*! version 1.0 16April2019

*! Author: Volker Ludwig

Title

xtart -- User-written ado for Artificial Regression Test (ART) version of the Hausman test

Syntax

xtart [Model A] [,] [addvars(varlist)] [keepvars(varlist)] [fe] [predicted(stub1 stub2)]

Description

xtart implements the ART version of the Hausman test.
xtart is used after estimation of a linear Fixed-Effects models with Individual-Specific Slopes (FEIS) (Wooldridge 2010, pp. 374-381).
It tests the Null hypothesis that there are no systematic differences in coefficients between an FEIS and a standard FE model.
The ART is intended as a test for inconsistency of FE estimates due to heterogeneous slopes of a subset of covariates.
xtart can also be used to test for differences between standard FE and standard Random-Effects (RE) estimates, a typical application of the ART version of the Hausman test (Arellano 1993),
and to test for differences between FEIS and RE estimates.

xtart requires estimation of a regression model using xtfeis before the ART test is conducted.
You may specify the name of Model A after saving regression results with estimates store (see [XT] estimates).
If Model A is not specified, xtart uses regression results of the most recent model estimated by xtfeis. The ART tests for
systematic differences in coefficients between Model A and a restricted Model B.

Options

Options

fe requests the ART for comparing coefficients of standard FE and RE models.
By default, coefficients of an FEIS and an FE model are compared.

re requests the ART for comparing coefficients of an FEIS and an RE model.
By default, coefficients of an FEIS and an FE model are compared.

addvars(varlist) adds further covariates in varlist to the specification of Model B.

keep(varlist) requests that the ART be conducted only for the specified subset of common coefficients of Model A and Model B.

predicted(stub1 stub2) adds variables to the data set carrying unit-specific means
and predicted values for the dependent variable and covariates of Model A.
Names of the variables carrying predicted values are original variable names prefixed by stub1.
Variable names for the means are prefixed by stub2. If stub1 and stub2 are left unspecified,
default prefixes pred and mean are used.

Examples

. webuse nlswork

Estimate Fixed-Effects model with Individual-specific Slope for total work experience
. xtfeis ln_wage msp tenure year, slope(ttl_exp) cluster(idcode)
. estimates store FEIS

Test for FEIS versus FE model
. xtart

Test for FE versus RE model
. xtart FEIS, fe

Test for FEIS versus RE model
. xtart FEIS, re

Compute test for subset of specified variables
. xtart FEIS, keep(msp)

Add variables with predicted and mean values to current data set
. est restore FEIS
. xtart FEIS, predicted(_p_ _m_)

Compute test "by hand"
. return list
. `r(estcmd)'
. test _p_msp _p_tenure _p_year

References

Arellano, M. (1993). On the testing of correlated effects with panel data. Journal of Econometrics 59: 87-97.
Wooldridge, J. (2010). Econometrics of Cross Section and Panel Data, Cambridge: MIT Press, 2nd edition.

Author

Volker Ludwig
Technische Universität Kaiserslautern
ludwig@sowi.uni-kl.de

Citation

Please cite this software as follows:

Ludwig, V. (2019). XTFEIS: Stata module to estimate linear Fixed-Effects model with Individual-specific Slopes (FEIS).
https://EconPapers.repec.org/RePEc:boc:bocode:s458045