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Generalized hurdle count data regression models

被引：49
|
作者：
Gurmu, S [1 ]
机构：
[1] Univ Virginia, Dept Econ, Charlottesville, VA 22903 USA
来源：
ECONOMICS LETTERS | 1998年 / 58卷 / 03期
关键词：
two-part model; double Poisson; generalized logit; heteroscedasticity;
D O I：
10.1016/S0165-1765(97)00295-4
中图分类号：
F [经济];
学科分类号：
02 ;
摘要：
This paper considers generalized hurdle models suitable for the analysis of overdispersed or underdispersed count data. The first stage allows for asymmetric departures from the binary logit model. An application using Medicaid utilization data is given. (C) 1998 Elsevier Science S.A.
引用
收藏
页码：263 / 268
页数：6
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