Semiparametric efficiency bound for models of sequential moment restrictions containing unknown functions
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.
Year of publication: |
2009-10
|
---|---|
Authors: | Ai, Chunrong ; Chen, Xiaohong |
Institutions: | Centre for Microdata Methods and Practice (CEMMAP) |
Saved in:
freely available
Saved in favorites
Similar items by person
-
Sieve inference on semi-nonparametric time series models
Chen, Xiaohong, (2012)
-
Penalized sieve estimation and inference of semi-nonparametric dynamic models: a selective review
Chen, Xiaohong, (2011)
-
A practical asymptotic variance estimator for two-step semiparametric estimators
Ackerberg, Daniel, (2011)
- More ...