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Analyzing the Composition of the Female Workforce - A Semiparametric Copula Approach

Autor: Jörg Schwiebert
Nummer: 503, Oct 2012, pp. 30
JEL-Class: C21, C24, J21, J31

Abstract:
We provide a semiparametric copula approach for estimating a 'classical' sample selection model. We impose that the joint distribution function of unobservables can be characterized by a specifc copula, but the marginal distribution functions are estimated semiparametrically. In contrast to existing semiparametric estimators for sample selection models, our approach provides a measure of dependence between unobservables in main and selection equation which can be used to analyze the composition of, say, the female workforce. We apply our estimation procedure to a female labor supply data set and show that those women with the best skills participate in the labor market; moreover, we find evidence for the existence of an ability threshold which involves that women with high ability are to some extent advantaged and, therefore, have also obtained the best skills.

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