Maximum likelihood and two-step estimation of an ordered-probit selection model

被引：55
|
作者：
Chiburis, Richard [1 ]
Lokshin, Michael
机构：
[1] Princeton Univ, Princeton, NJ 08544 USA
[2] World Bank, Dev Econ Res Grp, Washington, DC 20433 USA
来源：
STATA JOURNAL | 2007年 / 7卷 / 02期
关键词：
st0123; oheckman; selection bias; ordered probit; maximum likelihood;
D O I：
10.1177/1536867X0700700202
中图分类号：
O1 [数学]; C [社会科学总论];
学科分类号：
03 ; 0303 ; 0701 ; 070101 ;
摘要：
We discuss the estimation of a regression model with an ordered-probit selection rule. We have written a Stata command, oheckman, that computes two-step and full-information rnaximum-likelihood estimates of this model. Using Monte Carlo simulations, we compare the performances of these estimators under various conditions.
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页码：167 / 182
页数：16
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