Estimating the Link Function in Multinomial Response Models Under Endogeneity

21 Pages Posted: 13 Nov 2003

See all articles by George Judge

George Judge

University of California, Berkeley - Department of Agricultural & Resource Economics

Ron Mittelhammer

Washington State University - Department of Agricultural and Resource Economics

Douglas J. Miller

University of Missouri at Columbia - Department of Economics

Abstract

This paper considers estimation and inference for the multinomial response model in the case where endogenous variables are included as arguments of the unknown link function. Semiparametric estimators are proposed that avoid the parametric assumptions underlying the likelihood approach as well as the loss of precision when using nonparametric estimation. The large sample properties of the estimators are also developed in the context of a quasi-likelihood modeling framework.

Keywords: multinomial process, endogeneity, empirical likelihood procedures, semiparametric estimation and inference, quasi-likelihood estimation

JEL Classification: C10, C24

Suggested Citation

Judge, George G. and Mittelhammer, Ron C. and Miller, Douglas J., Estimating the Link Function in Multinomial Response Models Under Endogeneity. Available at SSRN: https://ssrn.com/abstract=468101 or http://dx.doi.org/10.2139/ssrn.468101

George G. Judge (Contact Author)

University of California, Berkeley - Department of Agricultural & Resource Economics ( email )

207 Giannini Hall
University of California
Berkeley, CA 94720
United States

Ron C. Mittelhammer

Washington State University - Department of Agricultural and Resource Economics ( email )

111E Hulbert Hall
Pullman, WA 99164-4741
United States

HOME PAGE: http://www.arec.wsu.edu/people/mittelha.htm

Douglas J. Miller

University of Missouri at Columbia - Department of Economics ( email )

118 Professional Building
Columbia, MO 65211
United States

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