Title
Semiparametric Maximum Profile Likelihood Estimation of Polytomous and Sequential Choice Models
Publisher
Center for Economic Research, Department of Economics, University of Minnesota
Abstract
This article considers semiparametric estimation of discrete choice models. The estimation methods
are some semiparametric maximum profile likelihood methods which generalize Klein and Spady [1987] to
the estimation of polytomous choice and sequential choice models. Special emphases are on the correction
of asymptotic bias and negative density estimates caused by high order kernel density estimation. The
estimators are shown to be Vn consistent and asymptotically normal. They attain the asymptotic efficiency
bound of semiparametric estimation with some infinite dimensional parameter spaces of index probability
functions.
Previously Published Citation
Lee, L., (1989), "Semiparametric Maximum Profile Likelihood Estimation of Polytomous and Sequential Choice Models", Discussion Paper No. 253, Center for Economic Research, Department of Economics, University of Minnesota.
Suggested Citation
Lee, Lung-Fei.
(1989).
Semiparametric Maximum Profile Likelihood Estimation of Polytomous and Sequential Choice Models.
Center for Economic Research, Department of Economics, University of Minnesota.
Retrieved from the University of Minnesota Digital Conservancy,
https://hdl.handle.net/11299/55532.