How Reliable are Bootstrap-based Heteroskedasticity Robust Tests?

Benedikt Pötscher and David Preinerstorfer

MPRA Paper from University Library of Munich, Germany

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: wild bootstrap-based heteroskedasticity robust tests; size distortions (search for similar items in EconPapers)
JEL-codes: C12 C2 (search for similar items in EconPapers)
Date: 2020-04
New Economics Papers: this item is included in nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://mpra.ub.uni-muenchen.de/100234/1/MPRA_paper_100234.pdf original version (application/pdf)
https://mpra.ub.uni-muenchen.de/110613/1/MPRA_paper_110613.pdf revised version (application/pdf)

Related works:
Journal Article: HOW RELIABLE ARE BOOTSTRAP-BASED HETEROSKEDASTICITY ROBUST TESTS? (2023)
Working Paper: How Reliable are Bootstrap-based Heteroskedasticity Robust Tests? (2021)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:100234

Access Statistics for this paper

More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter ().