A Heteroskedasticity-Robust F-Test Statistic for Individual Effects

Chris D. Orme, Takashi Yamagata

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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. © 2014 Copyright Chris D. Orme and Takashi Yamagata.
Original languageEnglish
Pages (from-to)431-471
Number of pages40
JournalEconometric Reviews
Volume33
Issue number5-6
DOIs
Publication statusPublished - Aug 2014

Keywords

  • Bootstrap
  • F-test
  • Heteroskedasticity
  • Non-normality
  • Random effects

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