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Generalized Empirical Likelihood-Based Model Selection Criteria for Moment Condition Models

Hong, Han and Preston, Bruce and Shum, Matthew (2003) Generalized Empirical Likelihood-Based Model Selection Criteria for Moment Condition Models. Econometric Theory, 19 (6). pp. 923-943. ISSN 0266-4666.

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This paper proposes model selection criteria (MSC) for unconditional moment models using generalized empirical likelihood (GEL) statistics. The use of GEL-statistics in lieu of J-statistics (in the spirit of Andrews, 1999, Econometrica 67, 543–564; and Andrews and Lu, 2001, Journal of Econometrics 101, 123–164) leads to an alternative interpretation of the MSCs that emphasizes the common information-theoretic rationale underlying model selection procedures for both parametric and semiparametric models. The result of this paper also provides a GEL-based model selection alternative to the information criteria–based nonnested tests for generalized method of moments models considered in Kitamura (2000, University of Wisconsin). The results of a Monte Carlo experiment are reported to illustrate the finite-sample performance of the selection criteria and their impact on parameter estimation.

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Additional Information:© 2003 Cambridge University Press. Published online: 24 September 2003. The authors gratefully acknowledge support from the NSF (Hong: SES-0079495, Shum: SES-0003352) and the Fellowship of Woodrow Wilson Scholars (Preston). We thank the co-editor Don Andrews, Xiaohong Chen, John Geweke, Bo Honore, Yuichi Kitamura, Serena Ng, Harry Paarsch, Gautam Tripathi, and two anonymous referees for insightful suggestions and helpful comments.
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Fellowship of Woodrow Wilson ScholarsUNSPECIFIED
Record Number:CaltechAUTHORS:20111017-113050114
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:27255
Deposited By: Tony Diaz
Deposited On:17 Oct 2011 18:50
Last Modified:26 Dec 2012 14:16

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