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.
| Originalsprache | Englisch |
|---|---|
| Seiten (von - bis) | 789-847 |
| Seitenumfang | 59 |
| Fachzeitschrift | Econometric Theory |
| Jahrgang | 39 |
| Ausgabenummer | 4 |
| DOIs | |
| Publikationsstatus | Veröffentlicht - 27 Aug. 2023 |
| Extern publiziert | Ja |
Bibliographische Notiz
Publisher Copyright:© The Author(s), 2022. Published by Cambridge University Press.