Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/79518
Authors: 
Chen, Xiaohong
Hahn, Jinyong
Liao, Zhipeng
Year of Publication: 
2012
Series/Report no.: 
cemmap working paper, Centre for Microdata Methods and Practice CWP31/12
Abstract: 
In this note, we characterize the semiparametric efficiency bound for a class of semi- parametric 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 uncondi tional 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.
Subjects: 
Overlapping Information Sets
Semiparametric Efficiency
Two-Step GMM
JEL: 
C14
C31
C32
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

Files in This Item:
File
Size
245.68 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.