{smcl} {* *! version 1.1.1 16mar2021}{...} {* *! Sebastian Kripfganz, www.kripfganz.de}{...} {* *! Jan F. Kiviet, sites.google.com/site/homepagejfk/}{...} {vieweralsosee "kinkyreg" "help kinkyreg"}{...} {vieweralsosee "" "--"}{...} {vieweralsosee "[R] predict" "help predict"}{...} {vieweralsosee "[R] regress postestimation" "help regress_postestimation"}{...} {viewerjumpto "Postestimation commands" "kinkyreg_postestimation##description"}{...} {viewerjumpto "predict" "kinkyreg_postestimation##predict"}{...} {viewerjumpto "estat" "kinkyreg_postestimation##estat"}{...} {viewerjumpto "Example" "kinkyreg_postestimation##example"}{...} {viewerjumpto "Authors" "kinkyreg_postestimation##authors"}{...} {viewerjumpto "References" "kinkyreg_postestimation##references"}{...} {title:Title} {p2colset 5 32 34 2}{...} {p2col :{bf:kinkyreg postestimation} {hline 2}}Postestimation tools for kinkyreg{p_end} {p2colreset}{...} {marker description}{...} {title:Postestimation commands} {pstd} The following postestimation commands are of special interest after {cmd:kinkyreg}: {synoptset 14}{...} {p2coldent:Command}Description{p_end} {synoptline} {synopt:{helpb kinkyreg postestimation##estat:estat test}}perform test of linear hypotheses{p_end} {synopt:{helpb kinkyreg postestimation##estat:estat exclusion}}perform test of exclusion restrictions{p_end} {synopt:{helpb kinkyreg postestimation##estat:estat reset}}perform the Ramsey regression specification error test{p_end} {synopt:{helpb kinkyreg postestimation##estat:estat hettest}}perform test for heteroskedasticity{p_end} {synopt:{helpb kinkyreg postestimation##estat:estat durbinalt}}perform Durbin's alternative test for serial correlation{p_end} {synopt:{helpb kinkyreg postestimation##estat:estat rcr}}compute sensitivity parameters for RCR estimation{p_end} {synoptline} {p2colreset}{...} {pstd} The following standard postestimation commands are available after {cmd:kinkyreg} with option {opt correlation(#)}: {synoptset 14}{...} {p2coldent:Command}Description{p_end} {synoptline} {p2col:{helpb estat}}VCE and estimation sample summary{p_end} INCLUDE help post_estimates INCLUDE help post_hausman INCLUDE help post_lincom INCLUDE help post_nlcom {synopt:{helpb kinkyreg postestimation##predict:predict}}predictions, residuals, influence statistics, and other diagnostic measures{p_end} INCLUDE help post_predictnl INCLUDE help post_test INCLUDE help post_testnl {synoptline} {p2colreset}{...} {marker predict}{...} {title:Syntax for predict} {p 8 16 2} {cmd:predict} {dtype} {newvar} {ifin} [{cmd:,} {it:{help kinkyreg_postestimation##predict_statistics:statistic}}] {marker predict_statistics}{...} {synoptset 13 tabbed}{...} {synopthdr:statistic} {synoptline} {syntab:Main} {synopt:{opt xb}}calculate linear prediction; the default{p_end} {synopt:{opt r:esiduals}}calculate the residuals{p_end} {synopt:{opt stdp}}calculate standard error of the prediction{p_end} {synoptline} {p2colreset}{...} {title:Description for predict} {pstd} {cmd:predict} creates a new variable containing predictions such as fitted values, residuals, and standard errors based on the postulated endogeneity correlation specified in option {opt correlation(#)} of {cmd:kinkyreg}. {title:Options for predict} {dlgtab:Main} {phang} {opt xb} calculates the linear prediction from the fitted model; see {helpb predict##options:[R] predict}. This is the default. {phang} {opt residuals} calculates the residuals from the fitted model. {phang} {opt stdp} calculates the standard error of the linear prediction; see {helpb predict##options:[R] predict}. {marker estat}{...} {title:Syntax for estat} {phang} Test of linear hypotheses {p 8 16 2} {cmd:estat} {cmd:test} {cmd:(}{it:{help kinkyreg_postestimation##options_spec:test_spec}}{cmd:)} [{cmd:(}{it:{help kinkyreg_postestimation##options_spec:test_spec}}{cmd:)} ...] [{cmd:,} {it:{help kinkyreg_postestimation##estat_test_options:test_options}} {it:{help kinkyreg_postestimation##estat_graph_options:graph_options}}] {phang} Test of exclusion restrictions {p 8 16 2} {cmd:estat} {cmdab:excl:usion} [{varlist}] [{cmd:,} {it:{help kinkyreg_postestimation##estat_excl_options:excl_options}} {it:{help kinkyreg_postestimation##estat_graph_options:graph_options}}] {phang} Ramsey regression equation specification error test {p 8 16 2} {cmd:estat} {cmd:reset} [, {it:{help kinkyreg_postestimation##estat_reset_options:reset_options}} {it:{help kinkyreg_postestimation##estat_graph_options:graph_options}}] {phang} Tests for heteroskedasticity {p 8 16 2} {cmd:estat} {cmdab:hett:est} [{cmd:(}{varlist}{cmd:)} {cmd:(}{varlist}{cmd:)} ...] [{cmd:,} {it:{help kinkyreg_postestimation##estat_hett_options:hett_options}} {it:{help kinkyreg_postestimation##estat_graph_options:graph_options}}] {phang} Durbin's alternative test for serial correlation {p 8 16 2} {cmd:estat} {cmdab:dur:binalt} [, {it:{help kinkyreg_postestimation##estat_dur_options:dur_options}} {it:{help kinkyreg_postestimation##estat_graph_options:graph_options}}] {phang} Sensitivity parameters for relative correlation restriction estimation {p 8 16 2} {cmd:estat} {cmd:rcr} [, {it:{help kinkyreg_postestimation##estat_rcr_options:rcr_options}} {it:{help kinkyreg_postestimation##estat_graph_options:graph_options}}] {marker estat_test_options}{...} {synoptset 24 tabbed}{...} {synopthdr:test_options} {synoptline} {syntab:Model} {synopt:{it:{help test##test_options:test_options}}}standard options of the {cmd:test} command{p_end} {syntab:Reporting} {synopt:{opt corr:elation(#)}}postulated endogeneity for test output{p_end} {synoptline} {marker estat_excl_options}{...} {synoptset 24 tabbed}{...} {synopthdr:excl_options} {synoptline} {syntab:Model} {synopt:{opt nojoi:nt}}do not compute joint exclusion test{p_end} {synopt:{opt noind:ividual}}do not compute individual exclusion tests{p_end} {synopt:{opt ek:urtosis(#)}}specify kurtosis of error term{p_end} {synopt:{opt xk:urtosis(#)}}specify kurtosis of right-hand side variables{p_end} {syntab:Reporting} {synopt:{opt corr:elation(#)}}postulated endogeneity for test output{p_end} {synopt:{opt l:evel(#)}}set confidence level; default is {cmd:level(95)}{p_end} {synopt:{opt notab:le}}suppress results table{p_end} {synoptline} {marker estat_reset_options}{...} {synoptset 24 tabbed}{...} {synopthdr:reset_options} {synoptline} {syntab:Model} {synopt:{opt xb}}use fitted values; the default{p_end} {synopt:{opt rhs}}use right-hand side variables{p_end} {synopt:{opth o:rder(numlist)}}specify polynomial orders{p_end} {synopt:{opt ek:urtosis(#)}}specify kurtosis of error term{p_end} {synopt:{opt xk:urtosis(#)}}specify kurtosis of right-hand side variables{p_end} {syntab:Reporting} {synopt:{opt corr:elation(#)}}postulated endogeneity for test output{p_end} {synoptline} {marker estat_hett_options}{...} {synoptset 24 tabbed}{...} {synopthdr:hett_options} {synoptline} {syntab:Model} {synopt:{opt xb}}use fitted values{p_end} {synopt:{opt rhs}}add right-hand side variables{p_end} {syntab:Reporting} {synopt:{opt minp}}show minimum p-value for individual variables{p_end} {synopt:{opt corr:elation(#)}}postulated endogeneity for test output{p_end} {synoptline} {marker estat_dur_options}{...} {synoptset 24 tabbed}{...} {synopthdr:dur_options} {synoptline} {syntab:Model} {synopt:{opth o:rder(numlist)}}specify serial correlation lag orders{p_end} {synopt:{opt ek:urtosis(#)}}specify kurtosis of error term{p_end} {synopt:{opt xk:urtosis(#)}}specify kurtosis of right-hand side variables{p_end} {syntab:Reporting} {synopt:{opt corr:elation(#)}}postulated endogeneity for test output{p_end} {synoptline} {marker estat_rcr_options}{...} {synoptset 24 tabbed}{...} {synopthdr:rcr_options} {synoptline} {syntab:Model} {synopt:{opt lambda}}compute sensitivity parameter of Krauth (2016){p_end} {synopt:{opt delta}}compute sensitivity parameter of Oster (2019){p_end} {syntab:Reporting} {synopt:{opt corr:elation(#)}}postulated endogeneity for parameter output{p_end} {synoptline} {marker estat_graph_options}{...} {synopthdr:graph_options} {synoptline} {syntab:Reporting} {synopt:{opt tw:oway}{cmd:(}{it:{help kinkyreg_postestimation##options_spec:twoway_spec}}{cmd:)}}specify options for twoway graphs{p_end} {synopt:{opt pvalp:lot}{cmd:(}{it:{help kinkyreg_postestimation##options_spec:pvalplot_spec}}{cmd:)}}specify options for p-value or parameter plots{p_end} {synopt:{opt nogr:aph}}suppress creation of graph{p_end} {synoptline} {p2colreset}{...} {marker options_spec}{...} {p 4 6 2} {it:{help test##spec:test_spec}} is one of {p 8 8 2}{it:coeflist}{p_end} {p 8 8 2}{it:exp} {cmd:=} {it:exp} [{cmd:=} {it:exp}]{p_end} {p 4 6 2} {it:twoway_spec} is {p 8 8 2} [{cmd:,} {it:{help twoway_options}} {opt yrange(#_1 #_2)} {cmd:addplot(}{it:{help addplot_option:plot}}{cmd:)}] {p 4 6 2} {it:pvalplot_spec} is {p 8 8 2} [{it:name}|{it:#}] [{cmd:,} {it:{help line_options}} {cmd:recast(}{it:{help advanced_options:newplottype}}{cmd:)}] {title:Description for estat} {pstd} {cmd:estat test} computes linear hypotheses tests; see {helpb test:[R] test}. {pstd} {cmd:estat exclusion} computes Wald tests for the valid exclusion of the variables in {it:varlist} from the KLS regression, as described by Kiviet (2020). These are Wald tests for individual and joint insignificance after a KLS estimation of the regression model augmented with the respective variables. The p-values of the tests are graphically shown over the range of postulated endogeneity correlations used to compute the KLS estimates with {cmd:kinkyreg}. The null hypothesis is that the exclusion restrictions are valid. By default, {it:varlist} are the instrumental variables specified with {cmd:kinkyreg}. {pstd} {cmd:estat reset} computes the Ramsey (1969) regression equation specification error test. These are Wald tests for joint insignificance after a KLS estimation of the regression model augmented with powers of the fitted values or the right-hand side variables. The p-values of the tests are graphically shown over the range of postulated endogeneity correlations used to compute the KLS estimates with {cmd:kinkyreg}. The null hypothesis is that the regression model is correctly specified. {pstd} {cmd:estat hettest} computes the Breusch and Pagan (1979) tests for heteroskedasticity of the KLS error term. These are Wald tests in an auxiliary regression of the squared residuals separately on each specified {it:varlist}. The p-values of the tests are graphically shown over the range of postulated endogeneity correlations used to compute the KLS estimates with {cmd:kinkyreg}. The null hypothesis is that the errors are homoskedastic. {pstd} {cmd:estat durbinalt} computes the alternative test of Durbin (1970) for serial correlation of the KLS error term. These are Wald tests for joint insignificance after a KLS estimation of the regression model augmented with lagged residuals. The p-values of the tests are graphically shown over the range of postulated endogeneity correlations used to compute the KLS estimates with {cmd:kinkyreg}. The null hypothesis is that their is no serial correlation up to the specified order. This test requires time series data. {pstd} {cmd:estat rcr} computes the sensitivity parameters {it:lambda} and {it:delta} for the relative correlation restriction (RCR) estimators of Krauth (2016) and Oster (2019), respectively. For a given value of the endogeneity correlation, the KLS estimates can be replicated with the RCR estimators by using the corresponding values for these sensitivity parameters. {title:Options for estat} {dlgtab:Model} {phang} {opt nojoint} requests not to compute the joint exclusion test of all variables. {phang} {opt noindividual} requests not to compute the individual exclusion tests for each variable. {phang} {opt xb} requests to use the fitted values. Only the exogenous variation of the endogenous right-hand side variable is used to compute the fitted values. {pmore} With {cmd:estat reset}, powers of the fitted values are used. This is the default. {pmore} With {cmd:estat hettest}, a test with fitted values only is computed, in addition to tests with other specified varlists, if any. This option is the default if no varlists are specified. {phang} {opt rhs} requests to use the right-hand side variables of the fitted regression model. Only the exogenous variation of the endogenous variable is used. {pmore} With {cmd:estat reset}, powers of the individual right-hand side variables are used instead of the fitted values. {pmore} With {cmd:estat hettest}, the right-hand side variables are added to each {it:varlist}. This option allows {it:varlist} to be empty but parentheses are still required if multiple varlists are specified. {phang} {opth order(numlist)} specifies the orders to be used for the test. A separate test is computed for each value in {it:numlist}. {pmore} With {cmd:estat reset}, these are the polynomial orders of the fitted values or right-hand side variables. The default is {cmd:order(2 3 4)}. {pmore} With {cmd:estat durbinalt}, these are the maximum lag orders of the residuals. The default is {cmd:order(1)}. {phang} {opt ekurtosis(#)} specifies a value for the kurtosis of the error term to be used in the variance calculation. By default, the kurtosis is estimated based on the KLS estimates. {phang} {opt xkurtosis(#)} specifies a value for the kurtosis of the independent variables to be used in the variance calculation. By default, the maximum of the estimated kurtosis for all right-hand side variables is used. {phang} {opt lambda} and {opt delta} request to either compute Krauth's {it:lambda} or Oster's {it:delta} for the replication of the KLS estimates with the respective RCR estimator. By default, both sensitivity parameters are computed. {dlgtab:Reporting} {phang} {opt minp} returns for each endogeneity correlation the minimum p-value of individual significance tests among all variables in the respective variable list. By default, {cmd:estat hettest} computes joint significance tests of all variables in the auxiliary regression. {phang} {opt correlation(#)} requests to display test results or parameter values for the specified endogeneity correlation. If {it:#} does not match a value on the estimation grid, the results for the closest grid point to {it:#} are displayed. {phang} {opt level(#)}; see {helpb estimation options##level():[R] estimation options}. {phang} {cmd:twoway(}[{cmd:,} {it:{help twoway_options}} {opt yrange(#_1 #_2)} {cmd:addplot(}{it:{help addplot_option:plot}}{cmd:)}]{cmd:)} specifies options for twoway graphs; see {helpb graph_twoway:[G-2] graph twoway}. {pmore} If the twoway option {cmd:name(}{it:{help name_option:name}}{cmd:)} is not specified, {cmd:name(}{it:namestub}{cmd:_}{it:test}{cmd:, replace)} is assumed, where {it:test} is either {cmd:test}, {cmd:excl}, {cmd:reset}, {cmd:hett}, {cmd:dur}, or {cmd:rcr}, according to the minimum abbreviation of the respective {cmd:estat} subcommand. The prefix is set with the {cmd:kinkyreg} option {opt namestub(namestub)}. {pmore} {opt yrange(#_1 #_2)} specifies that the p-value or parameter value plots be restricted to the interval [{it:#_1}, {it:#_2}] on the {it:y} axis. A missing value for {it:#_1} or {it:#_2} refers to minus or plus infinity, respectively. {pmore} {cmd:addplot(}{it:{help addplot_option:plot}}{cmd:)} allows to overlay the twoway graph with additional plots; see {it:{help addplot_option}}. {phang} {cmd:pvalplot(}[{it:name}|{it:#}] [{cmd:,} {it:{help line_options}} {cmd:recast(}{it:{help advanced_options:newplottype}}{cmd:)}]{cmd:)} determines the look of the p-value or parameter value plots. By default, these are options for twoway line plots; see {helpb line:[G-2] graph twoway line}. {pmore} With {cmd:estat test}, neither {it:name} nor {it:#} must be specified. {pmore} With {cmd:estat exclusion}, {it:name} must be a variable name for the individual exclusion tests. For the joint exclusion test, {it:name} must not be specified. {pmore} With {cmd:estat reset} or {cmd:estat durbinalt}, {it:#} must be the integer value of an order specified with option {cmd:order()}. {pmore} With {cmd:estat hettest}, {it:#} must be the integer value referring to the {it:#}-th specified {it:varlist}. If option {cmd:xb} was specified, the corresponding test is ordered last. {pmore} With {cmd:estat rcr}, {it:name} must be {cmd:lambda} for Krauth's lambda or {cmd:delta} for Oster's delta. {pmore} {cmd:recast(}{it:{help advanced_options:newplottype}}{cmd:)} allows to treat the plot as {it:newplottype} instead of a line plot; see {it:{help advanced_options}}. {phang} {opt nograph} suppresses the creation of the graph for KLS inference. {phang} {opt notable} suppresses display of the results table. {marker example}{...} {title:Example} {pstd}Setup{p_end} {phang2}. {stata "use http://www.stata-press.com/data/imeus/griliches"}{p_end} {pstd}Graphical inference for KLS estimation{p_end} {phang2}. {stata kinkyreg lw s expr tenure rns smsa _I* (kww = iq), range(-0.7 0.7)}{p_end} {pstd}Graphical inference for linear hypothesis test{p_end} {phang2}. {stata estat test expr = tenure}{p_end} {pstd}Graphical inference for the exclusion restrictions tests{p_end} {phang2}. {stata estat exclusion}{p_end} {phang2}. {stata estat exclusion age mrt}{p_end} {pstd}Graphical inference for the RESET test{p_end} {phang2}. {stata estat reset, order(2 3)}{p_end} {phang2}. {stata estat reset, rhs order(2 3)}{p_end} {pstd}Graphical inference for the heteroskedasticity test{p_end} {phang2}. {stata estat hettest () (iq), xb rhs}{p_end} {phang2}. {stata estat hettest () (iq), rhs minp}{p_end} {marker authors}{...} {title:Authors} {pstd} Sebastian Kripfganz, University of Exeter, {browse "http://www.kripfganz.de"} {pstd} Jan F. Kiviet, University of Amsterdam, {browse "https://sites.google.com/site/homepagejfk/"} {marker references}{...} {title:References} {phang} Breusch, T. S., and A. R. Pagan. 1979. A simple test for heteroscedasticity and random coefficient variation. {it:Econometrica} 47: 1287-1294. {phang} Durbin, J. 1970. Testing for serial correlation in least-squares regression when some of the regressors are lagged dependent variables. {it:Econometrica} 38: 410-421. {phang} Kiviet, J. F. 2020. Testing the impossible: identifying exclusion restrictions. {it:Journal of Econometrics} 218: 294-316. {phang} Kiviet, J. F. 2020. Instrument-free inference under confined regressor endogeneity and mild regularity. {it:Stellenbosch Economic Working Papers}: WP09/2020. {phang} Krauth, B. 2016. Bounding a linear causal effect using relative correlation restrictions. {it:Journal of Econometric Methods} 5: 117-141. {phang} Oster, E. 2019. Unobservable selection and coefficient stability: Theory and evidence. {it:Journal of Business & Economic Statistics} 37: 187-204. {phang} Ramsey, J. B. 1969. Tests for specification errors in classical linear least-squares regression analysis. {it:Journal of the Royal Statistical Society, Series B} 31: 350-371.