In finite samples, the true size of White's information matrix test often differs greatly from its nominal size based on asymptotic critical values. This paper shows how the bootstrap can be used to obtain improved finite-sample critical values. The results of Monte Carlo experiments show that for the cases investigated, the bootstrap largely eliminates the problem of incorrect finite-sample size. Moreover, when size-corrected critical values are used, forms of the test that have small size distortions with asymptotic critical values can have much lower power than forms that have large size distortions with asymptotic critical values.
|Original language||English (US)|
|Number of pages||17|
|Journal||Journal of Econometrics|
|State||Published - Apr 1994|
- Information matrix test
ASJC Scopus subject areas
- Economics and Econometrics