Asymptotic Efficiency of Semiparametric Two-Step GMM

24 Pages Posted: 9 Oct 2012

See all articles by Xiaohong Chen

Xiaohong Chen

Yale University - Cowles Foundation

Jinyong Hahn

University of California, Los Angeles

Zhipeng Liao

University of California, Los Angeles (UCLA) - Department of Economics

Date Written: October 9, 2012

Abstract

In this note, we characterize the semiparametric efficiency bound for a class of semiparametric models in which the unknown nuisance functions are identified via nonparametric conditional moment restrictions with possibly non-nested or over-lapping conditioning sets, and the finite dimensional parameters are potentially over-identified via unconditional moment restrictions involving the nuisance functions. We discover a surprising result that semiparametric two-step optimally weighted GMM estimators achieve the efficiency bound, where the nuisance functions could be estimated via any consistent nonparametric procedures in the first step. Regardless of whether the efficiency bound has a closed form expression or not, we provide easy-to-compute sieve based optimal weight matrices that lead to asymptotically efficient two-step GMM estimators.

Keywords: Overlapping Information Sets, Semiparametric Efficiency, Two-Step GMM

JEL Classification: C14, C31, C32

Suggested Citation

Chen, Xiaohong and Hahn, Jinyong and Liao, Zhipeng, Asymptotic Efficiency of Semiparametric Two-Step GMM (October 9, 2012). Cowles Foundation Discussion Paper No. 1880, Available at SSRN: https://ssrn.com/abstract=2159348 or http://dx.doi.org/10.2139/ssrn.2159348

Xiaohong Chen (Contact Author)

Yale University - Cowles Foundation ( email )

Box 208281
New Haven, CT 06520-8281
United States

Jinyong Hahn

University of California, Los Angeles ( email )

405 Hilgard Avenue
Box 951361
Los Angeles, CA 90095-1361
United States

Zhipeng Liao

University of California, Los Angeles (UCLA) - Department of Economics ( email )

8283 Bunche Hall
Los Angeles, CA 90095-1477
United States

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

Paper statistics

Downloads
102
Abstract Views
896
Rank
473,049
PlumX Metrics