Asymptotic efficiency of semiparametric two-step GMM
Xiaohong Chen () and
Authors registered in the RePEc Author Service: Zhipeng Liao ()
No CWP31/12, CeMMAP working papers from Centre for Microdata Methods and Practice, Institute for Fiscal Studies
In this note, we characterise 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 non-parametric 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 (search for similar items in EconPapers)
JEL-codes: C14 C31 C32 (search for similar items in EconPapers)
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Journal Article: 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)
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