Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5097186 | Journal of Econometrics | 2008 | 8 Pages |
Abstract
The wild bootstrap is studied in the context of regression models with heteroskedastic disturbances. We show that, in one very specific case, perfect bootstrap inference is possible, and a substantial reduction in the error in the rejection probability of a bootstrap test is available much more generally. However, the version of the wild bootstrap with this desirable property is without the skewness correction afforded by the currently most popular version of the wild bootstrap. Simulation experiments show that this does not prevent the preferred version from having the smallest error in rejection probability in small and medium-sized samples.
Related Topics
Physical Sciences and Engineering
Mathematics
Statistics and Probability
Authors
Russell Davidson, Emmanuel Flachaire,