Semiparametric Maximum Profile Likelihood Estimation of Polytomous and Sequential Choice Models

Lee, Lung-Fei
1989-12
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Semiparametric Maximum Profile Likelihood Estimation of Polytomous and Sequential Choice Models

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1989-12

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Center for Economic Research, Department of Economics, University of Minnesota

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Working Paper

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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.

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Center for Economic Research Discussion Papers

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Discussion Paper
 253

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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.

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Lee, Lung-Fei. (1989). Semiparametric Maximum Profile Likelihood Estimation of Polytomous and Sequential Choice Models. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/55532.

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