This file is part of IDEAS, which uses RePEc data


[ Papers | Articles | Software | Books | Chapters | Authors | Institutions | JEL Classification | NEP reports | Search | New papers by email | Author registration | Rankings | Volunteers | FAQ | Blog | Help! ]

Generalized Empirical Likelihood Based Model Selection Criteria For Moment Condition Models

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Hong, Han
Preston, Bruce
Shum, Matthew

Additional information is available for the following registered author(s):

Abstract

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.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.

Download Info
To download:

If you experience problems downloading a file, check if you have the proper application to view it first. Information about this may be contained in the File-Format links below. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://journals.cambridge.org/abstract_S0266466603196028
File Format: text/html
File Function: link to article abstract page
Download Restriction: no

Publisher Info
Article provided by Cambridge University Press in its journal Econometric Theory.

Volume (Year): 19 (2003)
Issue (Month): 06 (December)
Pages: 923-943
Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Handle: RePEc:cup:etheor:v:19:y:2003:i:06:p:923-943_19

Contact details of provider:
Postal: The Edinburgh Building, Shaftesbury Road, Cambridge CB2 2RU UK
Fax: +44 (0)1223 325150
Email:
Web page: http://journals.cambridge.org/jid_ECT

For technical questions regarding this item, or to correct its listing, contact: (Mike Eden).

Related research
Keywords:

Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Han Hong & Bruce Preston, 2008. "Bayesian Averaging, Prediction and Nonnested Model Selection," NBER Working Papers 14284, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  2. Taisuke Otsu & Myung Hwan Seo & Yoon-Jae Whang, 2008. "Testing for Non-Nested Conditional Moment Restrictions Using Unconditional Empirical Likelihood," Cowles Foundation Discussion Papers 1660, Cowles Foundation, Yale University. [Downloadable!]
Statistics
Access and download statistics

Did you know? You too can volunteer for RePEc, for example by encouraging others to register as authors.

This page was last updated on 2009-11-24.


This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.