Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/73118
Authors: 
Schwiebert, Jörg
Year of Publication: 
2012
Series/Report no.: 
Diskussionspapiere der Wirtschaftswissenschaftlichen Fakultät, Universität Hannover 505
Abstract: 
In this paper we provide semiparametric estimation strategies for a sample selection model with a binary dependent variable. To the best of our knowledge, this has not been done before. We propose a control function approach based on two di erent identifying assumptions. This gives rise to semiparametric estimators which are extensions of the Klein and Spady (1993), maximum score (Manski, 1975) and smoothed maximum score (Horowitz, 1992) estimators. We provide Monte Carlo evidence and an empirical example to study the nite sample properties of our estimators. Finally, we outline an extension of these estimators to the case of endogenous covariates.
Subjects: 
Sample selection model
binary dependent variable
semiparametric estimation
control function approach
endogenous covariates
JEL: 
C21
C24
C25
C26
Document Type: 
Working Paper

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