Asymptotic Efficiency of Semiparametric Two-step GMM

Daniel Ackerberg, Xiaohong Chen (), Jinyong Hahn and Zhipeng Liao

The Review of Economic Studies, 2014, vol. 81, issue 3, 919-943

Abstract: Many structural economics models are semiparametric ones in which the unknown nuisance functions are identified via non-parametric conditional moment restrictions with possibly non-nested or overlapping conditioning sets, and the finite dimensional parameters of interest are over-identified via unconditional moment restrictions involving the nuisance functions. In this article we characterize the semiparametric efficiency bound for this class of models. We show that semiparametric two-step optimally weighted GMM estimators achieve the efficiency bound, where the nuisance functions could be estimated via any consistent non-parametric methods 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.

Date: 2014
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Related works:
Working Paper: Asymptotic efficiency of semiparametric two-step GMM (2014)
Working Paper: Asymptotic efficiency of semiparametric two-step GMM (2014)
Working Paper: Asymptotic efficiency of semiparametric two-step GMM (2012)
Working Paper: Asymptotic Efficiency of Semiparametric Two-step GMM (2012)
Working Paper: Asymptotic efficiency of semiparametric two-step GMM (2012)
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