Second-order Refinement of Empirical Likelihood for Testing Overidentifying Restrictions
Yukitoshi Matsushita and
Taisuke Otsu
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Yukitoshi Matsushita: Graduate School of Humanities and Social Science, University of Tsukuba
Taisuke Otsu: Cowles Foundation, Yale University, https://cowles.yale.edu/
No 1791, Cowles Foundation Discussion Papers from Cowles Foundation for Research in Economics, Yale University
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.
Keywords: Empirical likelihood; GMM; Overidentification test; Bartlett correction; Higher order analysis (search for similar items in EconPapers)
JEL-codes: C12 C14 (search for similar items in EconPapers)
Pages: 32 pages
Date: 2011-04, Revised 2012-01
New Economics Papers: this item is included in nep-ecm
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Persistent link: https://EconPapers.repec.org/RePEc:cwl:cwldpp:1791
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