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Empirically Relevant Critical Values For Hypothesis Tests: The Bootstrap to the Rescue

Author

Listed:
  • Horowitz, J.L.

    (University of Iowa)

  • Savin, N.E.

    (University of Iowa)

Abstract

Tests of statistical hypotheses can be based on either of two critical values: the Type I critical value or the size-corrected critical value. The former usually depends on unknown population parameters and cannot be evaluated exactly in applications, but it can often be estimated very accurately by using the bootstrap. The latter does not depend on unknown population parameters but is likely to yield a test with low power. The critical values used in most Monte Carlo studies of the powers of tests are neither Type I nor size-corrected. They are irrelevant to empirical research.

Suggested Citation

  • Horowitz, J.L. & Savin, N.E., 1998. "Empirically Relevant Critical Values For Hypothesis Tests: The Bootstrap to the Rescue," Working Papers 98-07, University of Iowa, Department of Economics.
    • Handle: RePEc:uia:iowaec:98-07
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    Cited by:

    1. Geert Dhaene & J. M. C. Santos Silva, 2012. "Specification and testing of models estimated by quadrature," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(2), pages 322-332, March.

    More about this item

    Keywords

    Hypothesis test; critical value; size; Type I error; bootstrap;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

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