and nonclassical measurement error models. We describe the asymptotic behavior of the tests under the null and alternative hypotheses and investigate the finite sample properties of the proposed test through a Monte Carlo study. We illustrate our method empirically by estimating a measurement error model using the CPS/SSR 1978 exact match file. Journal: Econometric Reviews Pages: 373-399 Issue: 4 Volume: 41 Year: 2022 Month: 4 X-DOI: 10.1080/07474938.2021.1957285 File-URL: http://hdl.handle.net/10.1080/07474938.2021.1957285 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:4:p:373-399 Template-Type: ReDIF-Article 1.0 Author-Name: Pavel Čížek Author-X-Name-First: Pavel Author-X-Name-Last: Čížek Author-Name: Chao Hui Koo Author-X-Name-First: Chao Hui Author-X-Name-Last: Koo Title: Semiparametric transition models Abstract: A new semiparametric time series model is introduced – the semiparametric transition (SETR) model – that generalizes the threshold and smooth transition models by letting the transition function to be of an unknown form. Estimation is based on a combination of the (local) least squares estimations of the transition function and regression parameters. The asymptotic behavior for the regression coefficient estimator of the SETR model is established, including its oracle property. Monte Carlo simulations demonstrate that the proposed estimator is more robust to the form of the transition function than parametric threshold and smooth transition methods and more precise than varying coefficient estimators. Journal: Econometric Reviews Pages: 400-415 Issue: 4 Volume: 41 Year: 2022 Month: 4 X-DOI: 10.1080/07474938.2021.1957281 File-URL: http://hdl.handle.net/10.1080/07474938.2021.1957281 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:4:p:400-415 Template-Type: ReDIF-Article 1.0 Author-Name: Alexander Chudik Author-X-Name-First: Alexander Author-X-Name-Last: Chudik Author-Name: M. Hashem Pesaran Author-X-Name-First: M. Hashem Author-X-Name-Last: Pesaran Title: An augmented Anderson–Hsiao estimator for dynamic short-T panels† Abstract: This article introduces the idea of self-instrumenting endogenous regressors in settings when the correlation between these regressors and the errors can be derived and used to bias-correct the moment conditions. The resulting bias-corrected moment conditions are less likely to be subject to the weak instrument problem and can be used on their own or in conjunction with other available moment conditions to obtain more efficient estimators. This approach can be applied to estimation of a variety of models such as spatial and dynamic panel data models. This article focuses on the latter, and proposes a new estimator for short T dynamic panels by augmenting Anderson and Hsiao (AAH) estimator with bias-corrected quadratic moment conditions in first differences which substantially improve the small sample performance of the AH estimator without sacrificing the generality of its underlying assumptions regarding the fixed effects, initial values, and heteroskedasticity of error terms. Using Monte-Carlo experiments it is shown that AAH estimator represents a substantial improvement over the AH estimator and more importantly it performs well even when compared to Arellano and Bond and Blundell and Bond (BB) estimators that are based on more restrictive assumptions, and continues to have satisfactory performance in cases where the standard GMM estimators are inconsistent. Finally, to decide between AAH and BB estimators we also propose a Hausman type test which is shown to work well when T is small and n sufficiently large. Journal: Econometric Reviews Pages: 416-447 Issue: 4 Volume: 41 Year: 2022 Month: 4 X-DOI: 10.1080/07474938.2021.1971388 File-URL: http://hdl.handle.net/10.1080/07474938.2021.1971388 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:4:p:416-447 Template-Type: ReDIF-Article 1.0 Author-Name: Paul Bekker Author-X-Name-First: Paul Author-X-Name-Last: Bekker Author-Name: Joëlle van Essen Author-X-Name-First: Joëlle Author-X-Name-Last: van Essen Title: ML and GMM with concentrated instruments in the static panel data model Abstract: We study the asymptotic behavior of instrumental variable estimators in the static panel model under many-instruments asymptotics. We provide new estimators and standard errors based on concentrated instruments as alternatives to an estimator based on maximum likelihood. We prove that the latter estimator is consistent under many-instruments asymptotics only if the starting value in an iterative procedure is root-N consistent. A similar approach for continuous updating GMM shows the derivation is nontrivial. For the standard cross-sectional case (T = 1), the simple formulation of standard errors offer an alternative to earlier formulations. Journal: Econometric Reviews Pages: 181-195 Issue: 2 Volume: 39 Year: 2019 Month: 12 X-DOI: 10.1080/07474938.2019.1580946 File-URL: http://hdl.handle.net/10.1080/07474938.2019.1580946 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2019:i:2:p:181-195 Template-Type: ReDIF-Article 1.0 Author-Name: Zhengyu Zhang Author-X-Name-First: Zhengyu Author-X-Name-Last: Zhang Author-Name: Zequn Jin Author-X-Name-First: Zequn Author-X-Name-Last: Jin Title: Identification and estimation in a linear correlated random coefficients model with censoring Abstract: In this paper, we study the identification and estimation of a linear correlated random coefficients model with censoring, namely, Y=max{B0+X′B,C}, where C is a known constant or an unknown function of regressors. Here, random coefficients (B0,B) can be correlated with one or more components of X. Under a generalized conditional median restriction similar to that in Hoderlein and Sherman, we show that both the average partial effect and the average partial effect on the treated are identified. We develop estimators for the identified parameters and analyze their large sample properties. A Monte Carlo simulation indicates that our estimators perform reasonably well with small samples. We then present an application. Journal: Econometric Reviews Pages: 196-213 Issue: 2 Volume: 39 Year: 2019 Month: 12 X-DOI: 10.1080/07474938.2019.1580949 File-URL: http://hdl.handle.net/10.1080/07474938.2019.1580949 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2019:i:2:p:196-213 Template-Type: ReDIF-Article 1.0 Author-Name: Laura Magazzini Author-X-Name-First: Laura Author-X-Name-Last: Magazzini Author-Name: Giorgio Calzolari Author-X-Name-First: Giorgio Author-X-Name-Last: Calzolari Title: Testing initial conditions in dynamic panel data models Abstract: We propose a new framework for testing the “mean stationarity” assumption in dynamic panel data models, required for the consistency of the system GMM estimator. In our set up the assumption is obtained as a parametric restriction in an extended set of moment conditions, allowing the use of a LM test to check its validity. Our framework provides a ranking in terms of power of the analyzed test statistics, in which our approach exhibits better power than the difference-in-Sargan/Hansen test that compares system GMM and difference GMM, that is, on its turn, more powerful than the Sargan/Hansen test based on the system GMM moment conditions. Journal: Econometric Reviews Pages: 115-134 Issue: 2 Volume: 39 Year: 2019 Month: 12 X-DOI: 10.1080/07474938.2019.1690194 File-URL: http://hdl.handle.net/10.1080/07474938.2019.1690194 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2019:i:2:p:115-134 Template-Type: ReDIF-Article 1.0 Author-Name: Michael S. Delgado Author-X-Name-First: Michael S. Author-X-Name-Last: Delgado Author-Name: Deniz Ozabaci Author-X-Name-First: Deniz Author-X-Name-Last: Ozabaci Author-Name: Yiguo Sun Author-X-Name-First: Yiguo Author-X-Name-Last: Sun Author-Name: Subal C. Kumbhakar Author-X-Name-First: Subal C. Author-X-Name-Last: Kumbhakar Title: Smooth coefficient models with endogenous environmental variables Abstract: We develop a three-step, oracle-efficient estimator for a structural semiparametric smooth coefficient model with endogenous variables in the nonparametric part of the model. We use a control function approach, combined with both series and kernel estimators to obtain consistent and asymptotically normal estimators of the functions and their partial derivatives. We develop a residual-based test statistic for testing endogeneity, and demonstrate the finite sample performance of our estimators, as well as our test, via Monte Carlo simulations. Finally, we develop an application of our estimator to the relationship between public benefits and private savings. Journal: Econometric Reviews Pages: 158-180 Issue: 2 Volume: 39 Year: 2019 Month: 12 X-DOI: 10.1080/07474938.2018.1552413 File-URL: http://hdl.handle.net/10.1080/07474938.2018.1552413 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2019:i:2:p:158-180 Template-Type: ReDIF-Article 1.0 Author-Name: Hervé Cardot Author-X-Name-First: Hervé Author-X-Name-Last: Cardot Author-Name: Antonio Musolesi Author-X-Name-First: Antonio Author-X-Name-Last: Musolesi Title: Modeling temporal treatment effects with zero inflated semi-parametric regression models: The case of local development policies in France Abstract: A semi-parametric approach is proposed to estimate the variation along time of the effects of two distinct public policies that were devoted to boost rural development in France over a similar period of time. At a micro data level, it is often observed that the dependent variable, such as local employment, does not vary along time, so that we face a kind of zero inflated phenomenon that cannot be dealt with a continuous response model. We introduce a conditional mixture model which combines a mass at zero and a continuous response. The suggested zero inflated semi-parametric statistical approach relies on the flexibility and modularity of additive models with the ability of panel data to deal with selection bias and to allow for the estimation of dynamic treatment effects. In this multiple treatment analysis, we find evidence of interesting patterns of temporal treatment effects with relevant nonlinear policy effects. The adopted semi-parametric modeling also offers the possibility of making a counterfactual analysis at an individual level. The methodology is illustrated and compared with parametric linear approaches on a few municipalities for which the mean evolution of the potential outcomes is estimated under the different possible treatments. Journal: Econometric Reviews Pages: 135-157 Issue: 2 Volume: 39 Year: 2019 Month: 12 X-DOI: 10.1080/07474938.2019.1690193 File-URL: http://hdl.handle.net/10.1080/07474938.2019.1690193 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:39:y:2019:i:2:p:135-157 Template-Type: ReDIF-Article 1.0 Author-Name: Natalia Bailey Author-X-Name-First: Natalia Author-X-Name-Last: Bailey Author-Name: Dandan Jiang Author-X-Name-First: Dandan Author-X-Name-Last: Jiang Author-Name: Jianfeng Yao Author-X-Name-First: Jianfeng Author-X-Name-Last: Yao Title: A RMT-based LM test for error cross-sectional independence in large heterogeneous panel data models* Abstract: This paper introduces a new test for error cross-sectional independence in large panel data models with exogenous regressors having heterogenous slope coefficients. The proposed statistic, LMRMT, is based on the Lagrange Multiplier (LM) principle and the sample correlation matrix R^N of the model’s residuals. Since in large panels R^N poorly estimates its population counterpart, results from Random Matrix Theory (RMT) are used to establish the high-dimensional limiting distribution of LMRMT under heteroskedastic normal errors and assuming that both the panel size N and the sample size T grow to infinity in comparable magnitude. Simulation results show that LMRMT is largely correctly sized (except for some small values of N and T). Further, the empirical size and power outcomes show robustness of our statistic to deviations from the assumptions of normality for the error terms and of strict exogeneity for the regressors. The test has comparable small sample properties to related tests in the literature which have been developed under different asymptotic theory. Journal: Econometric Reviews Pages: 564-582 Issue: 5 Volume: 41 Year: 2022 Month: 6 X-DOI: 10.1080/07474938.2021.2009705 File-URL: http://hdl.handle.net/10.1080/07474938.2021.2009705 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:5:p:564-582 Template-Type: ReDIF-Article 1.0 Author-Name: Amaresh K. Tiwari Author-X-Name-First: Amaresh K. Author-X-Name-Last: Tiwari Title: A control function approach to estimate panel data binary response model Abstract: We propose a new control function (CF) method to estimate a binary response model in a triangular system with multiple unobserved heterogeneities The CFs are the expected values of the heterogeneity terms in the reduced form equations conditional on the histories of the endogenous and the exogenous variables. The method requires weaker restrictions compared to CF methods with similar imposed structures. If the support of endogenous regressors is large, average partial effects are point-identified even when instruments are discrete. Bounds are provided when the support assumption is violated. An application and Monte Carlo experiments compare several alternative methods with ours. Journal: Econometric Reviews Pages: 505-538 Issue: 5 Volume: 41 Year: 2022 Month: 6 X-DOI: 10.1080/07474938.2021.1983328 File-URL: http://hdl.handle.net/10.1080/07474938.2021.1983328 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:5:p:505-538 Template-Type: ReDIF-Article 1.0 Author-Name: Kien C. Tran Author-X-Name-First: Kien C. Author-X-Name-Last: Tran Author-Name: Mike G. Tsionas Author-X-Name-First: Mike G. Author-X-Name-Last: Tsionas Title: Efficient semiparametric copula estimation of regression models with endogeneity Abstract: An efficient sieve maximum likelihood estimation procedure for regression models with endogenous regressors using a copula-based approach is proposed. Specifically, the joint distribution of the endogenous regressor and the error term is characterized by a parametric copula function evaluated at the nonparametric marginal distributions. The asymptotic properties of the proposed estimator are derived, including semiparametrically efficient property. Monte Carlo simulations reveal that the proposed method performs well in finite samples comparing to other existing methods. An empirical application is presented to demonstrate the usefulness of the proposed approach. Journal: Econometric Reviews Pages: 485-504 Issue: 5 Volume: 41 Year: 2022 Month: 6 X-DOI: 10.1080/07474938.2021.1957284 File-URL: http://hdl.handle.net/10.1080/07474938.2021.1957284 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:5:p:485-504 Template-Type: ReDIF-Article 1.0 Author-Name: Siyang Peng Author-X-Name-First: Siyang Author-X-Name-Last: Peng Author-Name: Shaojun Guo Author-X-Name-First: Shaojun Author-X-Name-Last: Guo Author-Name: Yonghong Long Author-X-Name-First: Yonghong Author-X-Name-Last: Long Title: Large dimensional portfolio allocation based on a mixed frequency dynamic factor model Abstract: In this paper, we propose a mixed-frequency dynamic factor model (MFDFM) taking into account the high-frequency variation and low-frequency variation at the same time. The factor loadings in our model are affected by the past quadratic variation of factor returns, while the process of the factor quadratic variation is under a mixed-frequency framework (DCC-RV). By combing the variations from the high-frequency and low-frequency domain, our approach exhibits a better estimation and forecast of the assets covariance matrix. Our empirical study compares our MFDFM model with the sample realized covariance matrix and the traditional factor model with intraday returns or daily returns. The results of the empirical study indicate that our proposed model indeed outperforms other models in the sense that the Markowitz’s portfolios based on the MFDFM have a better performance. Journal: Econometric Reviews Pages: 539-563 Issue: 5 Volume: 41 Year: 2022 Month: 6 X-DOI: 10.1080/07474938.2021.1983327 File-URL: http://hdl.handle.net/10.1080/07474938.2021.1983327 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:5:p:539-563 Template-Type: ReDIF-Article 1.0 Author-Name: Stan Hurn Author-X-Name-First: Stan Author-X-Name-Last: Hurn Author-Name: Vance L. Martin Author-X-Name-First: Vance L. Author-X-Name-Last: Martin Author-Name: Lina Xu Author-X-Name-First: Lina Author-X-Name-Last: Xu Title: Specification tests for univariate diffusions Abstract: A new class of specification tests for stochastic differential equations (SDE) is proposed to determine whether the probability integral transform of the estimated model generates an independent and identically distributed uniform random variable. The tests are based on Neyman’s smooth test, appropriately adjusted to correct for both the size distortion arising from having to estimate the unknown parameters of the SDE and possible dependence in the uniform random variable. The suite of tests is compared against other commonly used specification tests for SDEs. The finite sample properties of the tests are investigated using a range of Monte Carlo experiments. The tests are then applied to testing the specification of SDEs used to model the spot interest rate and financial asset volatility. Journal: Econometric Reviews Pages: 607-632 Issue: 6 Volume: 41 Year: 2022 Month: 7 X-DOI: 10.1080/07474938.2021.1995683 File-URL: http://hdl.handle.net/10.1080/07474938.2021.1995683 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:6:p:607-632 Template-Type: ReDIF-Article 1.0 Author-Name: Francesco Bravo Author-X-Name-First: Francesco Author-X-Name-Last: Bravo Title: Second order expansions of estimators in nonparametric moment conditions models with weakly dependent data Abstract: This paper considers estimation of nonparametric moment conditions models with weakly dependent data. The estimator is based on a local linear version of the generalized empirical likelihood approach, and is an alternative to the popular local linear generalized method of moment estimator. The paper derives uniform convergence rates and pointwise asymptotic normality of the resulting local linear generalized empirical likelihood estimator. The paper also develops second order stochastic expansions (under a standard undersmoothing condition) that explain the better finite sample performance of the local linear generalized empirical likelihood estimator compared to that of the efficient local linear generalized method of moments estimator, and can be used to obtain (second order) bias corrected estimators. Monte Carlo simulations and an empirical application illustrate the competitive finite sample properties and the usefulness of the proposed estimators and second order bias corrections. Journal: Econometric Reviews Pages: 583-606 Issue: 6 Volume: 41 Year: 2022 Month: 7 X-DOI: 10.1080/07474938.2021.1991140 File-URL: http://hdl.handle.net/10.1080/07474938.2021.1991140 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:6:p:583-606 Template-Type: ReDIF-Article 1.0 Author-Name: Dalia Ghanem Author-X-Name-First: Dalia Author-X-Name-Last: Ghanem Title: A James-Stein-type adjustment to bias correction in fixed effects panel models Abstract: This paper proposes a James-Stein-type (JS) adjustment to analytical bias correction in fixed effects panel models that suffer from the incidental parameters problem. We provide high-level conditions under which the infeasible JS adjustment leads to a higher-order MSE improvement over the bias-corrected estimator, and the former is asymptotically equivalent to the latter. To obtain a feasible JS adjustment, we propose a nonparametric bootstrap procedure to estimate the JS weighting matrix and provide conditions for its consistency. We apply the JS adjustment to two models: (1) the linear autoregressive model with fixed effects, (2) the nonlinear static fixed effects model. For each application, we employ Monte Carlo simulations which confirm the theoretical results and illustrate the finite-sample improvements due to the JS adjustment. Finally, the extension of the JS procedure to a more general class of models and other policy parameters are illustrated. Journal: Econometric Reviews Pages: 633-651 Issue: 6 Volume: 41 Year: 2022 Month: 7 X-DOI: 10.1080/07474938.2021.1996994 File-URL: http://hdl.handle.net/10.1080/07474938.2021.1996994 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:6:p:633-651 Template-Type: ReDIF-Article 1.0 Author-Name: Fei Jin Author-X-Name-First: Fei Author-X-Name-Last: Jin Author-Name: Yuqin Wang Author-X-Name-First: Yuqin Author-X-Name-Last: Wang Title: GMM estimation of a spatial autoregressive model with autoregressive disturbances and endogenous regressors Abstract: This paper considers the generalized method of moments (GMM) estimation of a spatial autoregressive (SAR) model with SAR disturbances, where we allow for endogenous regressors in addition to a spatial lag of the dependent variable. We do not assume any reduced form of the endogenous regressors, thus we allow for spatial dependence and heterogeneity in endogenous regressors, and allow for nonlinear relations between endogenous regressors and their instruments. Innovations in the model can be homoscedastic or heteroskedastic with unknown forms. We prove that GMM estimators with linear and quadratic moments are consistent and asymptotically normal. In the homoscedastic case, we derive the best linear and quadratic moments that can generate an optimal GMM estimator with the minimum asymptotic variance. Journal: Econometric Reviews Pages: 652-674 Issue: 6 Volume: 41 Year: 2022 Month: 7 X-DOI: 10.1080/07474938.2021.2002521 File-URL: http://hdl.handle.net/10.1080/07474938.2021.2002521 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:6:p:652-674 Template-Type: ReDIF-Article 1.0 # input file: catalog-resolver5897852068298930950.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220713T202513 git hash: 99d3863004 Author-Name: Erik Meijer Author-X-Name-First: Erik Author-X-Name-Last: Meijer Author-Name: Laura Spierdijk Author-X-Name-First: Laura Author-X-Name-Last: Spierdijk Author-Name: Tom Wansbeek Author-X-Name-First: Tom Author-X-Name-Last: Wansbeek Title: Moment conditions for the quadratic regression model with measurement error Abstract: We consider a new estimator for the quadratic errors-in-variables model that exploits higher-order moment conditions under the assumption that the distribution of the measurement error is symmetric and free of excess kurtosis. Our approach contributes to the literature by not requiring any side information and by straightforwardly allowing for one or more error-free control variables. We propose a Wald-type statistical test, based on an auxiliary method-of-moments estimator, to verify a necessary condition for our estimator’s consistency. We derive the asymptotic properties of the estimator and the statistical test and illustrate their finite-sample properties by means of a simulation study and an empirical application to existing data from the literature. Our simulations show that the method-of-moments estimator performs well in terms of bias and variance and even exhibits a certain degree of robustness to the distributional assumptions about the measurement error. In the simulation experiments where such robustness is not present, our statistical test already has high power for relatively small samples. Journal: Econometric Reviews Pages: 749-774 Issue: 7 Volume: 41 Year: 2022 Month: 8 X-DOI: 10.1080/07474938.2022.2052666 File-URL: http://hdl.handle.net/10.1080/07474938.2022.2052666 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:7:p:749-774 Template-Type: ReDIF-Article 1.0 # input file: catalog-resolver7011080076405554254.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220713T202513 git hash: 99d3863004 Author-Name: Ye Yang Author-X-Name-First: Ye Author-X-Name-Last: Yang Title: Unified M-estimation of matrix exponential spatial dynamic panel specification Abstract: In this paper, a unified M-estimation method in Yang (2018) is extended to the matrix exponential spatial dynamic panel specification (MESDPS) with fixed effects in short panels. Similar to the STLE model which includes the spatial lag effect, the space-time effect and the spatial error effect in Yang (2018), the quasi-maximum likelihood (QML) estimation for MESDPS also has the initial condition specification problem. The initial-condition free M-estimator in this paper solves this problem and is proved to be consistent and asymptotically normal. An outer product of martingale difference (OPMD) estimator for the variance-covariance (VC) matrix of the M-estimator is also derived and proved to be consistent. The finite sample property of the M-estimator is studied through an extensive Monte Carlo study. The method is applied to US outward FDI data to show its validity. Journal: Econometric Reviews Pages: 729-748 Issue: 7 Volume: 41 Year: 2022 Month: 8 X-DOI: 10.1080/07474938.2022.2039494 File-URL: http://hdl.handle.net/10.1080/07474938.2022.2039494 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:7:p:729-748 Template-Type: ReDIF-Article 1.0 # input file: catalog-resolver2954190192561525714.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220713T202513 git hash: 99d3863004 Author-Name: Shuo Li Author-X-Name-First: Shuo Author-X-Name-Last: Li Author-Name: Liuhua Peng Author-X-Name-First: Liuhua Author-X-Name-Last: Peng Author-Name: Yundong Tu Author-X-Name-First: Yundong Author-X-Name-Last: Tu Title: Testing independence between exogenous variables and unobserved errors Abstract: Although the exogeneity condition is usually used in many econometric models to identify parameters, the stronger restriction that the error term is independent of a vector of exogenous variables might lead to theoretical benefits. In this paper, we develop a unified methodology for testing the independence assumption. Our methodology can deal with a wide class of parametric models and allows for endogeneity and instrumental variables. In the first-step development, we construct tests that are continuous functionals of the estimated difference of the joint distribution and the product marginal distributions. Next, to remedy the dimensionality issue that arises when the dimension of the exogenous random vector is large, we propose a multiple testing approach which combines marginal p-values obtained by employing the original tests to test independence between the error term and each exogenous variable, while taking full account of the multiplicity nature of the testing problem. We obtain null limiting distributions of our tests, establish the testing consistency, and justify the sensitivity to n−1/2-local alternatives, with n the sample size. The multiplier bootstrap is employed to estimate the critical values. Our methodology is illustrated in the linear regression, the instrumental variables regression, and the nonlinear quantile regression. Our tests are found to perform well in simulations and are demonstrated via an empirical example. Journal: Econometric Reviews Pages: 697-728 Issue: 7 Volume: 41 Year: 2022 Month: 8 X-DOI: 10.1080/07474938.2022.2039493 File-URL: http://hdl.handle.net/10.1080/07474938.2022.2039493 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:7:p:697-728 Template-Type: ReDIF-Article 1.0 # input file: catalog-resolver2363472726524469405.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220713T202513 git hash: 99d3863004 Author-Name: Jiahui Zou Author-X-Name-First: Jiahui Author-X-Name-Last: Zou Author-Name: Wendun Wang Author-X-Name-First: Wendun Author-X-Name-Last: Wang Author-Name: Xinyu Zhang Author-X-Name-First: Xinyu Author-X-Name-Last: Zhang Author-Name: Guohua Zou Author-X-Name-First: Guohua Author-X-Name-Last: Zou Title: Optimal model averaging for divergent-dimensional Poisson regressions Abstract: This paper proposes a new model averaging method to address model uncertainty in Poisson regressions, allowing the dimension of covariates to increase with the sample size. We derive an unbiased estimator of the Kullback–Leibler (KL) divergence to choose averaging weights. We show that when all candidate models are misspecified, the proposed estimate is asymptotically optimal by achieving the least KL divergence among all possible averaging estimators. In another situation where correct models exist in the model space, our method can produce consistent coefficient estimates. We apply the proposed techniques to study the determinants and predict corporate innovation outcomes measured by the number of patents. Journal: Econometric Reviews Pages: 775-805 Issue: 7 Volume: 41 Year: 2022 Month: 8 X-DOI: 10.1080/07474938.2022.2047508 File-URL: http://hdl.handle.net/10.1080/07474938.2022.2047508 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:7:p:775-805 Template-Type: ReDIF-Article 1.0 # input file: catalog-resolver8564431966767516299.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220713T202513 git hash: 99d3863004 Author-Name: Jack Fosten Author-X-Name-First: Jack Author-X-Name-Last: Fosten Author-Name: Ryan Greenaway-McGrevy Author-X-Name-First: Ryan Author-X-Name-Last: Greenaway-McGrevy Title: Panel data nowcasting Abstract: This article promotes the use of panel data methods in nowcasting. This shifts the focus of the literature from national to regional nowcasting of variables like gross domestic product (GDP). We propose a mixed-frequency panel VAR model and a bias-corrected least squares estimator which attenuates the bias in fixed effects dynamic panel settings. Simulations show that panel forecast model selection and combination methods are successfully adapted to the nowcasting setting. Our novel empirical application of nowcasting quarterly U.S. state-level real GDP growth highlights the success of state-level nowcasting, as well as the gains from pooling information across states. Journal: Econometric Reviews Pages: 675-696 Issue: 7 Volume: 41 Year: 2022 Month: 8 X-DOI: 10.1080/07474938.2021.2017670 File-URL: http://hdl.handle.net/10.1080/07474938.2021.2017670 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:7:p:675-696 Template-Type: ReDIF-Article 1.0 # input file: catalog-resolver-4356618351439161000.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220713T202513 git hash: 99d3863004 Author-Name: Aubrey Poon Author-X-Name-First: Aubrey Author-X-Name-Last: Poon Author-Name: Dan Zhu Author-X-Name-First: Dan Author-X-Name-Last: Zhu Title: A new Bayesian model for contagion and interdependence Abstract: We develop a flexible Bayesian time-varying parameter model with a Leamer correction to measure contagion and interdependence. Our proposed framework facilitates a model-based identification mechanism for static and dynamic interdependence. We also allow for fat-tails stochastic volatility within the model, which enables us to capture volatility clustering and outliers in high-frequency financial data. We apply our new proposed framework to two empirical applications: the Chilean foreign exchange market during the Argentine crisis of 2001 and the recent Covid-19 pandemic in the United Kingdom. We find no evidence of contagion effects from Argentina or Brazil to Chile and three additional key insights compared to Ciccarelli and Rebucci 2006 study. For the Covid-19 pandemic application, our results convey that the United Kingdom government was largely ineffective in preventing the importation of Covid-19 cases from European countries during the second wave of the pandemic. Journal: Econometric Reviews Pages: 806-826 Issue: 7 Volume: 41 Year: 2022 Month: 8 X-DOI: 10.1080/07474938.2022.2072319 File-URL: http://hdl.handle.net/10.1080/07474938.2022.2072319 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:7:p:806-826 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2073743_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220804T044749 git hash: 24b08f8188 Author-Name: Barbara Brune Author-X-Name-First: Barbara Author-X-Name-Last: Brune Author-Name: Wolfgang Scherrer Author-X-Name-First: Wolfgang Author-X-Name-Last: Scherrer Author-Name: Efstathia Bura Author-X-Name-First: Efstathia Author-X-Name-Last: Bura Title: A state-space approach to time-varying reduced-rank regression Abstract: We propose a new approach to reduced-rank regression that allows for time-variation in the regression coefficients. The Kalman filter based estimation allows for usage of standard methods and easy implementation of our procedure. The EM-algorithm ensures convergence to a local maximum of the likelihood. Our estimation approach in time-varying reduced-rank regression performs well in simulations, with amplified competitive advantage in time series that experience large structural changes. We illustrate the performance of our approach with a simulation study and two applications to stock index and Covid-19 case data. Journal: Econometric Reviews Pages: 895-917 Issue: 8 Volume: 41 Year: 2022 Month: 9 X-DOI: 10.1080/07474938.2022.2073743 File-URL: http://hdl.handle.net/10.1080/07474938.2022.2073743 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:8:p:895-917 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2047507_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220804T044749 git hash: 24b08f8188 Author-Name: Ye Yang Author-X-Name-First: Ye Author-X-Name-Last: Yang Author-Name: Osman Doğan Author-X-Name-First: Osman Author-X-Name-Last: Doğan Author-Name: Suleyman Taspinar Author-X-Name-First: Suleyman Author-X-Name-Last: Taspinar Title: Model selection and model averaging for matrix exponential spatial models Abstract: In this paper, we focus on a model specification problem in spatial econometric models when an empiricist needs to choose from a pool of candidates for the spatial weights matrix. We propose a model selection (MS) procedure for the matrix exponential spatial specification (MESS), when the true spatial weights matrix may not be in the set of candidate spatial weights matrices. We show that the selection estimator is asymptotically optimal in the sense that asymptotically it is as efficient as the infeasible estimator that uses the best candidate spatial weights matrix. The proposed selection procedure is also consistent in the sense that when the data generating process involves spatial effects, it chooses the true spatial weights matrix with probability approaching one in large samples. We also propose a model averaging (MA) estimator that compromises across a set of candidate models. We show that it is asymptotically optimal. We further flesh out how to extend the proposed selection and averaging schemes to higher order specifications and to the MESS with heteroscedasticity. Our Monte Carlo simulation results indicate that the MS and MA estimators perform well in finite samples. We also illustrate the usefulness of the proposed MS and MA schemes in a spatially augmented economic growth model. Journal: Econometric Reviews Pages: 827-858 Issue: 8 Volume: 41 Year: 2022 Month: 9 X-DOI: 10.1080/07474938.2022.2047507 File-URL: http://hdl.handle.net/10.1080/07474938.2022.2047507 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:8:p:827-858 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2074188_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220804T044749 git hash: 24b08f8188 Author-Name: Wen Xu Author-X-Name-First: Wen Author-X-Name-Last: Xu Title: Testing for time-varying factor loadings in high-dimensional factor models Abstract: This paper proposes a test for structural changes in factor loadings in high-dimensional factor models under weak serial and cross-sectional dependence. The test is an aggregate statistic in the form of the maximum of the variable-specific statistics whose asymptotic null distribution and local power property are studied. Two approaches including extreme value theory and Bonferroni correction are adopted to compute the critical values of the aggregate test statistic. Monte Carlo simulations reveal the non-trivial power of the proposed test against various types of structural changes, including abrupt changes, nonrandom smooth changes, random-walk variations and stationary variations. Additionally, our test can be more powerful than some alternative tests in the considered scenarios. The usefulness of the test is illustrated by an empirical application to Stock and Watson’s U.S. data set. Journal: Econometric Reviews Pages: 918-965 Issue: 8 Volume: 41 Year: 2022 Month: 9 X-DOI: 10.1080/07474938.2022.2074188 File-URL: http://hdl.handle.net/10.1080/07474938.2022.2074188 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:8:p:918-965 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2072323_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220804T044749 git hash: 24b08f8188 Author-Name: Dimitra Kyriakopoulou Author-X-Name-First: Dimitra Author-X-Name-Last: Kyriakopoulou Author-Name: Christian M. Hafner Author-X-Name-First: Christian M. Author-X-Name-Last: Hafner Title: Reconciling negative return skewness with positive time-varying risk premia Abstract: One of the implications of the intertemporal capital asset pricing model (ICAPM) is a positive and linear relationship between the conditional mean and conditional variance of returns to the market portfolio. Empirically, however, it is often observed that there is a negative skewness in equity returns. This article shows that a negative skewness is only compatible with a positive risk premium if the innovation distribution is asymmetric with a negative skewness. We extend recent work using the EGARCH-in-Mean specification to allow for asymmetric innovations, and give results for the unconditional skewness of returns. We apply the model to the prediction of Value-at-Risk of the largest stock market indices, and demonstrate its good performance. Keywords: Exponential GARCH, in-mean, risk premium, ICAPM, unconditional skewness, asymmetric distribution, portfolio selection, Value-at-Risk. Journal: Econometric Reviews Pages: 877-894 Issue: 8 Volume: 41 Year: 2022 Month: 9 X-DOI: 10.1080/07474938.2022.2072323 File-URL: http://hdl.handle.net/10.1080/07474938.2022.2072323 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:8:p:877-894 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2072321_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220804T044749 git hash: 24b08f8188 Author-Name: Chuhui Li Author-X-Name-First: Chuhui Author-X-Name-Last: Li Author-Name: Donald S. Poskitt Author-X-Name-First: Donald S. Author-X-Name-Last: Poskitt Author-Name: Frank Windmeijer Author-X-Name-First: Frank Author-X-Name-Last: Windmeijer Author-Name: Xueyan Zhao Author-X-Name-First: Xueyan Author-X-Name-Last: Zhao Title: Binary outcomes, OLS, 2SLS and IV probit Abstract: For a binary outcome Y, generated by a simple threshold crossing model with a single exogenous normally distributed explanatory variable X, the OLS estimator of the coefficient on X in a linear probability model is a consistent estimator of the average partial effect of X. Even in this very simple setting, we show that when allowing for X to be endogenously determined, the 2SLS estimator, using a normally distributed instrumental variable Z, does not identify the same causal parameter. It instead estimates the average partial effect of Z, scaled by the coefficient on Z in the linear first-stage model for X, denoted γ1, or equivalently, it estimates the average partial effect of the population predicted value of X, Zγ1. These causal parameters can differ substantially as we show for the normal Probit model, which implies that care has to be taken when interpreting 2SLS estimation results in a linear probability model. Under joint normality of the error terms, IV Probit maximum likelihood estimation does identify the average partial effect of X. The two-step control function procedure of Rivers and Vuong can also estimate this causal parameter consistently, but a double averaging is needed, one over the distribution of the first-stage error V and one over the distribution of X. If instead a single averaging is performed over the joint distribution of X and V, then the same causal parameter is estimated as the one estimated by the 2SLS estimator in the linear probability model. The 2SLS estimator is a consistent estimator when the average partial effect is equal to 0, and the standard Wald test for this hypothesis has correct size under strong instrument asymptotics. We show that, in general, the standard weak instrument first-stage F-test interpretations do not apply in this setting. Journal: Econometric Reviews Pages: 859-876 Issue: 8 Volume: 41 Year: 2022 Month: 9 X-DOI: 10.1080/07474938.2022.2072321 File-URL: http://hdl.handle.net/10.1080/07474938.2022.2072321 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:8:p:859-876 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2091713_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220804T044749 git hash: 24b08f8188 Author-Name: Dakyung Seong Author-X-Name-First: Dakyung Author-X-Name-Last: Seong Author-Name: Jin Seo Cho Author-X-Name-First: Jin Seo Author-X-Name-Last: Cho Author-Name: Timo Teräsvirta Author-X-Name-First: Timo Author-X-Name-Last: Teräsvirta Title: Comprehensively testing linearity hypothesis using the smooth transition autoregressive model Abstract: This article examines the null limit distribution of the quasi-likelihood ratio (QLR) statistic for testing linearity condition against the smooth transition autoregressive (STAR) model. We explicitly show that the QLR test statistic weakly converges to a functional of a multivariate Gaussian process under the null of linearity, which is done by resolving the issue of identification problem arises in two different ways under the null. In contrast with the Lagrange multiplier test that is widely employed for testing the linearity condition, the proposed QLR statistic has an omnibus power, and thus, it complements the existing testing procedure. We show the empirical relevance of our test by testing the neglected nonlinearity of the US fiscal multipliers and growth rates of US unemployment. These empirical examples demonstrate that the QLR test is useful for detecting the nonlinear structure among economic variables. Journal: Econometric Reviews Pages: 966-984 Issue: 8 Volume: 41 Year: 2022 Month: 9 X-DOI: 10.1080/07474938.2022.2091713 File-URL: http://hdl.handle.net/10.1080/07474938.2022.2091713 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:8:p:966-984 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2074187_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220823T191300 git hash: 39867e6e2f Author-Name: Xin Geng Author-X-Name-First: Xin Author-X-Name-Last: Geng Author-Name: Kai Sun Author-X-Name-First: Kai Author-X-Name-Last: Sun Title: Estimation of a partially linear seemingly unrelated regressions model: application to a translog cost system Abstract: This article studies a partially linear seemingly unrelated regressions (SUR) model to estimate a translog cost system that consists of a partially linear translog cost function and input share equations. The parametric component is estimated via a simple two-step feasible SUR estimation procedure. We show that the resulting estimator achieves root-n convergence and is asymptotically normal. The nonparametric component is estimated with a nonparametric SUR estimator based on the Cholesky decomposition. We show that this estimator is consistent, asymptotically normal, and more efficient relative to the ones that ignore cross-equation correlation. We emphasize the importance and implication of the choice of square root of the covariance matrix by comparing the Cholesky and Spectral decompositions. A model specification test for parametric functional form is proposed. An Italian banking data set is used to estimate the translog cost system. Results show that marginal effects of risks on cost of production are heterogeneous but increase with risk levels. Journal: Econometric Reviews Pages: 1008-1046 Issue: 9 Volume: 41 Year: 2022 Month: 9 X-DOI: 10.1080/07474938.2022.2074187 File-URL: http://hdl.handle.net/10.1080/07474938.2022.2074187 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:9:p:1008-1046 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2091361_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220823T191300 git hash: 39867e6e2f Author-Name: Shuaizhang Feng Author-X-Name-First: Shuaizhang Author-X-Name-Last: Feng Author-Name: Yingyao Hu Author-X-Name-First: Yingyao Author-X-Name-Last: Hu Author-Name: Jiandong Sun Author-X-Name-First: Jiandong Author-X-Name-Last: Sun Title: Rotation group bias and the persistence of misclassification errors in the Current Population Surveys Abstract: We develop a general misclassification model to explain the so-called “Rotation Group Bias (RGB)” problem in the Current Population Surveys, where different rotation groups report different labor force statistics. The key insight is that responses to repeated questions in surveys can depend not only on unobserved true values, but also on previous responses to the same questions. Our method provides a framework to understand why unemployment rates in rotation group one are higher than those in other rotation groups in the CPS, without imposing any a priori assumptions on the existence and direction of RGB. Using our method, we provide new estimates of the U.S. unemployment rates, which are much higher than the official series, but lower than previous estimates that ignored persistence in misclassification. Journal: Econometric Reviews Pages: 1077-1094 Issue: 9 Volume: 41 Year: 2022 Month: 9 X-DOI: 10.1080/07474938.2022.2091361 File-URL: http://hdl.handle.net/10.1080/07474938.2022.2091361 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:9:p:1077-1094 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2091363_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220823T191300 git hash: 39867e6e2f Author-Name: David M. Drukker Author-X-Name-First: David M. Author-X-Name-Last: Drukker Author-Name: Di Liu Author-X-Name-First: Di Author-X-Name-Last: Liu Title: Finite-sample results for lasso and stepwise Neyman-orthogonal Poisson estimators Abstract: High-dimensional models that include many covariates which might potentially affect an outcome are increasingly common. This paper begins by introducing a lasso-based approach and a stepwise-based approach to valid inference for a high-dimensional model. It then discusses several essential extensions to the literature that make the estimators more usable in practice. Finally, it presents Monte Carlo evidence to help applied researchers choose which of several available estimators should be used in practice. The Monte Carlo evidence shows that our extensions to the literature perform well. It also shows that a BIC-stepwise approach performs well for a data-generating process for which the lasso-based approaches and a testing-stepwise approach fail. The Monte Carlo evidence also indicates the BIC-based lasso and plugin-based lasso can produce better inferential results than the ubiquitous CV-based lasso. Easy-to-use Stata commands are available for all the methods that we discuss. Journal: Econometric Reviews Pages: 1047-1076 Issue: 9 Volume: 41 Year: 2022 Month: 9 X-DOI: 10.1080/07474938.2022.2091363 File-URL: http://hdl.handle.net/10.1080/07474938.2022.2091363 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:9:p:1047-1076 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2091360_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220823T191300 git hash: 39867e6e2f Author-Name: Shunan Zhao Author-X-Name-First: Shunan Author-X-Name-Last: Zhao Author-Name: Yiguo Sun Author-X-Name-First: Yiguo Author-X-Name-Last: Sun Author-Name: Subal C. Kumbhakar Author-X-Name-First: Subal C. Author-X-Name-Last: Kumbhakar Title: Income and democracy: a semiparametric approach Abstract: We examine heterogeneous nonlinear effects of income on democracy using country-level data from 1960 to 2000. Existing studies mainly focused on a linear relationship or restricted nonlinear ones and find mixed findings about the effects of income on democracy. The strong positive cross-country correlation between income and democracy is often found to disappear after controlling country specific fixed effects, although the result varies with different estimation methods and samples. In contrast to previous studies, we apply a flexible semiparametric additive partially linear dynamic panel data model to explore the heterogeneous effects of income on democracy. We assume income is endogenous and it enters in the regression model nonparametrically. Our model specification also allows for different democracy equilibria and adjustment speeds toward equilibria. We propose a nonlinearity test for our model and a penalized sieve minimum distance estimator to solve the ill-posed inverse problem in the semiparametric instrumental variable estimator. The finite sample performance of the proposed test and estimator are evaluated by simulations. In the empirical model, we find that the relationship between income and democracy is nonlinear and it is more complex than a simple inverted U-shape. Specifically, depending on the choice of the democracy measure, income may have positive effects on democracy for low-income countries, negative effects for middle-income countries, and no effects for high-income countries. Journal: Econometric Reviews Pages: 1113-1140 Issue: 9 Volume: 41 Year: 2022 Month: 9 X-DOI: 10.1080/07474938.2022.2091360 File-URL: http://hdl.handle.net/10.1080/07474938.2022.2091360 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:9:p:1113-1140 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2091362_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220823T191300 git hash: 39867e6e2f Author-Name: Bin Chen Author-X-Name-First: Bin Author-X-Name-Last: Chen Title: A robust test for serial correlation in panel data models Abstract: We consider a new nonparametric test for serial correlation of unknown form in the estimated residuals of a panel regression model, where individual and time effects can be fixed or random, and the panel data can be balanced or unbalanced. Our test is robust against potential weak error cross-sectional dependence and error serial dependence in higher-order moments. This is in contrast to existing tests for serial correlation in panel data models, which assume error components to be cross-sectionally and serially independent. Our test has an asymptotic N(0, 1) distribution under the null hypothesis and is consistent against serial correlation of unknown form. No common alternative is assumed and hence our test allows for substantial inhomogeneity in serial correlation across individuals. A simulation study highlights the merits of the proposed test relative to a variety of existing tests in the literature. We apply the new test to the empirical study of Wolfers on the relationship between unilateral divorce laws and divorce rates and find strong evidence against serial uncorrelatedness even controlling for the fixed effect. Journal: Econometric Reviews Pages: 1095-1112 Issue: 9 Volume: 41 Year: 2022 Month: 9 X-DOI: 10.1080/07474938.2022.2091362 File-URL: http://hdl.handle.net/10.1080/07474938.2022.2091362 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:9:p:1095-1112 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2082169_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220823T191300 git hash: 39867e6e2f Author-Name: Yu-Chin Hsu Author-X-Name-First: Yu-Chin Author-X-Name-Last: Hsu Author-Name: Jen-Che Liao Author-X-Name-First: Jen-Che Author-X-Name-Last: Liao Author-Name: Eric S. Lin Author-X-Name-First: Eric S. Author-X-Name-Last: Lin Title: Two-step series estimation and specification testing of (partially) linear models with generated regressors Abstract: This paper studies three semiparametric models that are useful and frequently encountered in applied econometric work—a linear and two partially linear specifications with generated regressors, i.e., the regressors that are unobserved, but can be nonparametrically estimated from the data. Our framework allows for generated regressors to appear in linear or nonlinear components of partially linear models. We propose two-step series estimators for the finite-dimensional parameters, establish their n-consistency (with sample size n) and asymptotic normality, and provide the asymptotic variance formulae that take into account the estimation error of generated regressors. Moreover, we develop a nonparametric specification test for the models considered. Numerical performances of the proposed estimators and test via simulation experiments and an empirical application illustrate the utility of our approach. Journal: Econometric Reviews Pages: 985-1007 Issue: 9 Volume: 41 Year: 2022 Month: 9 X-DOI: 10.1080/07474938.2022.2082169 File-URL: http://hdl.handle.net/10.1080/07474938.2022.2082169 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:9:p:985-1007 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2127077_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949 Author-Name: Martin Huber Author-X-Name-First: Martin Author-X-Name-Last: Huber Author-Name: Lukáš Lafférs Author-X-Name-First: Lukáš Author-X-Name-Last: Lafférs Title: Bounds on direct and indirect effects under treatment/mediator endogeneity and outcome attrition Abstract: Causal mediation analysis aims at disentangling a treatment effect into an indirect mechanism operating through an intermediate outcome or mediator, as well as the direct effect of the treatment on the outcome of interest. However, the evaluation of direct and indirect effects is frequently complicated by non-ignorable selection into the treatment and/or mediator, even after controlling for observables, as well as sample selection/outcome attrition. We propose a method for bounding direct and indirect effects in the presence of such complications using a method that is based on a sequence of linear programming problems. Considering inverse probability weighting by propensity scores, we compute the weights that would yield identification in the absence of complications and perturb them by an entropy parameter reflecting a specific amount of propensity score misspecification to set-identify the effects of interest. We apply our method to data from the National Longitudinal Survey of Youth 1979 to derive bounds on the explained and unexplained components of a gender wage gap decomposition that is likely prone to non-ignorable mediator selection and outcome attrition. Journal: Econometric Reviews Pages: 1141-1163 Issue: 10 Volume: 41 Year: 2022 Month: 11 X-DOI: 10.1080/07474938.2022.2127077 File-URL: http://hdl.handle.net/10.1080/07474938.2022.2127077 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:10:p:1141-1163 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2114624_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949 Author-Name: Ju Hyun Kim Author-X-Name-First: Ju Hyun Author-X-Name-Last: Kim Author-Name: Byoung G. Park Author-X-Name-First: Byoung G. Author-X-Name-Last: Park Title: Testing rank similarity in the local average treatment effects model Abstract: This paper develops a test for the rank similarity condition of the nonseparable instrumental variable quantile regression model using the local average treatment effect model. When the instrument takes more than two values or multiple binary instruments are available, there exist multiple complier groups for which the marginal distributions of potential outcomes are identified. A testable implication is obtained by comparing the distributions of ranks across complier groups. We propose a test procedure in a semiparametric quantile regression specification. We establish the weak convergence of the test statistic and the validity of the bootstrap critical value. We illustrate the test with an empirical example of the effects of fertility on women’s labor supply. Journal: Econometric Reviews Pages: 1265-1286 Issue: 10 Volume: 41 Year: 2022 Month: 11 X-DOI: 10.1080/07474938.2022.2114624 File-URL: http://hdl.handle.net/10.1080/07474938.2022.2114624 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:10:p:1265-1286 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2114623_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949 Author-Name: Maoshan Tian Author-X-Name-First: Maoshan Author-X-Name-Last: Tian Author-Name: Huw Dixon Author-X-Name-First: Huw Author-X-Name-Last: Dixon Title: The variances of non-parametric estimates of the cross-sectional distribution of durations Abstract: This paper focuses on the link between non-parametric survival analysis and three distributions. The delta method is applied to derive the variances of the non-parametric estimators of three distributions: the distribution of durations (DD), the cross-sectional distribution of ages (CSA) and the cross-sectional distribution of (completed) durations (CSD). The non-parametric estimator of the the cross-sectional distribution of durations (CSD) has been defined and derived by Dixon (2012) and used in the generalized Taylor price model (GTE) by Dixon and Le Bihan (2012). The Monte Carlo method is applied to evaluate the variances of the estimators of DD and CSD and how their performance varies with sample size and the censoring of data. We apply those estimators to two data sets: the UK CPI micro-price data and waiting-time data from UK hospitals. Both the estimates of the distributions and their variances are calculated. Depending on the empirical results, the estimated variances indicate that the DD and CSD estimators are all significant. Journal: Econometric Reviews Pages: 1243-1264 Issue: 10 Volume: 41 Year: 2022 Month: 11 X-DOI: 10.1080/07474938.2022.2114623 File-URL: http://hdl.handle.net/10.1080/07474938.2022.2114623 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:10:p:1243-1264 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2114625_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949 Author-Name: Marie-Claude Beaulieu Author-X-Name-First: Marie-Claude Author-X-Name-Last: Beaulieu Author-Name: Lynda Khalaf Author-X-Name-First: Lynda Author-X-Name-Last: Khalaf Author-Name: Maral Kichian Author-X-Name-First: Maral Author-X-Name-Last: Kichian Author-Name: Olena Melin Author-X-Name-First: Olena Author-X-Name-Last: Melin Title: Finite sample inference in multivariate instrumental regressions with an application to Catastrophe bonds* Abstract: We propose exact exogeneity tests and weak-instruments-robust tests on factor loadings for a system of regressions with possibly non-Gaussian disturbances. Our methodology is valid in finite samples and accounts for common cross-sectional factors. Analytical invariance results are derived, with companion simulation studies. Finally, a total-effect parameter is introduced that embeds the unobservable endogeneity factor. Proposed tests are applied to assess whether Catastrophe bond mutual funds co-move with financial markets. Significant risk premiums are detected globally and over time, although they are less pervasive from a domestic currency perspective. Findings underscore the importance of instrumenting and assessing direct and total effects. Journal: Econometric Reviews Pages: 1205-1242 Issue: 10 Volume: 41 Year: 2022 Month: 11 X-DOI: 10.1080/07474938.2022.2114625 File-URL: http://hdl.handle.net/10.1080/07474938.2022.2114625 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:10:p:1205-1242 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2127076_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949 Author-Name: Hao Dong Author-X-Name-First: Hao Author-X-Name-Last: Dong Author-Name: Taisuke Otsu Author-X-Name-First: Taisuke Author-X-Name-Last: Otsu Author-Name: Luke Taylor Author-X-Name-First: Luke Author-X-Name-Last: Taylor Title: Nonparametric estimation of additive models with errors-in-variables Abstract: In the estimation of nonparametric additive models, conventional methods, such as backfitting and series approximation, cannot be applied when measurement error is present in a covariate. This paper proposes a two-stage estimator for such models. In the first stage, to adapt to the additive structure, we use a series approximation together with a ridge approach to deal with the ill-posedness brought by mismeasurement. We derive the uniform convergence rate of this first-stage estimator and characterize how the measurement error slows down the convergence rate for ordinary/super smooth cases. To establish the limiting distribution, we construct a second-stage estimator via one-step backfitting with a deconvolution kernel using the first-stage estimator. The asymptotic normality of the second-stage estimator is established for ordinary/super smooth measurement error cases. Finally, a Monte Carlo study and an empirical application highlight the applicability of the estimator. Journal: Econometric Reviews Pages: 1164-1204 Issue: 10 Volume: 41 Year: 2022 Month: 11 X-DOI: 10.1080/07474938.2022.2127076 File-URL: http://hdl.handle.net/10.1080/07474938.2022.2127076 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:10:p:1164-1204 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2147136_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949 Author-Name: The Editors Title: Back Matter Journal: Econometric Reviews Pages: 1287-1288 Issue: 10 Volume: 41 Year: 2022 Month: 11 X-DOI: 10.1080/07474938.2022.2147136 File-URL: http://hdl.handle.net/10.1080/07474938.2022.2147136 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:41:y:2022:i:10:p:1287-1288 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2135495_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20 Author-Name: Helmut Herwartz Author-X-Name-First: Helmut Author-X-Name-Last: Herwartz Author-Name: Simone Maxand Author-X-Name-First: Simone Author-X-Name-Last: Maxand Author-Name: Yabibal M. Walle Author-X-Name-First: Yabibal M. Author-X-Name-Last: Walle Title: Forward detrending for heteroskedasticity-robust panel unit root testing Abstract: The variances of most economic time series display marked fluctuations over time. Panel unit root tests of the so-called first and second generation are not robust in such cases. In response to this problem, a few heteroskedasticity-robust panel unit root tests have been proposed. An important limitation of these tests is, however, that they become invalid if the data are trending. As a prominent means of drift adjustment under the panel unit root hypothesis, the (unweighted) forward detrending scheme of Breitung suffers from nuisance parameters if the data feature time-varying variances. In this article, we propose a weighted forward-detrending scheme. Unlike its unweighted counterpart, the new detrending scheme restores the pivotalness of the heteroskedasticity-robust panel unit root tests suggested by Demetrescu and Hanck and Herwartz et al. when applied to trending panels with heteroskedastic variances. As an empirical illustration, we provide evidence in favor of non-stationarity of health care expenditures as shares of GDP in a panel of OECD economies. Journal: Econometric Reviews Pages: 28-53 Issue: 1 Volume: 42 Year: 2023 Month: 1 X-DOI: 10.1080/07474938.2022.2135495 File-URL: http://hdl.handle.net/10.1080/07474938.2022.2135495 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:42:y:2023:i:1:p:28-53 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2094539_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20 Author-Name: Jingjie Xiang Author-X-Name-First: Jingjie Author-X-Name-Last: Xiang Author-Name: Gangzheng Guo Author-X-Name-First: Gangzheng Author-X-Name-Last: Guo Author-Name: Jiaolong Li Author-X-Name-First: Jiaolong Author-X-Name-Last: Li Title: Determining the number of factors in constrained factor models via Bayesian information criterion Abstract: This paper estimates the number of factors in constrained and partially constrained factor models (Tsai and Tsay, 2010) based on constrained Bayesian information criterion (CBIC). Following Bai and Ng (2002), the estimation of the number of factors depends on the tradeoff between good fit and parsimony, so we first derive the convergence rate of constrained factor estimates under the framework of large cross-sections (N) and large time dimensions (T). Furthermore, we demonstrate that the penalty for overfitting can be a function of N alone, so the BIC form, which does not work in the case of (unconstrained) approximate factor models, consistently estimates the number of factors in constrained factor models. We then conduct Monte Carlo simulations to show that our proposed CBIC has good finite sample performance and outperforms competing methods. Journal: Econometric Reviews Pages: 98-122 Issue: 1 Volume: 42 Year: 2023 Month: 1 X-DOI: 10.1080/07474938.2022.2094539 File-URL: http://hdl.handle.net/10.1080/07474938.2022.2094539 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:42:y:2023:i:1:p:98-122 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2140982_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20 Author-Name: Martin Burda Author-X-Name-First: Martin Author-X-Name-Last: Burda Author-Name: Remi Daviet Author-X-Name-First: Remi Author-X-Name-Last: Daviet Title: Hamiltonian sequential Monte Carlo with application to consumer choice behavior Abstract: The practical use of nonparametric Bayesian methods requires the availability of efficient algorithms for posterior inference. The inherently serial nature of traditional Markov chain Monte Carlo (MCMC) methods imposes limitations on their efficiency and scalability. In recent years, there has been a surge of research activity devoted to developing alternative implementation methods that target parallel computing environments. Sequential Monte Carlo (SMC), also known as a particle filter, has been gaining popularity due to its desirable properties. SMC uses a genetic mutation-selection sampling approach with a set of particles representing the posterior distribution of a stochastic process. We propose to enhance the performance of SMC by utilizing Hamiltonian transition dynamics in the particle transition phase, in place of random walk used in the previous literature. We call the resulting procedure Hamiltonian Sequential Monte Carlo (HSMC). Hamiltonian transition dynamics have been shown to yield superior mixing and convergence properties relative to random walk transition dynamics in the context of MCMC procedures. The rationale behind HSMC is to translate such gains to the SMC environment. HSMC will facilitate practical estimation of models with complicated latent structures, such as nonparametric individual unobserved heterogeneity, that are otherwise difficult to implement. We demonstrate the behavior of HSMC in a challenging simulation study and contrast its favorable performance with SMC and other alternative approaches. We then apply HSMC to a panel discrete choice model with nonparametric consumer heterogeneity, allowing for multiple modes, asymmetries, and data-driven clustering, providing insights for consumer segmentation, individual level marketing, and price micromanagement. Journal: Econometric Reviews Pages: 54-77 Issue: 1 Volume: 42 Year: 2023 Month: 1 X-DOI: 10.1080/07474938.2022.2140982 File-URL: http://hdl.handle.net/10.1080/07474938.2022.2140982 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:42:y:2023:i:1:p:54-77 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2156740_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20 Author-Name: Saban Nazlioglu Author-X-Name-First: Saban Author-X-Name-Last: Nazlioglu Author-Name: Junsoo Lee Author-X-Name-First: Junsoo Author-X-Name-Last: Lee Author-Name: Margie Tieslau Author-X-Name-First: Margie Author-X-Name-Last: Tieslau Author-Name: Cagin Karul Author-X-Name-First: Cagin Author-X-Name-Last: Karul Author-Name: Yu You Author-X-Name-First: Yu Author-X-Name-Last: You Title: Smooth structural changes and common factors in nonstationary panel data: an analysis of healthcare expenditures† Abstract: This article suggests new panel unit root tests that allow for multiple structural breaks and control for cross-correlations in the panel. Breaks are modeled with a Fourier function, which allows for smooth or gradual change rather than abrupt breaks. Cross-correlations are corrected by using the PANIC procedure. The simulations show that our tests have good size and power properties and perform reasonably well when the nature of breaks or the factor structure is unknown. The new panel unit root tests support fresh evidence on the persistence of healthcare expenditures in OECD countries. Journal: Econometric Reviews Pages: 78-97 Issue: 1 Volume: 42 Year: 2023 Month: 1 X-DOI: 10.1080/07474938.2022.2156740 File-URL: http://hdl.handle.net/10.1080/07474938.2022.2156740 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:42:y:2023:i:1:p:78-97 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2157965_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20 Author-Name: Masayuki Hirukawa Author-X-Name-First: Masayuki Author-X-Name-Last: Hirukawa Author-Name: Irina Murtazashvili Author-X-Name-First: Irina Author-X-Name-Last: Murtazashvili Author-Name: Artem Prokhorov Author-X-Name-First: Artem Author-X-Name-Last: Prokhorov Title: Yet another look at the omitted variable bias Abstract: When conducting regression analysis, econometricians often face the situation where some relevant regressors are unavailable in the data set at hand. This article shows how to construct a new class of nonparametric proxies by combining the original data set with one containing the missing regressors. Imputation of the missing values is done using a nonstandard kernel adapted to mixed data. We derive the asymptotic distribution of the resulting semiparametric two-sample estimator of the parameters of interest and show, using Monte Carlo simulations, that it dominates the solutions involving instrumental variables and other parametric alternatives. An application to the PSID and NLS data illustrates the importance of our estimation approach for empirical research. Journal: Econometric Reviews Pages: 1-27 Issue: 1 Volume: 42 Year: 2023 Month: 1 X-DOI: 10.1080/07474938.2022.2157965 File-URL: http://hdl.handle.net/10.1080/07474938.2022.2157965 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:42:y:2023:i:1:p:1-27 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2178089_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20 Author-Name: Bhavna Rai Author-X-Name-First: Bhavna Author-X-Name-Last: Rai Title: Efficient estimation with missing data and endogeneity Abstract: I study the problem of missing values in the outcome and endogenous covariates in linear models. I propose an estimator that improves efficiency relative to a complete cases 2SLS. Unlike traditional imputation, my estimator is consistent even if the model contains nonlinear functions – like squares and interactions – of the endogenous covariates. It can also be used to combine data sets with missing outcome, missing endogenous covariates, and no missing variables. It includes the well-known “Two-Sample 2SLS” as a special case under weaker assumptions than the corresponding literature. Journal: Econometric Reviews Pages: 220-239 Issue: 2 Volume: 42 Year: 2023 Month: 2 X-DOI: 10.1080/07474938.2023.2178089 File-URL: http://hdl.handle.net/10.1080/07474938.2023.2178089 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:42:y:2023:i:2:p:220-239 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2178086_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20 Author-Name: Andres Aradillas-Lopez Author-X-Name-First: Andres Author-X-Name-Last: Aradillas-Lopez Title: Inference in an incomplete information entry game with an incumbent and with beliefs conditioned on unobservable market characteristics Abstract: We consider a static entry game played between an incumbent and a collection of potential entrants. Entry decisions are made with incomplete information and beliefs are conditioned, at least partially, on a market characteristic that is unobserved by the econometrician. We describe conditions under which, even though the unobserved market characteristic cannot be identified, a subset of parameters of the model can still be identified, including all the strategic-interaction effects. We also characterize testable implications for strategic behavior by the incumbent when this player is able to shift the unobserved market characteristic to deter entry. We present results under Bayesian Nash equilibrium (BNE) and under the weaker behavioral model of iterated elimination of nonrationalizable strategies. Our empirical example analyzes geographic entry decisions in the Mexican internet service provider (ISP) industry. This industry has an incumbent, América Móvil (AMX), which established a widespread geographic presence as a monopolist following the privatization of Telmex in 1990. Our results show significant strategic interaction effects between AMX and its competitors, as well as evidence of strategic behavior by AMX to deter entry and maximize its market share. Journal: Econometric Reviews Pages: 123-156 Issue: 2 Volume: 42 Year: 2023 Month: 2 X-DOI: 10.1080/07474938.2023.2178086 File-URL: http://hdl.handle.net/10.1080/07474938.2023.2178086 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:42:y:2023:i:2:p:123-156 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2178139_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20 Author-Name: Badi H. Baltagi Author-X-Name-First: Badi H. Author-X-Name-Last: Baltagi Title: The two-way Mundlak estimator Abstract: Mundlak shows that the fixed effects estimator is equivalent to the random effects estimator in the one-way error component model once the random individual effects are modeled as a linear function of all the averaged regressors over time. In the spirit of Mundlak, this paper shows that this result also holds for the two-way error component model once the individual and time effects are modeled as linear functions of all the averaged regressors across time and across individuals. Wooldridge also shows that the two-way fixed effects estimator can be obtained as a pooled OLS with the regressors augmented by the time and individual averages and calls it the two-way Mundlak estimator. While Mundlak used GLS rather than OLS on this augmented regression, we show that both estimators are equivalent for this augmented regression. This extends Baltagi’s results from the one-way to the two-way error component model. The F test suggested by Mundlak to test for this correlation between the random effects and the regressors generate a Hausman type test that is easily generalizable to the two-way Mundlak regression. In fact, the resulting F-tests for the two-way error component regression are related to the Hausman type tests proposed by Kang for the two-way error component model. Journal: Econometric Reviews Pages: 240-246 Issue: 2 Volume: 42 Year: 2023 Month: 2 X-DOI: 10.1080/07474938.2023.2178139 File-URL: http://hdl.handle.net/10.1080/07474938.2023.2178139 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:42:y:2023:i:2:p:240-246 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2178087_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20 Author-Name: Fei Jin Author-X-Name-First: Fei Author-X-Name-Last: Jin Author-Name: Lung-fei Lee Author-X-Name-First: Lung-fei Author-X-Name-Last: Lee Author-Name: Jihai Yu Author-X-Name-First: Jihai Author-X-Name-Last: Yu Title: Estimating flow data models of international trade: dual gravity and spatial interactions Abstract: This article investigates asymptotic properties of quasi-maximum likelihood (QML) estimates for flow data on the dual gravity model in international trade with spatial interactions (dependence). The dual gravity model has a well-established economic foundation, and it takes the form of a spatial autoregressive (SAR) model. The dual gravity model originates from Behrens et al., but the spatial weights matrix motivated by their economic theory has a feature that violates existing regularity conditions for asymptotic econometrics analysis. By overcoming the limitations of existing asymptotic theory, we show that QML estimates are consistent and asymptotically normal. The simulation results show the satisfactory finite sample performance of the estimates. We illustrate the usefulness of the model by investigating the McCallum “border puzzle” in the gravity literature. Journal: Econometric Reviews Pages: 157-194 Issue: 2 Volume: 42 Year: 2023 Month: 2 X-DOI: 10.1080/07474938.2023.2178087 File-URL: http://hdl.handle.net/10.1080/07474938.2023.2178087 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:42:y:2023:i:2:p:157-194 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2178088_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20 Author-Name: Eric Beutner Author-X-Name-First: Eric Author-X-Name-Last: Beutner Author-Name: Yicong Lin Author-X-Name-First: Yicong Author-X-Name-Last: Lin Author-Name: Stephan Smeekes Author-X-Name-First: Stephan Author-X-Name-Last: Smeekes Title: GLS estimation and confidence sets for the date of a single break in models with trends Abstract: We develop a Feasible Generalized Least Squares estimator of the date of a structural break in level and/or trend. The estimator is based on a consistent estimate of a T-dimensional inverse autocovariance matrix. A cubic polynomial transformation of break date estimates can be approximated by a nonstandard yet nuisance parameter free distribution asymptotically. The new limiting distribution captures the asymmetry and bimodality in finite samples and is applicable for inference with a single, known, set of critical values. We consider the confidence intervals/sets for break dates based on both Wald-type tests and by inverting multiple likelihood ratio (LR) tests. A simulation study shows that the proposed estimator increases the empirical concentration probability in a small neighborhood of the true break date and potentially reduces the mean squared errors. The LR-based confidence intervals/sets have good coverage while maintaining informative length even with highly persistent errors and small break sizes. Journal: Econometric Reviews Pages: 195-219 Issue: 2 Volume: 42 Year: 2023 Month: 2 X-DOI: 10.1080/07474938.2023.2178088 File-URL: http://hdl.handle.net/10.1080/07474938.2023.2178088 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:42:y:2023:i:2:p:195-219 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2178138_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20 Author-Name: Federico Belotti Author-X-Name-First: Federico Author-X-Name-Last: Belotti Author-Name: Alessandro Casini Author-X-Name-First: Alessandro Author-X-Name-Last: Casini Author-Name: Leopoldo Catania Author-X-Name-First: Leopoldo Author-X-Name-Last: Catania Author-Name: Stefano Grassi Author-X-Name-First: Stefano Author-X-Name-Last: Grassi Author-Name: Pierre Perron Author-X-Name-First: Pierre Author-X-Name-Last: Perron Title: Simultaneous bandwidths determination for DK-HAC estimators and long-run variance estimation in nonparametric settings Abstract: We consider the derivation of data-dependent simultaneous bandwidths for double kernel heteroscedasticity and autocorrelation consistent (DK-HAC) estimators. In addition to the usual smoothing over lagged autocovariances for classical HAC estimators, the DK-HAC estimator also applies smoothing over the time direction. We obtain the optimal bandwidths that jointly minimize the global asymptotic MSE criterion and discuss the tradeoff between bias and variance with respect to smoothing over lagged autocovariances and over time. Unlike the MSE results of Andrews, we establish how nonstationarity affects the bias-variance tradeoff. We use the plug-in approach to construct data-dependent bandwidths for the DK-HAC estimators and compare them with the DK-HAC estimators from Casini that use data-dependent bandwidths obtained from a sequential MSE criterion. The former performs better in terms of size control, especially with stationary and close to stationary data. Finally, we consider long-run variance (LRV) estimation under the assumption that the series is a function of a nonparametric estimator rather than of a semiparametric estimator that enjoys the usual T rate of convergence. Thus, we also establish the validity of consistent LRV estimation in nonparametric parameter estimation settings. Journal: Econometric Reviews Pages: 281-306 Issue: 3 Volume: 42 Year: 2023 Month: 2 X-DOI: 10.1080/07474938.2023.2178138 File-URL: http://hdl.handle.net/10.1080/07474938.2023.2178138 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:42:y:2023:i:3:p:281-306 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2178136_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20 Author-Name: Yong Bao Author-X-Name-First: Yong Author-X-Name-Last: Bao Title: Indirect inference estimation of higher-order spatial autoregressive models Abstract: This paper proposes estimating parameters in higher-order spatial autoregressive models, where the error term also follows a spatial autoregression and its innovations are heteroskedastic, by matching the simple ordinary least squares estimator with its analytical approximate expectation, following the principle of indirect inference. The resulting estimator is shown to be consistent, asymptotically normal, simulation-free, and robust to unknown heteroskedasticity. Monte Carlo simulations demonstrate its good finite-sample properties in comparison with existing estimators. An empirical study of Airbnb rental prices in the city of Asheville illustrates that the structure of spatial correlation and effects of various factors at the early stage of the COVID-19 pandemic are quite different from those during the second summer. Notably, during the pandemic, safety is valued more and on-line reviews are valued much less. Journal: Econometric Reviews Pages: 247-280 Issue: 3 Volume: 42 Year: 2023 Month: 2 X-DOI: 10.1080/07474938.2023.2178136 File-URL: http://hdl.handle.net/10.1080/07474938.2023.2178136 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:42:y:2023:i:3:p:247-280 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2178140_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20 Author-Name: Sungho Noh Author-X-Name-First: Sungho Author-X-Name-Last: Noh Title: Nonparametric identification and estimation of heterogeneous causal effects under conditional independence Abstract: In this article, I propose a nonparametric strategy to identify the distribution of heterogeneous causal effects. A set of identification restrictions proposed in this article differs from existing approaches in three ways. First, it extends the random coefficient model by allowing potentially nonlinear interactions between distributional parameters and the set of covariates. Second, the causal effect distributions identified in this article give an alternative to those under the rank invariance assumption. Third, identified distribution lies within the sharp bound of distributions of the treatment effect. I develop a consistent nonparametric estimator exploiting the identifying restriction by extending the conventional statistical deconvolution method to the Rubin causal framework. Results from a Monte Carlo experiment and an application to wage loss of displaced workers suggest that the method yields robust estimates under various scenarios. Journal: Econometric Reviews Pages: 307-341 Issue: 3 Volume: 42 Year: 2023 Month: 2 X-DOI: 10.1080/07474938.2023.2178140 File-URL: http://hdl.handle.net/10.1080/07474938.2023.2178140 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:42:y:2023:i:3:p:307-341 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2191105_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20 Author-Name: Hao Dong Author-X-Name-First: Hao Author-X-Name-Last: Dong Author-Name: Taisuke Otsu Author-X-Name-First: Taisuke Author-X-Name-Last: Otsu Author-Name: Luke Taylor Author-X-Name-First: Luke Author-X-Name-Last: Taylor Title: Bandwidth selection for nonparametric regression with errors-in-variables Abstract: We propose two novel bandwidth selection procedures for the nonparametric regression model with classical measurement error in the regressors. Each method evaluates the prediction errors of the regression using a second (density) deconvolution. The first approach uses a typical leave-one-out cross-validation criterion, while the second applies a bootstrap approach and the concept of out-of-bag prediction. We show the asymptotic validity of both procedures and compare them to the SIMEX method in a Monte Carlo study. As well as dramatically reducing computational cost, the methods proposed in this article lead to lower mean integrated squared error (MISE) compared to the current state-of-the-art. Journal: Econometric Reviews Pages: 393-419 Issue: 4 Volume: 42 Year: 2023 Month: 4 X-DOI: 10.1080/07474938.2023.2191105 File-URL: http://hdl.handle.net/10.1080/07474938.2023.2191105 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:42:y:2023:i:4:p:393-419 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2178137_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20 Author-Name: Richard Startz Author-X-Name-First: Richard Author-X-Name-Last: Startz Author-Name: Douglas G. Steigerwald Author-X-Name-First: Douglas G. Author-X-Name-Last: Steigerwald Title: Inference and extrapolation in finite populations with special attention to clustering Abstract: Statistical inference in economics is commonly based on formulas assuming infinite populations. We present appropriate formulas for use when sampling from finite populations, with special attention given to issues of treatment effects and to issues of clustering. Issues of whether to apply finite population corrections are often subtle, and appropriate corrections may depend on difficult to observe parameters, leaving the investigator only with bounds on relevant estimator variances. Journal: Econometric Reviews Pages: 343-357 Issue: 4 Volume: 42 Year: 2023 Month: 4 X-DOI: 10.1080/07474938.2023.2178137 File-URL: http://hdl.handle.net/10.1080/07474938.2023.2178137 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:42:y:2023:i:4:p:343-357 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2178141_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20 Author-Name: Martin Wagner Author-X-Name-First: Martin Author-X-Name-Last: Wagner Author-Name: Karsten Reichold Author-X-Name-First: Karsten Author-X-Name-Last: Reichold Title: Panel cointegrating polynomial regressions: group-mean fully modified OLS estimation and inference Abstract: We develop group-mean fully modified OLS (FM-OLS) estimation and inference for panels of cointegrating polynomial regressions, i.e., regressions that include an integrated process and its powers as explanatory variables. The stationary errors are allowed to be serially correlated, the integrated regressors – allowed to contain drifts – to be endogenous and, as usual in the panel literature, we include individual-specific fixed effects and also allow for individual-specific time trends. We consider a fixed cross-section dimension and asymptotics in the time dimension only. Within this setting, we develop cross-section dependence robust inference for the group-mean estimator. In both the simulations and an illustrative application estimating environmental Kuznets curves (EKCs) for carbon dioxide emissions we compare our group-mean FM-OLS approach with a recently proposed pooled FM-OLS approach of de Jong and Wagner. Journal: Econometric Reviews Pages: 358-392 Issue: 4 Volume: 42 Year: 2023 Month: 4 X-DOI: 10.1080/07474938.2023.2178141 File-URL: http://hdl.handle.net/10.1080/07474938.2023.2178141 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:42:y:2023:i:4:p:358-392 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2198930_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20 Author-Name: Enzo D’Innocenzo Author-X-Name-First: Enzo Author-X-Name-Last: D’Innocenzo Author-Name: Alessandra Luati Author-X-Name-First: Alessandra Author-X-Name-Last: Luati Author-Name: Mario Mazzocchi Author-X-Name-First: Mario Author-X-Name-Last: Mazzocchi Title: A robust score-driven filter for multivariate time series Abstract: A multivariate score-driven filter is developed to extract signals from noisy vector processes. By assuming that the conditional location vector from a multivariate Student’s t distribution changes over time, we construct a robust filter which is able to overcome several issues that naturally arise when modeling heavy-tailed phenomena and, more in general, vectors of dependent non-Gaussian time series. We derive conditions for stationarity and invertibility and estimate the unknown parameters by maximum likelihood. Strong consistency and asymptotic normality of the estimator are derived. Analytical formulae are derived which consent to develop estimation procedures based on a fast and reliable Fisher scoring method. An extensive Monte–Carlo study is designed to assess the finite samples properties of the estimator, the impact of initial conditions on the filtered sequence, the performance when some of the underlying assumptions are violated, such as symmetry of the underlying distribution and homogeneity of the degrees of freedom parameter across marginals. The theory is supported by a novel empirical illustration that shows how the model can be effectively applied to estimate consumer prices from home scanner data. Journal: Econometric Reviews Pages: 441-470 Issue: 5 Volume: 42 Year: 2023 Month: 5 X-DOI: 10.1080/07474938.2023.2198930 File-URL: http://hdl.handle.net/10.1080/07474938.2023.2198930 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:42:y:2023:i:5:p:441-470 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2205339_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20 Author-Name: Offer Lieberman Author-X-Name-First: Offer Author-X-Name-Last: Lieberman Author-Name: Francesca Rossi Author-X-Name-First: Francesca Author-X-Name-Last: Rossi Title: Inference in a similarity-based spatial autoregressive model Abstract: In this article, we develop asymptotic theory for a spatial autoregressive (SAR) model where the network structure is defined according to a similarity-based weight matrix, in line with the similarity theory, which in turn has an axiomatic justification. We prove consistency of the quasi-maximum-likelihood estimator and derive its limit distribution. The contribution of this article is two-fold: on one hand, we incorporate a regression component in the data generating process while allowing the similarity structure to accommodate non-ordered data and by estimating explicitly the weight of the similarity, allowing it to be equal to unity. On the other hand, this work complements the literature on SAR models by adopting a data-driven weight matrix which depends on a finite set of parameters that have to be estimated. The spatial parameter, which corresponds to the weight of the similarity structure, is in turn allowed to take values at the boundary of the standard SAR parameter space. In addition, our setup accommodates strong forms of cross-sectional correlation that are normally ruled out in the standard SAR literature. Our framework is general enough to include as special cases also the random walk with a drift model, the local to unit root model (LUR) with a drift and the model for moderate integration with a drift. Journal: Econometric Reviews Pages: 471-486 Issue: 5 Volume: 42 Year: 2023 Month: 5 X-DOI: 10.1080/07474938.2023.2205339 File-URL: http://hdl.handle.net/10.1080/07474938.2023.2205339 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:42:y:2023:i:5:p:471-486 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2209008_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20 Author-Name: Estela Bee Dagum Author-X-Name-First: Estela Bee Author-X-Name-Last: Dagum Author-Name: Silvia Bianconcini Author-X-Name-First: Silvia Author-X-Name-Last: Bianconcini Title: Monitoring the direction of the short-term trend of economic indicators Abstract: Socioeconomic indicators have long been used by official statistical agencies to analyze and assess the current stage at which the economy stands via the application of linear filters used in conjunction with seasonal adjustment procedures. In this study, we propose a new set of symmetric and asymmetric weights that offer substantial gains in real-time by providing timely and more accurate information for detecting short-term trends with respect to filters commonly applied by statistical agencies. We compare the new filters to the classical ones through application to indicators of the US economy, which remains the linchpin of the global economic system. To assess the superiority of the proposed filters, we develop and evaluate explicit tests of the null hypothesis of no difference in revision accuracy of two competing filters. Furthermore, asymptotic and exact finite-sample tests are proposed and illustrated to assess if two compared filters have equal probabilities of failing to detect turning points at different time horizons after their occurrence. Journal: Econometric Reviews Pages: 421-440 Issue: 5 Volume: 42 Year: 2023 Month: 5 X-DOI: 10.1080/07474938.2023.2209008 File-URL: http://hdl.handle.net/10.1080/07474938.2023.2209008 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:42:y:2023:i:5:p:421-440 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2198929_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20 Author-Name: Kohtaro Hitomi Author-X-Name-First: Kohtaro Author-X-Name-Last: Hitomi Author-Name: Masamune Iwasawa Author-X-Name-First: Masamune Author-X-Name-Last: Iwasawa Author-Name: Yoshihiko Nishiyama Author-X-Name-First: Yoshihiko Author-X-Name-Last: Nishiyama Title: Optimal minimax rates of specification testing with data-driven bandwidth Abstract: This study investigates optimal minimax rates of specification testing for linear and non-linear instrumental variable regression models. The test constructed by non-parametric kernel techniques can be rate optimal when bandwidths are selected appropriately. Since bandwidths are often selected in a data-dependent way in empirical studies, the rate-optimality of the test with data-driven bandwidths is investigated. While least squares cross-validation selects bandwidths that are optimal for estimation, it is shown not to be optimal for testing. Thus, we propose a novel bandwidth selection method for testing, the performance of which is investigated in a simulation study. Journal: Econometric Reviews Pages: 487-512 Issue: 6 Volume: 42 Year: 2023 Month: 6 X-DOI: 10.1080/07474938.2023.2198929 File-URL: http://hdl.handle.net/10.1080/07474938.2023.2198929 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:42:y:2023:i:6:p:487-512 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2209007_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20 Author-Name: Yuta Yamauchi Author-X-Name-First: Yuta Author-X-Name-Last: Yamauchi Author-Name: Yasuhiro Omori Author-X-Name-First: Yasuhiro Author-X-Name-Last: Omori Title: Dynamic factor, leverage and realized covariances in multivariate stochastic volatility Abstract: In the stochastic volatility models for multivariate daily stock returns, it has been found that the estimates of parameters become unstable as the dimension of returns increases. To solve this problem, we focus on the factor structure of multiple returns and consider two additional sources of information: first, the stock index associated with the market factor and, second, the realized covariance matrix calculated from high-frequency data. The proposed dynamic factor model with the leverage effect and realized measures is applied to 10 top stocks composing the exchange traded fund linked with the investment return of the S&P 500 index and the model is shown to have a stable advantage in portfolio performance. Journal: Econometric Reviews Pages: 513-539 Issue: 6 Volume: 42 Year: 2023 Month: 6 X-DOI: 10.1080/07474938.2023.2209007 File-URL: http://hdl.handle.net/10.1080/07474938.2023.2209007 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:42:y:2023:i:6:p:513-539 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2217077_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20 Author-Name: Bingduo Yang Author-X-Name-First: Bingduo Author-X-Name-Last: Yang Author-Name: Xiaohui Liu Author-X-Name-First: Xiaohui Author-X-Name-Last: Liu Author-Name: Wei Long Author-X-Name-First: Wei Author-X-Name-Last: Long Author-Name: Liang Peng Author-X-Name-First: Liang Author-X-Name-Last: Peng Title: A unified unit root test regardless of intercept Abstract: Using the augmented Dickey-Fuller test to verify the existence of a unit root in an autoregressive process often requires the correctly specified intercept, since the test statistics can be distinctive under different model specifications and lead to contradictory results at times. In this article, we develop a unified inference that not only unifies the specifications of the intercept but also accommodates different degrees of persistence of the underlying process and heteroscedastic errors. A simulation study shows that the resulting unified unit root test exhibits excellent size control and reasonably good power. In an empirical application, we implement the proposed test to re-examine the presence of unit roots within eleven widely used variables in stock return predictability. Journal: Econometric Reviews Pages: 540-555 Issue: 6 Volume: 42 Year: 2023 Month: 6 X-DOI: 10.1080/07474938.2023.2217077 File-URL: http://hdl.handle.net/10.1080/07474938.2023.2217077 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:42:y:2023:i:6:p:540-555 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2215034_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20 Author-Name: Xiaohu Wang Author-X-Name-First: Xiaohu Author-X-Name-Last: Wang Author-Name: Jun Yu Author-X-Name-First: Jun Author-X-Name-Last: Yu Title: Latent local-to-unity models Abstract: The article studies a class of state-space models where the state equation is a local-to-unity process. The parameter of interest is the persistence parameter of the latent process. The large sample theory for the least squares (LS) estimator and an instrumental variable (IV) estimator of the persistent parameter in the autoregressive (AR) representation of the model is developed under two sets of conditions. In the first set of conditions, the measurement error is independent and identically distributed, and the error term in the state equation is stationary and fractionally integrated with memory parameter d∈(−0.5,0.5). For both estimators, the convergence rate and the asymptotic distribution crucially depend on d. The LS estimator has a severe downward bias, which is aggravated even more by the measurement error when d≤0. The IV estimator eliminates the effects of the measurement error and reduces the bias. In the second set of conditions, the measurement error is independent but not necessarily identically distributed, and the error term in the state equation is strongly mixing. In this case, the IV estimator still leads to a smaller bias than the LS estimator. Special cases of our models and results in relation to those in the literature are discussed. Journal: Econometric Reviews Pages: 586-611 Issue: 7 Volume: 42 Year: 2023 Month: 8 X-DOI: 10.1080/07474938.2023.2215034 File-URL: http://hdl.handle.net/10.1080/07474938.2023.2215034 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:42:y:2023:i:7:p:586-611 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2219183_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20 Author-Name: Yining Chen Author-X-Name-First: Yining Author-X-Name-Last: Chen Author-Name: Hudson S. Torrent Author-X-Name-First: Hudson S. Author-X-Name-Last: Torrent Author-Name: Flavio A. Ziegelmann Author-X-Name-First: Flavio A. Author-X-Name-Last: Ziegelmann Title: Robust nonparametric frontier estimation in two steps Abstract: We propose a robust methodology for estimating production frontiers with multi-dimensional input via a two-step nonparametric regression, in which we estimate the level and shape of the frontier before shifting it to an appropriate position. Our main contribution is to derive a novel frontier estimation method under a variety of flexible models which is robust to the presence of outliers and possesses some inherent advantages over traditional frontier estimators. Our approach may be viewed as a simplification, yet a generalization, of those proposed by Martins-Filho and coauthors, who estimate frontier surfaces in three steps. In particular, outliers, as well as commonly seen shape constraints of the frontier surfaces, such as concavity and monotonicity, can be straightforwardly handled by our estimation procedure. We show consistency and asymptotic distributional theory of our resulting estimators under standard assumptions in the multi-dimensional input setting. The competitive finite-sample performances of our estimators are highlighted in both simulation studies and empirical data analysis. Journal: Econometric Reviews Pages: 612-634 Issue: 7 Volume: 42 Year: 2023 Month: 8 X-DOI: 10.1080/07474938.2023.2219183 File-URL: http://hdl.handle.net/10.1080/07474938.2023.2219183 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:42:y:2023:i:7:p:612-634 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2213605_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20 Author-Name: Yundong Tu Author-X-Name-First: Yundong Author-X-Name-Last: Tu Author-Name: Xinling Xie Author-X-Name-First: Xinling Author-X-Name-Last: Xie Title: Forecasting vector autoregressions with mixed roots in the vicinity of unity Abstract: This article evaluates the forecast performance of model averaging forecasts in a nonstationary vector autoregression with mixed roots in the vicinity of unity. The deviation from unit root allows for local to unity, moderate deviation from unity and strong unit root, and the direction of such deviation could be from either the stationary or the explosive side. We provide a theoretical foundation for comparison among various forecasts, including the least squares estimator, the constrained estimator imposing the unit root constraint, and the selection or average over these two basic estimators. Furthermore, three new types of estimators are constructed, i.e., the bagging versions of the pretest estimator, the Mallows-pretest estimator that marries the Mallows averaging criterion and the Wald test, and the Mallows-bagging estimator that combines the Mallows averaging criterion and bagging technique. The asymptotic risks are shown to depend on the local parameters, which are not consistently estimable. Via Monte Carlo simulations, graphic comparisons indicate that the Mallows averaging estimator has both robust and outstanding forecasting performance. Model averaging over the vector autoregressive lag order is further considered to address the issue of model uncertainty in the lag specification. Finite sample simulations show that the Mallows averaging estimator performs superior to other frequently used selection and averaging methods. The application to forecasting the financial indices popularly used in the predictive regression further illustrates the practical merit of the proposed estimator. Journal: Econometric Reviews Pages: 556-585 Issue: 7 Volume: 42 Year: 2023 Month: 8 X-DOI: 10.1080/07474938.2023.2213605 File-URL: http://hdl.handle.net/10.1080/07474938.2023.2213605 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:42:y:2023:i:7:p:556-585 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2222637_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20 Author-Name: C. Grazian Author-X-Name-First: C. Author-X-Name-Last: Grazian Author-Name: A. McInnes Author-X-Name-First: A. Author-X-Name-Last: McInnes Title: An application of copulas to OPEC’s changing influence on fossil fuel prices Abstract: This work examines how the dependence structures between energy futures asset prices differ in two periods identified before and after the 2008 global financial crisis. These two periods were characterized by a difference in the number of extraordinary meetings of OPEC countries organized to announce a change of oil production. In the period immediately following the global financial crisis, the decrease in oil prices and oil and gas demand forced OPEC countries to make frequent adjustments to the production of oil, while, since the first quarter of 2010, the recovery led to more regular meetings, with only three organized extraordinary meetings. We propose to use a copula model to study how the dependence structure among energy prices changed among the two periods. The use of copula models allows to introduce flexible and realistic models for the marginal time series; once marginal parameters are estimated, the estimates are used to fit several copula models for all asset combinations. Model selection techniques based on information criteria are implemented to choose the best models both for the univariate asset prices series and for the distribution of co-movements. The changes in the dependence structure of couple of assets are investigated through copula functionals and their uncertainty estimated through a bootstrapping method. We find the strength of dependence between asset combinations considerably differ between the two periods, showing a significant decrease for all the pairs of assets. Journal: Econometric Reviews Pages: 676-699 Issue: 8 Volume: 42 Year: 2023 Month: 9 X-DOI: 10.1080/07474938.2023.2222637 File-URL: http://hdl.handle.net/10.1080/07474938.2023.2222637 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:42:y:2023:i:8:p:676-699 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2224658_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20 Author-Name: Helmut Farbmacher Author-X-Name-First: Helmut Author-X-Name-Last: Farbmacher Author-Name: Harald Tauchmann Author-X-Name-First: Harald Author-X-Name-Last: Tauchmann Title: Linear fixed-effects estimation with nonrepeated outcomes Abstract: We demonstrate that popular linear fixed-effects panel-data estimators are biased and inconsistent when applied in a discrete-time hazard setting, even if the data-generating process is consistent with the linear model. The bias is not just survival bias, but originates from the impossibility to transform the model such that the remaining disturbance term becomes conditional mean independent of the explanatory variables. The bias is hence present even in the absence of unobserved heterogeneity. We discuss instrumental variables estimation, using first-differences of the explanatory variables as instruments, as alternative estimation strategy. Monte Carlo simulations and an empirical application substantiate our theoretical results. Journal: Econometric Reviews Pages: 635-654 Issue: 8 Volume: 42 Year: 2023 Month: 9 X-DOI: 10.1080/07474938.2023.2224658 File-URL: http://hdl.handle.net/10.1080/07474938.2023.2224658 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:42:y:2023:i:8:p:635-654 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2225947_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20 Author-Name: Fang Lu Author-X-Name-First: Fang Author-X-Name-Last: Lu Author-Name: Sisheng Liu Author-X-Name-First: Sisheng Author-X-Name-Last: Liu Author-Name: Jing Yang Author-X-Name-First: Jing Author-X-Name-Last: Yang Author-Name: Xuewen Lu Author-X-Name-First: Xuewen Author-X-Name-Last: Lu Title: Automatic variable selection for semiparametric spatial autoregressive model Abstract: This article studies the generalized method of moment estimation of semiparametric varying coefficient partially linear spatial autoregressive model. The technique of profile least squares is employed and all estimators have explicit formulas which are computationally convenient. We derive the limiting distributions of the proposed estimators for both parametric and non parametric components. Variable selection procedures based on smooth-threshold estimating equations are proposed to automatically eliminate irrelevant parameters and zero varying coefficient functions. Compared to the alternative approaches based on shrinkage penalty, the new method is easily implemented. Oracle properties of the resulting estimators are established. Large amounts of Monte Carlo simulations confirm our theories and demonstrate that the estimators perform reasonably well in finite samples. We also apply the novel methods to an empirical data analysis. Journal: Econometric Reviews Pages: 655-675 Issue: 8 Volume: 42 Year: 2023 Month: 9 X-DOI: 10.1080/07474938.2023.2225947 File-URL: http://hdl.handle.net/10.1080/07474938.2023.2225947 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:42:y:2023:i:8:p:655-675 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2222634_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20 Author-Name: David I. Harvey Author-X-Name-First: David I. Author-X-Name-Last: Harvey Author-Name: Stephen J. Leybourne Author-X-Name-First: Stephen J. Author-X-Name-Last: Leybourne Author-Name: A. M. Robert Taylor Author-X-Name-First: A. M. Robert Author-X-Name-Last: Taylor Title: Improved tests for stock return predictability Abstract: Predictive regression methods are widely used to examine the predictability of (excess) stock returns by lagged financial variables characterized by unknown degrees of persistence and endogeneity. We develop a new hybrid test for predictability in these circumstances based on simple regression t-statistics. Where the predictor is endogenous, the optimal, but infeasible, test for predictability is based on the t-statistic on the lagged predictor in the basic predictive regression augmented with the current period innovation driving the predictor. We propose a feasible version of this augmented test, designed for the case where the predictor is an endogenous near-unit root process, using a GLS-based estimate of the innovation used in the infeasible test regression. The limiting null distribution of this statistic depends on both the endogeneity correlation parameter and the local-to-unity parameter characterizing the predictor. A method for obtaining asymptotic critical values is discussed and response surfaces are provided. We compare the asymptotic power properties of the feasible augmented test with those of a (non augmented) t-test recently considered in Harvey et al. and show that the augmented test is more powerful in the strongly persistent predictor case. We then propose using a weighted combination of the augmented statistic and the t-statistic of Harvey et al., where the weights are obtained using the p-values from a unit root test on the predictor. We find this can further improve asymptotic power in cases where the predictor has persistence at or close to that of a unit root process. Our final hybrid testing procedure then embeds the weighted statistic within a switching-based procedure which makes use of a standard predictive regression t-test, compared with standard normal critical values, when there is evidence for the predictor being weakly persistent. Monte Carlo simulations suggest that overall our new hybrid test displays superior finite sample performance to comparable extant tests. Journal: Econometric Reviews Pages: 834-861 Issue: 9-10 Volume: 42 Year: 2023 Month: 11 X-DOI: 10.1080/07474938.2023.2222634 File-URL: http://hdl.handle.net/10.1080/07474938.2023.2222634 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:42:y:2023:i:9-10:p:834-861 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2222633_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20 Author-Name: H. Peter Boswijk Author-X-Name-First: H. Author-X-Name-Last: Peter Boswijk Author-Name: Giuseppe Cavaliere Author-X-Name-First: Giuseppe Author-X-Name-Last: Cavaliere Author-Name: Luca De Angelis Author-X-Name-First: Luca Author-X-Name-Last: De Angelis Author-Name: A. M. Robert Taylor Author-X-Name-First: A. M. Robert Author-X-Name-Last: Taylor Title: Adaptive information-based methods for determining the co-integration rank in heteroskedastic VAR models Abstract: Standard methods, such as sequential procedures based on Johansen’s (pseudo-)likelihood ratio (PLR) test, for determining the co-integration rank of a vector autoregressive (VAR) system of variables integrated of order one can be significantly affected, even asymptotically, by unconditional heteroskedasticity (non-stationary volatility) in the data. Known solutions to this problem include wild bootstrap implementations of the PLR test or the use of an information criterion, such as the BIC, to select the co-integration rank. Although asymptotically valid in the presence of heteroskedasticity, these methods can display very low finite sample power under some patterns of non-stationary volatility. In particular, they do not exploit potential efficiency gains that could be realized in the presence of non-stationary volatility by using adaptive inference methods. Under the assumption of a known autoregressive lag length, Boswijk and Zu develop adaptive PLR test based methods using a non-parametric estimate of the covariance matrix process. It is well-known, however, that selecting an incorrect lag length can significantly impact on the efficacy of both information criteria and bootstrap PLR tests to determine co-integration rank in finite samples. We show that adaptive information criteria-based approaches can be used to estimate the autoregressive lag order to use in connection with bootstrap adaptive PLR tests, or to jointly determine the co-integration rank and the VAR lag length and that in both cases they are weakly consistent for these parameters in the presence of non-stationary volatility provided standard conditions hold on the penalty term. Monte Carlo simulations are used to demonstrate the potential gains from using adaptive methods and an empirical application to the U.S. term structure is provided. Journal: Econometric Reviews Pages: 725-757 Issue: 9-10 Volume: 42 Year: 2023 Month: 11 X-DOI: 10.1080/07474938.2023.2222633 File-URL: http://hdl.handle.net/10.1080/07474938.2023.2222633 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:42:y:2023:i:9-10:p:725-757 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2241223_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20 Author-Name: Panayiotis C. Andreou Author-X-Name-First: Panayiotis C. Author-X-Name-Last: Andreou Author-Name: Sofia Anyfantaki Author-X-Name-First: Sofia Author-X-Name-Last: Anyfantaki Author-Name: Esfandiar Maasoumi Author-X-Name-First: Esfandiar Author-X-Name-Last: Maasoumi Author-Name: Carlo Sala Author-X-Name-First: Carlo Author-X-Name-Last: Sala Title: Extremal quantiles and stock price crashes Abstract: We employ extreme value theory to identify stock price crashes, featuring low-probability events that produce large, idiosyncratic negative outliers in the conditional distribution. Traditional methods employ approximations under Gaussian assumptions and central moments. This is inherently imprecise and susceptible to misspecifications, especially for tail events. We instead propose new definitions and measures for crash risk based on conditional extremal quantiles (CEQ) of idiosyncratic stock returns. CEQ provide information on quantile-specific impact of covariates, and shed light on prior empirical puzzles and shortcomings in identifying crashes. Additionally, to capture the magnitude of crashes, we provide an expected shortfall analysis of the losses due to crash. Our findings have important implications for a burgeoning literature in financial economics that relies on traditional approximations. Journal: Econometric Reviews Pages: 703-724 Issue: 9-10 Volume: 42 Year: 2023 Month: 11 X-DOI: 10.1080/07474938.2023.2241223 File-URL: http://hdl.handle.net/10.1080/07474938.2023.2241223 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:42:y:2023:i:9-10:p:703-724 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2243696_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20 Author-Name: Esfandiar Maasoumi Author-X-Name-First: Esfandiar Author-X-Name-Last: Maasoumi Author-Name: Robert Taylor Author-X-Name-First: Robert Author-X-Name-Last: Taylor Title: In memory of Michael McAleer: special issue of Econometric Reviews Journal: Econometric Reviews Pages: 700-702 Issue: 9-10 Volume: 42 Year: 2023 Month: 11 X-DOI: 10.1080/07474938.2023.2243696 File-URL: http://hdl.handle.net/10.1080/07474938.2023.2243696 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:42:y:2023:i:9-10:p:700-702 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2221558_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20 Author-Name: Chaoyi Chen Author-X-Name-First: Chaoyi Author-X-Name-Last: Chen Author-Name: Thanasis Stengos Author-X-Name-First: Thanasis Author-X-Name-Last: Stengos Author-Name: Yiguo Sun Author-X-Name-First: Yiguo Author-X-Name-Last: Sun Title: Endogeneity in semiparametric threshold regression models with two threshold variables Abstract: This article considers a semiparametric threshold regression model with two threshold variables. The proposed model allows endogenous threshold variables and endogenous slope regressors. Under the diminishing threshold effects framework, we derive consistency and asymptotic results of our proposed estimator for weakly dependent data. We study the finite sample performance of our proposed estimator via small Monte Carlo simulations and apply our model to classify economic growth regimes based on both national public debt and national external debt. Journal: Econometric Reviews Pages: 758-779 Issue: 9-10 Volume: 42 Year: 2023 Month: 11 X-DOI: 10.1080/07474938.2023.2221558 File-URL: http://hdl.handle.net/10.1080/07474938.2023.2221558 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:42:y:2023:i:9-10:p:758-779 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2227019_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20 Author-Name: Feifei Guo Author-X-Name-First: Feifei Author-X-Name-Last: Guo Author-Name: Shiqing Ling Author-X-Name-First: Shiqing Author-X-Name-Last: Ling Title: Inference for the VEC(1) model with a heavy-tailed linear process errors* Abstract: This article studies the first-order vector error correction (VEC(1)) model when its noise is a linear process of independent and identically distributed (i.i.d.) heavy-tailed random vectors with a tail index α∈(0,2) . We show that the rate of convergence of the least squares estimator (LSE) related to the long-run parameters is n (sample size) and its limiting distribution is a stochastic integral in terms of two stable random processes, while the LSE related to the short-term parameters is not consistent. We further propose an automated approach via adaptive shrinkage techniques to determine the cointegrating rank in the VEC(1) model. It is demonstrated that the cointegration rank r0 can be consistently selected despite the fact that the LSE related to the short-term parameters is not consistently estimable when the tail index α∈(1,2) . Simulation studies are carried out to evaluate the performance of the proposed procedure in finite samples. Last, we use our techniques to explore the long-run and short-run behavior of the monthly prices of wheat, corn, and wheat flour in the United States. Journal: Econometric Reviews Pages: 806-833 Issue: 9-10 Volume: 42 Year: 2023 Month: 11 X-DOI: 10.1080/07474938.2023.2227019 File-URL: http://hdl.handle.net/10.1080/07474938.2023.2227019 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:42:y:2023:i:9-10:p:806-833 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2224175_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20 Author-Name: Kees Jan van Garderen Author-X-Name-First: Kees Jan Author-X-Name-Last: van Garderen Title: Forecasting Levels in Loglinear Unit Root Models Abstract: This article considers unbiased prediction of levels when data series are modeled as a random walk with drift and other exogenous factors after taking natural logs. We derive the unique unbiased predictors for growth and its variance. Derivation of level forecasts is more involved because the last observation enters the conditional expectation and is highly correlated with the parameter estimates, even asymptotically. This leads to conceptual questions regarding conditioning on endogenous variables. We prove that no conditionally unbiased forecast exists. We derive forecasts that are unconditionally unbiased and take into account estimation uncertainty, non linearity of the transformations, and the correlation between the last observation and estimate, which is quantitatively more important than estimation uncertainty and future disturbances together. The exact unbiased forecasts are shown to have lower Mean Squared Forecast Error (MSFE) than usual forecasts. The results are applied to Bitcoin price levels and a disaggregated eight sector model of UK industrial production. Journal: Econometric Reviews Pages: 780-805 Issue: 9-10 Volume: 42 Year: 2023 Month: 11 X-DOI: 10.1080/07474938.2023.2224175 File-URL: http://hdl.handle.net/10.1080/07474938.2023.2224175 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:42:y:2023:i:9-10:p:780-805 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2237274_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20 Author-Name: Zhongfang He Author-X-Name-First: Zhongfang Author-X-Name-Last: He Title: Time-dependent shrinkage of time-varying parameter regression models Abstract: This article studies the time-varying parameter (TVP) regression model in which the regression coefficients are random walk latent states with time-dependent conditional variances. This TVP model is flexible to accommodate a wide variety of time variation patterns but requires effective shrinkage on the state variances to avoid over-fitting. A Bayesian shrinkage prior is proposed based on reparameterization that translates the variance shrinkage problem into a variable shrinkage one in a conditionally linear regression with fixed coefficients. The proposed prior allows strong shrinkage for the state variances while maintaining the flexibility to accommodate local signals. A Bayesian estimation method is developed that employs the ancilarity-sufficiency interweaving strategy to boost sampling efficiency. Simulation study and an empirical application to forecast inflation rate illustrate the benefits of the proposed approach. Journal: Econometric Reviews Pages: 1-29 Issue: 1 Volume: 43 Year: 2024 Month: 1 X-DOI: 10.1080/07474938.2023.2237274 File-URL: http://hdl.handle.net/10.1080/07474938.2023.2237274 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:43:y:2024:i:1:p:1-29 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2280825_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20 Author-Name: Chaoxia Yuan Author-X-Name-First: Chaoxia Author-X-Name-Last: Yuan Author-Name: Fang Fang Author-X-Name-First: Fang Author-X-Name-Last: Fang Author-Name: Jialiang Li Author-X-Name-First: Jialiang Author-X-Name-Last: Li Title: Model averaging for generalized linear models in diverging model spaces with effective model size Abstract: While plenty of frequentist model averaging methods have been proposed, existing weight selection criteria for generalized linear models (GLM) are usually based on a model size penalized Kullback-Leibler (KL) loss or simply cross-validation. In this article, when the data is generated from an exponential distribution, we propose a novel model averaging approach for GLM motivated by an asymptotically unbiased estimator of the KL loss penalized by an “effective model size” that incorporates the model misspecification. When all the candidate models are misspecified, the proposed method achieves asymptotic optimality while allowing both the number of candidate models and the dimension of covariates to diverging. Furthermore, when correct models are included in the candidate model set, we prove that the weight of wrong candidate models converges to zero, and hence the weighted regression coefficient estimator is consistent. Simulation studies and two real-data examples demonstrate the advantage of our new method over the existing frequentist model averaging methods. Journal: Econometric Reviews Pages: 71-96 Issue: 1 Volume: 43 Year: 2024 Month: 1 X-DOI: 10.1080/07474938.2023.2280825 File-URL: http://hdl.handle.net/10.1080/07474938.2023.2280825 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:43:y:2024:i:1:p:71-96 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2246823_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20 Author-Name: Taoufik Bouezmarni Author-X-Name-First: Taoufik Author-X-Name-Last: Bouezmarni Author-Name: Mohamed Doukali Author-X-Name-First: Mohamed Author-X-Name-Last: Doukali Author-Name: Abderrahim Taamouti Author-X-Name-First: Abderrahim Author-X-Name-Last: Taamouti Title: Testing Granger non-causality in expectiles Abstract: This article aims to derive a consistent test of Granger causality at a given expectile. We also propose a sup-Wald test for jointly testing Granger causality at all expectiles that has the correct asymptotic size and power properties. Expectiles have the advantage of capturing similar information as quantiles, but they also have the merit of being much more straightforward to use than quantiles, since they are defined as least squares analog of quantiles. Studying Granger causality in expectiles is practically simpler and allows us to examine the causality at all levels of the conditional distribution. Moreover, testing Granger causality at all expectiles provides a sufficient condition for testing Granger causality in distribution. A Monte Carlo simulation study reveals that our tests have good finite-sample size and power properties for a variety of data-generating processes and different sample sizes. Finally, we provide two empirical applications to illustrate the usefulness of the proposed tests. Journal: Econometric Reviews Pages: 30-51 Issue: 1 Volume: 43 Year: 2024 Month: 1 X-DOI: 10.1080/07474938.2023.2246823 File-URL: http://hdl.handle.net/10.1080/07474938.2023.2246823 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:43:y:2024:i:1:p:30-51 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2255438_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20 Author-Name: Giampiero Marra Author-X-Name-First: Giampiero Author-X-Name-Last: Marra Author-Name: Rosalba Radice Author-X-Name-First: Rosalba Author-X-Name-Last: Radice Author-Name: David Zimmer Author-X-Name-First: David Author-X-Name-Last: Zimmer Title: A unifying switching regime regression framework with applications in health economics Abstract: Motivated by three health economics-related case studies, we propose a unifying and flexible regression modeling framework that involves regime switching. The proposal can handle the peculiar distributional shapes of the considered outcomes via a vast range of marginal distributions, allows for a wide variety of copula dependence structures and permits to specify all model parameters (including the dependence parameters) as flexible functions of covariate effects. The algorithm is based on a computationally efficient and stable penalized maximum likelihood estimation approach. The proposed modeling framework is employed in three applications in health economics, that use data from the Medical Expenditure Panel Survey, where novel patterns are uncovered. The framework has been incorporated in the R package GJRM, hence allowing users to fit the desired model(s) and produce easy-to-interpret numerical and visual summaries. Journal: Econometric Reviews Pages: 52-70 Issue: 1 Volume: 43 Year: 2024 Month: 1 X-DOI: 10.1080/07474938.2023.2255438 File-URL: http://hdl.handle.net/10.1080/07474938.2023.2255438 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:43:y:2024:i:1:p:52-70 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2315543_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a Author-Name: The Editors Title: ANNOUNCEMENT Journal: Econometric Reviews Pages: 97-97 Issue: 2-4 Volume: 43 Year: 2024 Month: 4 X-DOI: 10.1080/07474938.2024.2315543 File-URL: http://hdl.handle.net/10.1080/07474938.2024.2315543 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:43:y:2024:i:2-4:p:97-97 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2310987_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a Author-Name: Akanksha Negi Author-X-Name-First: Akanksha Author-X-Name-Last: Negi Author-Name: Wooldridge Jeffrey M. Author-X-Name-First: Wooldridge Author-X-Name-Last: Jeffrey M. Title: Doubly robust estimation of multivariate fractional outcome means with multivalued treatments Abstract: This article suggests a doubly robust method of estimating potential outcome means for multivariate fractional outcomes when the treatment of interest is unconfounded and can take more than two values. The method involves maximizing a propensity score weighted multinomial quasi-log-likelihood function with a multinomial logit conditional mean. We show that this estimator, which we call weighted multivariate fractional logit (wmflogit), consistently estimates the potential outcome means if either the propensity score model or the conditional mean model is misspecified. Our simulations demonstrate this double robustness property for the case of shares generated using a Dirichlet distribution. Finally, we advocate for the use of wmflogit by applying it to estimate time-use shares of women participating in the Mexican conditional cash transfer program, Progresa, using Stata’s fmlogit command developed by Buis. Journal: Econometric Reviews Pages: 175-196 Issue: 2-4 Volume: 43 Year: 2024 Month: 4 X-DOI: 10.1080/07474938.2024.2310987 File-URL: http://hdl.handle.net/10.1080/07474938.2024.2310987 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:43:y:2024:i:2-4:p:175-196 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2292383_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a Author-Name: Ignace De Vos Author-X-Name-First: Ignace Author-X-Name-Last: De Vos Author-Name: Gerdie Everaert Author-X-Name-First: Gerdie Author-X-Name-Last: Everaert Author-Name: Vasilis Sarafidis Author-X-Name-First: Vasilis Author-X-Name-Last: Sarafidis Title: A method to evaluate the rank condition for CCE estimators Abstract: We develop a binary classifier to evaluate whether the rank condition (RC) is satisfied or not for the Common Correlated Effects (CCE) estimator. The RC postulates that the number of unobserved factors, m, is not larger than the rank of the unobserved matrix of average factor loadings, ϱ. When this condition fails, the CCE estimator is inconsistent, in general. Despite its importance, to date this rank condition could not be verified. The difficulty lies in the fact that factor loadings are unobserved, such that ϱ cannot be directly determined. The key insight in this article is that ϱ can be consistently estimated with existing techniques through the matrix of cross-sectional averages of the data. Similarly, m can be estimated consistently from the data using existing methods. Thus, a binary classifier, constructed by comparing estimates of m and ϱ, correctly determines whether the RC is satisfied or not as (N,T)→∞. We illustrate the practical relevance of testing the RC by studying the effect of the Dodd-Frank Act on bank profitability. The RC classifier reveals that the rank condition fails for a subperiod of the sample, in which case the estimated effect of bank size on profitability appears to be biased upwards. Journal: Econometric Reviews Pages: 123-155 Issue: 2-4 Volume: 43 Year: 2024 Month: 4 X-DOI: 10.1080/07474938.2023.2292383 File-URL: http://hdl.handle.net/10.1080/07474938.2023.2292383 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:43:y:2024:i:2-4:p:123-155 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2306069_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a Author-Name: Ramses H. Abul Naga Author-X-Name-First: Ramses H. Author-X-Name-Last: Abul Naga Author-Name: Christopher Stapenhurst Author-X-Name-First: Christopher Author-X-Name-Last: Stapenhurst Author-Name: Gaston Yalonetzky Author-X-Name-First: Gaston Author-X-Name-Last: Yalonetzky Title: Inferring inequality: Testing for median-preserving spreads in ordinal data Abstract: The median-preserving spread (MPS) ordering for ordinal variables has become ubiquitous in the inequality literature. We devise statistical tests of the hypothesis that a distribution G is not an MPS of a distribution F. Rejecting this hypothesis enables the conclusion that G is more unequal than F according to the MPS criterion. Monte Carlo simulations and novel graphical techniques show that a simple, asymptotic Z test is sufficient for most applications. We illustrate our tests with two applications: happiness inequality in the US and self-assessed health in Europe. Journal: Econometric Reviews Pages: 156-174 Issue: 2-4 Volume: 43 Year: 2024 Month: 4 X-DOI: 10.1080/07474938.2024.2306069 File-URL: http://hdl.handle.net/10.1080/07474938.2024.2306069 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:43:y:2024:i:2-4:p:156-174 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2314092_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a Author-Name: Lukang Huang Author-X-Name-First: Lukang Author-X-Name-Last: Huang Author-Name: Wei Huang Author-X-Name-First: Wei Author-X-Name-Last: Huang Author-Name: Oliver Linton Author-X-Name-First: Oliver Author-X-Name-Last: Linton Author-Name: Zheng Zhang Author-X-Name-First: Zheng Author-X-Name-Last: Zhang Title: Nonparametric estimation of mediation effects with a general treatment Abstract: To investigate causal mechanisms, causal mediation analysis decomposes the total treatment effect into the natural direct and indirect effects. This article examines the estimation of the direct and indirect effects in a general treatment effect model, where the treatment can be binary, multi-valued, continuous, or a mixture. We propose generalized weighting estimators with weights estimated by solving an expanding set of equations. Under some sufficient conditions, we show that the proposed estimators are consistent and asymptotically normal. Specifically, when the treatment is discrete, the proposed estimators attain semiparametric efficiency bounds. Meanwhile, when the treatment is continuous, the convergence rates of the proposed estimators are slower than N−1/2; however, they are still more efficient than those constructed from the true weighting function. A simulation study reveals that our estimators exhibit satisfactory finite-sample performance, while an application shows their practical value. Journal: Econometric Reviews Pages: 215-237 Issue: 2-4 Volume: 43 Year: 2024 Month: 4 X-DOI: 10.1080/07474938.2024.2314092 File-URL: http://hdl.handle.net/10.1080/07474938.2024.2314092 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:43:y:2024:i:2-4:p:215-237 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2312288_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a Author-Name: David M. Kaplan Author-X-Name-First: David M. Author-X-Name-Last: Kaplan Author-Name: Xin Liu Author-X-Name-First: Xin Author-X-Name-Last: Liu Title: Confidence intervals for intentionally biased estimators Abstract: We propose and study three confidence intervals (CIs) centered at an estimator that is intentionally biased to reduce mean squared error. The first CI simply uses an unbiased estimator’s standard error; compared to centering at the unbiased estimator, this CI has higher coverage probability for confidence levels above 91. 7%, even if the biased and unbiased estimators have equal mean squared error. The second CI trades some of this “excess” coverage for shorter length. The third CI is centered at a convex combination of the two estimators to further reduce length. Practically, these CIs apply broadly and are simple to compute. Journal: Econometric Reviews Pages: 197-214 Issue: 2-4 Volume: 43 Year: 2024 Month: 4 X-DOI: 10.1080/07474938.2024.2312288 File-URL: http://hdl.handle.net/10.1080/07474938.2024.2312288 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:43:y:2024:i:2-4:p:197-214 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2292377_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a Author-Name: Dalei Yu Author-X-Name-First: Dalei Author-X-Name-Last: Yu Author-Name: Heng Lian Author-X-Name-First: Heng Author-X-Name-Last: Lian Author-Name: Yuying Sun Author-X-Name-First: Yuying Author-X-Name-Last: Sun Author-Name: Xinyu Zhang Author-X-Name-First: Xinyu Author-X-Name-Last: Zhang Author-Name: Yongmiao Hong Author-X-Name-First: Yongmiao Author-X-Name-Last: Hong Title: Post-averaging inference for optimal model averaging estimator in generalized linear models Abstract: This article considers the problem of post-averaging inference for optimal model averaging estimators in a generalized linear model (GLM). We establish the asymptotic distributions of optimal model averaging estimators for GLMs. The asymptotic distributions of the model averaging estimators are nonstandard, depending on the configuration of the penalty term in the weight choice criterion. We also propose a feasible simulation-based confidence interval estimator and investigate its asymptotic properties rigorously. Monte Carlo simulations verify the usefulness of our theoretical results, and the proposed methods are employed to analyze a stock car racing dataset. Journal: Econometric Reviews Pages: 98-122 Issue: 2-4 Volume: 43 Year: 2024 Month: 4 X-DOI: 10.1080/07474938.2023.2292377 File-URL: http://hdl.handle.net/10.1080/07474938.2023.2292377 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:43:y:2024:i:2-4:p:98-122 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2334119_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a Author-Name: Juan Lin Author-X-Name-First: Juan Author-X-Name-Last: Lin Author-Name: Ximing Wu Author-X-Name-First: Ximing Author-X-Name-Last: Wu Title: A hybrid nonparametric multivariate density estimator with applications to risk management Abstract: Multivariate density estimation is plagued by the curse of dimensionality in theory and practice. We propose a hybrid density estimator of a multivariate density f that combines the strengths of the kernel estimator and the exponential series estimator. This estimator refines a preliminary kernel estimate f̂0 with a multiplicative correction that estimates the ratio r=f/f̂0 with an exponential series estimator. Thanks to the consistency of the pilot estimate, the coefficients of the series expansion tend to approach zero asymptotically. Accordingly, we design a thresholding method for basis function selection. A major obstacle of multivariate exponential series estimator is the calculation of its normalization factor. We resolve this difficulty with Monte Carlo integration, using the pilot kernel estimate as the trial density for importance sampling. This approach greatly enhances the practicality of the hybrid estimator. Numerical simulations demonstrate the good finite sample performance of the hybrid estimator. We present one empirical application in financial risk management. Journal: Econometric Reviews Pages: 301-318 Issue: 5 Volume: 43 Year: 2024 Month: 5 X-DOI: 10.1080/07474938.2024.2334119 File-URL: http://hdl.handle.net/10.1080/07474938.2024.2334119 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:43:y:2024:i:5:p:301-318 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2328905_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a Author-Name: Jun Cai Author-X-Name-First: Jun Author-X-Name-Last: Cai Author-Name: William C. Horrace Author-X-Name-First: William C. Author-X-Name-Last: Horrace Author-Name: Yoonseok Lee Author-X-Name-First: Yoonseok Author-X-Name-Last: Lee Title: Identification and estimation of panel semiparametric conditional heteroskedastic frontiers with dynamic inefficiency Abstract: We study a semiparametric panel stochastic frontier model with nonseparable unobserved heterogeneity, which allows for time-varying conditional heteroskedastic productivity components. It does not require distributional assumptions on random noise except conditional symmetry. We utilize conditional characteristic functions from Kotlarski’s Lemma to derive new moment conditions that yield the identification of the heteroskedastic variance parameters of inefficiency and random noise. Identification only requires a panel with three periods for serially correlated inefficiency. A nonparametric estimation procedure is also developed for the conditional variance of inefficiency, and its convergence rate is established. Monte Carlo simulation shows that the estimator is robust to misspecification of inefficiency distributions. Journal: Econometric Reviews Pages: 238-268 Issue: 5 Volume: 43 Year: 2024 Month: 5 X-DOI: 10.1080/07474938.2024.2328905 File-URL: http://hdl.handle.net/10.1080/07474938.2024.2328905 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:43:y:2024:i:5:p:238-268 Template-Type: ReDIF-Article 1.0 # input file: LECR_A_2330127_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a Author-Name: Zhongfang He Author-X-Name-First: Zhongfang Author-X-Name-Last: He Title: Locally time-varying parameter regression Abstract: I discuss a framework to allow dynamic sparsity in time-varying parameter regression models. The conditional variances of the innovations of time-varying parameters are time varying and equal to zero adaptively via thresholding. The resulting model allows the dynamics of the time-varying parameters to mix over different frequencies of parameter changes in a data driven way and permits great flexibility while achieving model parsimony. A convenient strategy is discussed to infer if each coefficient is static or dynamic and, if dynamic, how frequent the parameter change is. An MCMC scheme is developed for model estimation. The performance of the proposed approach is illustrated in studies of both simulated and real economic data. Journal: Econometric Reviews Pages: 269-300 Issue: 5 Volume: 43 Year: 2024 Month: 5 X-DOI: 10.1080/07474938.2024.2330127 File-URL: http://hdl.handle.net/10.1080/07474938.2024.2330127 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:taf:emetrv:v:43:y:2024:i:5:p:269-300