How Reliable are Bootstrap-based Heteroskedasticity Robust Tests?
Statistics Theory
2023-08-17 v2 Econometrics
Methodology
Statistics Theory
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.
Keywords
Cite
@article{arxiv.2005.04089,
title = {How Reliable are Bootstrap-based Heteroskedasticity Robust Tests?},
author = {Benedikt M. Pötscher and David Preinerstorfer},
journal= {arXiv preprint arXiv:2005.04089},
year = {2023}
}
Comments
59 pages, 1 figure