An Information-Theoretic Alternative to Generalized Method of Moments Estimation

Posted: 4 Feb 1998

See all articles by Michael J. Stutzer

Michael J. Stutzer

University of Colorado at Boulder - Leeds School of Business

Yuichi Kitamura

Yale University - Cowles Foundation

Abstract

While optimally weighted GMM estimation has desirable large sample properties, its small sample performance is poor in some applications. We propose a computationally simple alternative, for weakly dependent data generating mechanisms, based on minimization of the Kullback-Leibler Information Criterion (a.k.a. relative entropy). Conditions are derived under which the large sample properties of this estimator are similar to GMM, i.e. the estimator will be consistent and asymptotically normal, with the same asymptotic covariance matrix as GMM. In addition, we propose overidentifying and parametric restrictions tests as alternatives to GMM procedures.

JEL Classification: C12, C13, C32

Suggested Citation

Stutzer, Michael Jay and Kitamura, Yuichi, An Information-Theoretic Alternative to Generalized Method of Moments Estimation. Available at SSRN: https://ssrn.com/abstract=57138

Michael Jay Stutzer (Contact Author)

University of Colorado at Boulder - Leeds School of Business ( email )

Boulder, CO 80309-0419
United States

Yuichi Kitamura

Yale University - Cowles Foundation ( email )

Box 208281
New Haven, CT 06520-8281
United States

Do you have negative results from your research you’d like to share?

Paper statistics

Abstract Views
1,074
PlumX Metrics