Large Sample Properties of Generalized Method of Moments Estimators
Econometrica (1982)
- ISSN: 00129682
- DOI: 10.2307/1912775
- PubMed: 100
Available from www.jstor.org
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Abstract
This paper studies estimators that make sample analogues of population orthogonality conditions close to zero. Strong consistency and asymptotic normality of such estimators is established under the assumption that the observable variables are stationary and ergodic. Since many linear and nonlinear econometric estimators reside within the class of estimators studied in this paper, a convenient summary of the large sample properties of these estimators, including some whose large sample properties have not heretofore been discussed, is provided.
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Large Sample Properties of Generalized Method of Moments Estimators
Large Sample Properties of Generalized Method of Moments Estimators
Lars Peter Hansen
Econometrica, Vol. 50, No. 4. (Jul., 1982), pp. 1029-1054.
Stable URL:
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Econometrica is currently published by The Econometric Society.
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Mon Jun 4 12:31:21 2007
Lars Peter Hansen
Econometrica, Vol. 50, No. 4. (Jul., 1982), pp. 1029-1054.
Stable URL:
http://links.jstor.org/sici?sici=0012-9682%28198207%2950%3A4%3C1029%3ALSPOGM%3E2.0.CO%3B2-O
Econometrica is currently published by The Econometric Society.
Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at
http://www.jstor.org/about/terms.html. JSTOR's Terms and Conditions of Use provides, in part, that unless you have obtained
prior permission, you may not download an entire issue of a journal or multiple copies of articles, and you may use content in
the JSTOR archive only for your personal, non-commercial use.
Please contact the publisher regarding any further use of this work. Publisher contact information may be obtained at
http://www.jstor.org/journals/econosoc.html.
Each copy of any part of a JSTOR transmission must contain the same copyright notice that appears on the screen or printed
page of such transmission.
JSTOR is an independent not-for-profit organization dedicated to and preserving a digital archive of scholarly journals. For
more information regarding JSTOR, please contact support@jstor.org.
http://www.jstor.org
Mon Jun 4 12:31:21 2007
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