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.
| Original language | English |
|---|---|
| Pages (from-to) | 789-847 |
| Number of pages | 59 |
| Journal | Econometric Theory |
| Volume | 39 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 27 Aug 2023 |
| Externally published | Yes |
Bibliographical note
Publisher Copyright:© The Author(s), 2022. Published by Cambridge University Press.