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- Title
Invalidity of the bootstrap and the m out of n bootstrap for confidence interval endpoints defined by moment inequalities.
- Authors
ANDREWS, DONALD W. K.; HAN, SUKJIN
- Abstract
This paper analyses the finite-sample and asymptotic properties of several bootstrap and m out of n bootstrap methods for constructing confidence interval (CI) endpoints in models defined by moment inequalities. In particular, we consider using these methods directly to construct CI endpoints. By considering two very simple models, the paper shows that neither the bootstrap nor the m out of n bootstrap is valid in finite samples or in a uniform asymptotic sense in general when applied directly to construct CI endpoints. In contrast, other results in the literature show that other ways of applying the bootstrap, m out of n bootstrap, and subsampling do lead to uniformly asymptotically valid confidence sets in moment inequality models. Thus, the uniform asymptotic validity of resampling methods in moment inequality models depends on the way in which the resampling methods are employed.
- Subjects
STATISTICAL bootstrapping; DISTRIBUTION (Probability theory); STATISTICAL sampling; CONFIDENCE intervals; MATHEMATICAL inequalities; RESAMPLING (Statistics); STATISTICAL tolerance regions
- Publication
Econometrics Journal, 2009, Vol 12, pS172
- ISSN
1368-4221
- Publication type
Article
- DOI
10.1111/j.1368-423X.2008.00265.x