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 language | English |
|---|---|
| Pages (from-to) | 431-471 |
| Number of pages | 40 |
| Journal | Econometric Reviews |
| Volume | 33 |
| Issue number | 5-6 |
| DOIs | |
| Publication status | Published - Aug 2014 |
Keywords
- Bootstrap
- F-test
- Heteroskedasticity
- Non-normality
- Random effects