Abstract
This paper considers inference based on a test statistic that has a limit distribution that is discontinuous in a parameter. The paper shows that subsampling and m out of n bootstrap tests based on such a test statistic often have asymptotic size - defined as the limit of exact size - that is greater than the nominal level of the tests. This is due to a lack of uniformity in the pointwise asymptotics. We determine precisely the asymptotic size of such tests under a general set of high-level conditions that are relatively easy to verify. The results show that the asymptotic size of subsampling and m out of n bootstrap tests is distorted in some examples but not in others.
Original language | English (US) |
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Pages (from-to) | 426-468 |
Number of pages | 43 |
Journal | Econometric Theory |
Volume | 26 |
Issue number | 2 |
DOIs | |
State | Published - Apr 2010 |
All Science Journal Classification (ASJC) codes
- Social Sciences (miscellaneous)
- Economics and Econometrics