In finite samples, the true size of White's information matrix test of
ten differs greatly from its nominal size based on asymptotic critical
values. This paper shows how the bootstrap can be used to obtain impr
oved finite-sample critical values. The results of Monte Carlo experim
ents show that for the cases investigated, the bootstrap largely elimi
nates 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 crit
ical values.