Exclusion restrictions are routinely used in sample-selection models with “selection” and “outcome” equations. A false restriction, however, can cause an “exclusion bias” for the outcome equation estimator. In this paper, the specific form of the exclusion bias is derived for various sample-selection model estimators. Furthermore, it is shown that the outcome equation parameters for regressors with zero coefficients in the selection equation are immune to exclusion bias if only one regressor is excluded. Exclusion bias, or a lack thereof, is verified through a simulation study with the regressors taken from Mroz (1987).
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Department of Economics, Penn State University, Media, PA 19063, Brandywine CampusDepartment of Economics, Penn State University, Media, PA 19063, Brandywine Campus
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Univ Bologna, Dept Stat Sci P Fortunati, Via Belle Arti 41, I-40126 Bologna, ItalyUniv Bologna, Dept Stat Sci P Fortunati, Via Belle Arti 41, I-40126 Bologna, Italy
De Nicolo, Silvia
Ferrante, Maria Rosaria
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Univ Bologna, Dept Stat Sci P Fortunati, Via Belle Arti 41, I-40126 Bologna, ItalyUniv Bologna, Dept Stat Sci P Fortunati, Via Belle Arti 41, I-40126 Bologna, Italy
Ferrante, Maria Rosaria
Pacei, Silvia
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Univ Bologna, Dept Stat Sci P Fortunati, Via Belle Arti 41, I-40126 Bologna, ItalyUniv Bologna, Dept Stat Sci P Fortunati, Via Belle Arti 41, I-40126 Bologna, Italy