EconStor >
Institute for Fiscal Studies (IFS), London >
cemmap working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies (IFS) >

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10419/64640
  
Title:Semiparametric efficiency bound for models of sequential moment restrictions containing unknown functions PDF Logo
Authors:Ai, Chunrong
Chen, Xiaohong
Issue Date:2009
Series/Report no.:cemmap working paper CWP28/09
Abstract:This paper computes the semiparametric efficiency bound for finite dimensional parameters identified by models of sequential moment restrictions containing unknown functions. Our results extend those of Chamberlain (1992b) and Ai and Chen (2003) for semiparametric conditional moment restriction models with identical information sets to the case of nested information sets, and those of Chamberlain (1992a) and Brown and Newey (1998) for models of sequential moment restrictions without unknown functions to cases with unknown functions of possibly endogenous variables. Our bound results are applicable to semiparametric panel data models and semiparametric two stage plug-in problems. As an example, we compute the efficiency bound for a weighted average derivative of a nonparametric instrumental variables (IV) regression, and find that the simple plug-in estimator is not efficient. Finally, we present an optimally weighted, orthogonalized, sieve minimum distance estimator that achieves the semiparametric efficiency bound.
Subjects:Sequential moment models
Semiparametric efficiency bounds
Optimally weighted orthogonalized sieve minimum distance
Nonparametric IV regression
Weighted average derivatives
Partially linear quantile IV
JEL:C14
C22
Persistent Identifier of the first edition:doi:10.1920/wp.cem.2009.2809
Document Type:Working Paper
Appears in Collections:cemmap working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies (IFS)

Files in This Item:
File Description SizeFormat
613185749.pdf427.26 kBAdobe PDF
No. of Downloads: Counter Stats
Download bibliographical data as: BibTeX
Share on:http://hdl.handle.net/10419/64640

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