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POOLING ESTIMATES WITH DIFFERENT RATES OF CONVERGENCE: A MINIMUM χ2 APPROACH WITH EMPHASIS ON A SOCIAL INTERACTIONS MODEL

Published online by Cambridge University Press:  19 June 2009

Lung-fei Lee
Lung-fei Lee*
Affiliation:
Ohio State University
*
*Address Correspondance to Lung-fei Lee, Department of Economics, Ohio State University, 410 Arps Hall, 1945 N. High St., Columbus, OH 43210-1172; e-mail: [email protected].
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Abstract

This paper considers the extension of the classical minimum distance approach for the pooling of estimates with various rates of convergence. Under a setting where relatively high rates of convergence can be attained, the minimum distance estimators are shown to be consistent and asymptotically normally distributed. The constrained estimates can be efficient relative to the unconstrained ones. The minimized distance function is shown to be asymptotically χ2-distributed, and can be used as a goodness-of-fit test for the constraints. As the extension is motivated by some social interactions models, which are of interest in their own right, we discuss this approach for the estimation and testing of a social interactions model.

Type
ARTICLES
Information
Econometric Theory , Volume 26 , Issue 1 , February 2010 , pp. 260 - 299
Copyright
Copyright © Cambridge University Press 2009

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