Testing inference in heteroskedastic fixed effects models

Carlos F.A. Uchôa, Francisco Cribari-Neto and Tatiane A. Menezes

European Journal of Operational Research, 2014, vol. 235, issue 3, 660-670

Abstract: This paper considers the issue of performing testing inference in fixed effects panel data models under heteroskedasticity of unknown form. We use numerical integration to compute the exact null distributions of different quasi-t test statistics and compare them to their limiting counterpart. The test statistics use different heteroskedasticity-consistent standard errors. Our results reveal that the asymptotic approximation is usually poor in small samples when the test statistic is based on the covariance matrix estimator proposed by Arellano (1987). The quality of the approximation is greatly increased when the standard error is obtained using other heteroskedasticity-consistent estimators, most notably the CHC4 estimator. Our results also reveal that the performance of Arellano’s test improves considerably when standard errors are computed using restricted residuals.

Keywords: Distribution; Simulation; Heteroskedasticity; Numerical integration; Longitudinal data; Quasi-t tests (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:235:y:2014:i:3:p:660-670

DOI: 10.1016/j.ejor.2014.01.032

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