Semiparametric competing risks analysis

被引：10
|
作者：
Canals-Cerda, Jose
Gurmu, Shiferaw
机构：
[1] Fed Reserve Bank Philadelphia, Philadelphia, PA 19106 USA
[2] Georgia State Univ, Andrew Young Sch Policy Studies, Dept Econ, Atlanta, GA 30302 USA
来源：
ECONOMETRICS JOURNAL | 2007年 / 10卷 / 02期
关键词：
competing risks; unobserved heterogeneity; series approximation; survival analysis;
D O I：
10.1111/j.1368-423X.2007.00205.x
中图分类号：
F [经济];
学科分类号：
02 ;
摘要：
In this paper we analyse a semi-parametric estimation technique for competing risks models based on series expansion of the joint density of the unobserved heterogeneity components. This technique allows for unrestricted correlation among the risks. The finite sample behavior of the estimation technique is analysed in a Monte Carlo experiment using an empirically relevant data-generating process. The estimator performs well when compared with the Heckman-Singer estimator.
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页码：193 / 215
页数：23
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