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Second-order Refinement of Empirical Likelihood for Testing Overidentifying Restrictions

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Abstract

This paper studies second-order properties of the empirical likelihood overidentifying restriction test to check the validity of moment condition models. We show that the empirical likelihood test is Bartlett correctable and suggest second-order refinement methods for the test based on the empirical Bartlett correction and adjusted empirical likelihood. Our second-order analysis supplements the one in Chen and Cui (2007) who considered parameter hypothesis testing for overidentified models. In simulation studies we find that the empirical Bartlett correction and adjusted empirical likelihood assisted by bootstrapping provide reasonable improvements for the properties of the null rejection probabilities.

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File URL: http://cowles.econ.yale.edu/P/cd/d17b/d1791.pdf
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Bibliographic Info

Paper provided by Cowles Foundation for Research in Economics, Yale University in its series Cowles Foundation Discussion Papers with number 1791.

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Length: 32 pages
Date of creation: Apr 2011
Date of revision: Jan 2012
Handle: RePEc:cwl:cwldpp:1791

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Postal: Cowles Foundation, Yale University, Box 208281, New Haven, CT 06520-8281 USA

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Keywords: Empirical likelihood; GMM; Overidentification test; Bartlett correction; Higher order analysis;

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