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Asymptotic efficiency of semiparametric two-step GMM

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

No CWP28/14, CeMMAP working papers from Centre for Microdata Methods and Practice, Institute for Fiscal Studies

Abstract: Many structural economics models are semiparametric ones in which the unknown nuisance functions are identifi?ed via nonparametric conditional moment restrictions with possibly non-nested or overlapping conditioning sets, and the ?finite dimensional parameters of interest are over-identi?fied via unconditional moment restrictions involving the nuisance functions. In this paper 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 nonparametric methods in the fi?rst 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: 2014-06-04
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Related works:
Journal Article: Asymptotic Efficiency of Semiparametric Two-step GMM (2014) Downloads
Working Paper: Asymptotic Efficiency of Semiparametric Two-step GMM (2012) Downloads
Working Paper: Asymptotic efficiency of semiparametric two-step GMM (2012) Downloads
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