Empirically relevant critical values for hypothesis tests: A bootstrap approach

Joel L. Horowitz*, N. B. Savin

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

47 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)375-389
Number of pages15
JournalJournal of Econometrics
Issue number2
StatePublished - Apr 2000


  • Bootstrap
  • Critical value
  • Hypothesis test
  • Size
  • Type I error

ASJC Scopus subject areas

  • Economics and Econometrics


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