Estimating the Link Function in Multinomial Response Models under Endogeneity and Quadratic Loss

George Judge () and Ron Mittelhammer ()

Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series from Department of Agricultural & Resource Economics, UC Berkeley

Abstract: This paper considers estimation and inference for the multinomial response model in the case where endogenous variables are 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. A data based shrinkage estimator that seeks an optimal combination of estimators and results in superior risk performance under quadratic loss is also developed.

Keywords: multinomial process; endogeneity; empirical likelihood procedures; quadratic loss; semiparametric estimation and inference; data dependent shrinkage; asymptotic and finite sample risk (search for similar items in EconPapers)
Date: 2004-02-03
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Citations: View citations in EconPapers (3)

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Working Paper: Estimating the Link Function in Multinomial Response Models under Endogeneity and Quadratic Loss (2004)
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Persistent link: https://EconPapers.repec.org/RePEc:cdl:agrebk:qt4422n50w

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