How Reliable are Bootstrap-based Heteroskedasticity Robust Tests?
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.
- Publication:
-
arXiv e-prints
- Pub Date:
- May 2020
- DOI:
- 10.48550/arXiv.2005.04089
- arXiv:
- arXiv:2005.04089
- Bibcode:
- 2020arXiv200504089P
- Keywords:
-
- Mathematics - Statistics Theory;
- Economics - Econometrics;
- Statistics - Methodology
- E-Print:
- 59 pages, 1 figure