How Reliable are Bootstrap-based Heteroskedasticity Robust Tests?

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.

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Year of publication:	2020-04
Authors:	Pötscher, Benedikt M. ; Preinerstorfer, David

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Type of publication:	Book / Working Paper
Language:	English
Notes:	Pötscher, Benedikt M. and Preinerstorfer, David (2020): How Reliable are Bootstrap-based Heteroskedasticity Robust Tests?
Classification:	C12 - Hypothesis Testing ; C2 - Econometric Methods: Single Equation Models
Source:	BASE

Persistent link: https://www.econbiz.de/10015260136