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Misspecification and Conditional Maximum Likelihood Estimation

Vuong, Quang H. (1983) Misspecification and Conditional Maximum Likelihood Estimation. Social Science Working Paper, 503. California Institute of Technology , Pasadena, CA. (Unpublished) http://resolver.caltech.edu/CaltechAUTHORS:20170920-161718102

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Abstract

Recently White (1982) studied the properties of Maximum Likelihood estimation of possibly misspecified models. The present paper extends Andersen (1970) results on Conditional Maximum Likelihood estimators (CMLE) to such a situation. In particular, the asymptotic properties of CMLE's are derived under correct and incorrect specification of the conditional model. Robustness of conditional inferences and estimation with respect to misspecification of the model for the conditioning variables is emphasized. Conditions for asymptotic efficiency of CMLE's are obtained, and specification tests a la Hausman (1978) and White (1982) are derived. Examples are also given to illustrate the use of CMLE's properties. These examples include the simple linear model, the multinomial logit model, the simple Tobit model, and the multivariate logit model.


Item Type:Report or Paper (Working Paper)
Additional Information:Revised. Original dated to April 1983. I am much indebted to J. Dubin, R. Engle, D. Grether, J. Link, D. Rivers, and H. White for helpful comments and criticism. Remaining errors are of course mine.
Group:Social Science Working Papers
Record Number:CaltechAUTHORS:20170920-161718102
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20170920-161718102
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:81658
Collection:CaltechAUTHORS
Deposited By: Jacquelyn Bussone
Deposited On:20 Sep 2017 23:31
Last Modified:20 Sep 2017 23:31

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