Bayesian semiparametric estimation of discrete duration models: An application of the Dirichlet process prior

被引:30
作者
Campolieti, M
机构
[1] Univ Toronto, Ctr Ind Relat, Toronto, ON M5S 3E8, Canada
[2] Univ Toronto, Div Management, Scarborough, ON M1C 1A4, Canada
关键词
D O I
10.1002/jae.587
中图分类号
F [经济];
学科分类号
02 ;
摘要
This paper proposes a Bayesian estimator for a discrete time duration model which incorporates a nonparametric specification of the unobserved heterogeneity distribution, through the use of a Dirichlet process prior. This estimator offers distinct advantages over the Nonparametric Maximum Likelihood estimator of this model. First, it allows for exact finite sample inference. Second, it is easily estimated and mixed with flexible specifications of the baseline hazard. An application of the model to employment duration data from the Canadian province of New Brunswick is provided. Copyright (C) 2001 John Wiley & Sons, Ltd.
引用
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页码:1 / 22
页数:22
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