Further Results on the Limiting Distribution of GMM Sample Moment Conditions
AbstractIn this article, we examine the limiting behavior of generalized method of moments (GMM) sample moment conditions and point out an important discontinuity that arises in their asymptotic distribution. We show that the part of the scaled sample moment conditions that gives rise to degeneracy in the asymptotic normal distribution is T -consistent and has a nonstandard limiting distribution. We derive the appropriate asymptotic (weighted chi-squared) distribution when this degeneracy occurs and show how to conduct asymptotically valid statistical inference. We also propose a new rank test that provides guidance on which (standard or nonstandard) asymptotic framework should be used for inference. The finite-sample properties of the proposed asymptotic approximation are demonstrated using simulated data from some popular asset pricing models.
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Bibliographic InfoArticle provided by Taylor & Francis Journals in its journal Journal of Business & Economic Statistics.
Volume (Year): 30 (2012)
Issue (Month): 4 (May)
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- Nikolay Gospodinov & Raymond Kan & Cesare Robotti, 2010. "Further results on the limiting distribution of GMM sample moment conditions," Working Paper 2010-11, Federal Reserve Bank of Atlanta.
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- Fletcher, Jonathan, 2014. "Benchmark models of expected returns in U.K. portfolio performance: An empirical investigation," International Review of Economics & Finance, Elsevier, vol. 29(C), pages 30-46.
- Gospodinov, Nikolay & Kan, Raymond & Robotti, Cesare, 2013.
"Chi-squared tests for evaluation and comparison of asset pricing models,"
Journal of Econometrics,
Elsevier, vol. 173(1), pages 108-125.
- Nikolay Gospodinov & Raymond Kan & Cesare Robotti, 2011. "Chi-squared tests for evaluation and comparison of asset pricing models," Working Paper 2011-08, Federal Reserve Bank of Atlanta.
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