Testing for heteroskedasticity in fixed effects models

Abstract

We derive tests for heteroskedasticity after fixed effects estimation of linear panel models. The asymptotic results are based on a ‘large N–fixed T’ framework, where the incidental parameters problem is bypassed by utilizing a (pseudo) likelihood function conditional on the sufficient statistic for these parameters. A simple ‘studentization’ produces distribution free tests that can easily be implemented using an artificial regression based on residuals after fixed effects estimation. A Monte Carlo exploration suggests that the tests perform well in small samples such as those encountered in practice.