Asymptotic size and a problem with subsampling and with the m out of n bootstrap

Donald W.K. Andrews, Patrik Guggenberger

Research output: Contribution to journalArticle

58 Scopus citations

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 languageEnglish (US)
Pages (from-to)426-468
Number of pages43
JournalEconometric Theory
Volume26
Issue number2
DOIs
StatePublished - Apr 1 2010

All Science Journal Classification (ASJC) codes

  • Social Sciences (miscellaneous)
  • Economics and Econometrics

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