How Reliable are Bootstrap-Based Heteroskedasticity Robust Tests?
Journal
Econometric Theory
Type
journal article
Date Issued
2023
Author(s)
Pötscher, Benedikt M.
;
Preinerstorfer, David
Abstract
We develop theoretical finite-sample results concerning the size of wild bootstrap-based heteroskedasticity robust tests in linear regression models. In particular, these results provide an efficient diagnostic check, which can be used to weed out tests that are unreliable for a given testing problem in the sense that they overreject substantially. This allows us to assess the reliability of a large variety of wild bootstrap-based tests in an extensive numerical study.
Language
English
HSG Classification
contribution to scientific community
Refereed
Yes
Volume
39
Start page
789
End page
847
Official URL
Subject(s)
Eprints ID
267604