We provide a theoretical framework in which to study the accuracy of bootstrap P values, which may be based on a parametric or nonparametric bootstrap. In the parametric case, the accuracy of a bootstrap test will depend on the shape of what we call the critical value function. We show that, in many circumstances, the error in rejection probability of a bootstrap test will be one whole order of magnitude smaller than that of the corresponding asymptotic test. We also propose a simulation method for estimating this error that requires the calculation of only two test statistics per replication.
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Article provided by Cambridge University Press in its journal Econometric Theory.
Volume (Year): 15 (1999) Issue (Month): 03 (June) Pages: 361-376 Download reference. The following formats are available: HTML
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