The Power of Bootstrap Tests

Russell Davidson and James MacKinnon ()

No 937, Working Papers from Queen's University, Department of Economics

Abstract: Bootstrap tests are tests for which the significance level is calculated using some variant of the bootstrap, which may be parametric or nonparametric. We show that the power of a bootstrap test will generally be very close to the power of the asymptotic test on which it is based, provided that both tests are properly adjusted to have the correct size. We also discuss the loss of power that can occur when the number of bootstrap samples is relatively small. Some Monte Carlo results for two forms of omitted variable test in logit models are presented. These illustrate the theoretical results of the paper and demonstrate that the size-adjusted power of asymptotic tests can vary greatly depending on the method used for size adjustment.

Keywords: bootstrapping; hypothesis testing; logit model (search for similar items in EconPapers)
JEL-codes: C12 C15 (search for similar items in EconPapers)
Date: Written
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