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HOW RELIABLE ARE BOOTSTRAP-BASED HETEROSKEDASTICITY ROBUST TESTS?

Published online by Cambridge University Press:  27 April 2022

Benedikt M. Pötscher  and
David Preinerstorfer
Benedikt M. Pötscher*
Affiliation:
Department of Statistics, University of Vienna
David Preinerstorfer
Affiliation:
SEPS-SEW, University of St. Gallen
*
Address correspondence to Benedikt Pötscher, Department of Statistics, University of Vienna, A-1090 Oskar-Morgenstern Platz 1, Vienna, Austria; e-mail: benedikt.poetscher@univie.ac.at.
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Abstract

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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.

Information

Type
ARTICLES
Information
Econometric Theory , Volume 39 , Issue 4 , August 2023 , pp. 789 - 847
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
© The Author(s), 2022. Published by Cambridge University Press

Footnotes

Financial support of the second author by the Program of Concerted Research Actions (ARC) of the Université libre de Bruxelles is gratefully acknowledged. We thank two referees, the Co-Editor, and the Editor for helpful comments.

References

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