Semiparametric and nonparametric estimation of sample selection models under symmetry
被引:23
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作者:
Chen, Songnian
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机构:
Hong Kong Univ Sci & Technol, Dept Econ, Hong Kong, Hong Kong, Peoples R China
Natl Univ Singapore, Singapore 117548, SingaporeHong Kong Univ Sci & Technol, Dept Econ, Hong Kong, Hong Kong, Peoples R China
Chen, Songnian
[1
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论文数: 引用数:
h-index:
机构:
Zhou, Yahong
[3
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机构:
[1] Hong Kong Univ Sci & Technol, Dept Econ, Hong Kong, Hong Kong, Peoples R China
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.
机构:
Korea Univ, Dept Econ, Seoul 136701, South Korea
Australian Natl Univ, Res Sch Econ, Canberra, ACT 0200, AustraliaKorea Univ, Dept Econ, Seoul 136701, South Korea