Averaging of moment condition estimators
Xiaohong Chen (),
David Jacho-Chávez and
Oliver Linton
No CWP26/12, CeMMAP working papers from Centre for Microdata Methods and Practice, Institute for Fiscal Studies
Abstract:
We establish the consistency and asymptotic normality for a class of estimators that are linear combinations of a set of vn- consistent estimators whose cardinality increases with sample size. A special case of our framework corresponds to the conditional moment restriction and the implied estimator in that case is shown to achieve the semiparametric efficiency bound. The proofs do not rely on smoothness of underlying criterion functions.
Keywords: Instrumental Variables; Minimum Distance; Semiparametric Efficiency; Two-Stage Least Squares (search for similar items in EconPapers)
JEL-codes: C12 C13 C14 (search for similar items in EconPapers)
Date: 2012-09-21
New Economics Papers: this item is included in nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://www.cemmap.ac.uk/wps/cwp261212.pdf (application/pdf)
Our link check indicates that this URL is bad, the error code is: 404 Not Found (http://www.cemmap.ac.uk/wps/cwp261212.pdf [301 Moved Permanently]--> http://www.cemmap.ac.uk/wp-content/legacy/wps/cwp261212.pdf)
Related works:
Working Paper: Averaging of moment condition estimators (2012) 
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:ifs:cemmap:26/12
Ordering information: This working paper can be ordered from
The Institute for Fiscal Studies 7 Ridgmount Street LONDON WC1E 7AE
Access Statistics for this paper
More papers in CeMMAP working papers from Centre for Microdata Methods and Practice, Institute for Fiscal Studies The Institute for Fiscal Studies 7 Ridgmount Street LONDON WC1E 7AE. Contact information at EDIRC.
Bibliographic data for series maintained by Emma Hyman ().