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

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Author Info
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.

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Publisher Info
Paper provided by University of Iowa, Department of Economics in its series Working Papers with number 98-07.

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Length: 16 Pages
Date of creation: Jul 1998
Date of revision:
Handle: RePEc:uia:iowaec:98-07

Contact details of provider:
Postal: University of Iowa, Department of Economics, Henry B. Tippie College of Business, Iowa City, Iowa 52242
Phone: (319) 335-0829
Fax: (319) 335-1956
Web page: http://tippie.uiowa.edu/economics/
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Related research
Keywords: Hypothesis test; critical value; size; Type I error; bootstrap;

Find related papers by JEL classification:
C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Hypothesis Testing
C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Statistical Simulation Methods

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This page was last updated on 2009-11-27.


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