Semiparametric and nonparametric estimation of sample selection models under symmetry

被引:23
|
作者
Chen, Songnian [1 ,2 ]
Zhou, Yahong [3 ]
机构
[1] Hong Kong Univ Sci & Technol, Dept Econ, Hong Kong, Hong Kong, Peoples R China
[2] Natl Univ Singapore, Singapore 117548, Singapore
[3] Shanghai Univ Finance & Econ, Sch Econ, Shanghai, Peoples R China
关键词
Sample selection models; Symmetry distribution; Heteroscedasticity; CENSORED REGRESSION-MODELS; ADAPTIVE ESTIMATION; EFFICIENCY BOUNDS; BINARY CHOICE; IDENTIFICATION; BIAS;
D O I
10.1016/j.jeconom.2009.10.022
中图分类号
F [经济];
学科分类号
02 ;
摘要
This paper considers the semiparametric estimation of binary choice sample selection models under a joint symmetry assumption. Our approaches overcome various drawbacks associated with existing estimators. In particular, our method provides root-n consistent estimators for both the intercept and slope parameters of the outcome equation in a heteroscedastic framework, without the usual cross equation exclusion restriction or parametric specification for the error distribution and/or the form of heteroscedasticity. Our two-step estimators are shown to be consistent and asymptotically normal. A Monte Carlo simulation study indicates the usefulness of our approaches. (C) 2009 Elsevier B.V. All rights reserved.
引用
收藏
页码:143 / 150
页数:8
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