Asymptotic Efficiency of Semiparametric Two-step GMM
Daniel Ackerberg (),
Xiaohong Chen (),
Jinyong Hahn and
Zhipeng Liao ()
Review of Economic Studies, 2014, vol. 81, issue 3, 919-943
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.
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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)
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Persistent link: https://EconPapers.repec.org/RePEc:oup:restud:v:81:y:2014:i:3:p:919-943
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