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

Jörg Schwiebert

Hannover Economic Papers (HEP) from Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät

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.

Keywords: Sample selection model; semiparametric estimation; copula approach; composition of the female workforce; female labor force participation (search for similar items in EconPapers)
JEL-codes: C21 C24 J21 J31 (search for similar items in EconPapers)
Pages: 30 pages
Date: 2012-10
New Economics Papers: this item is included in nep-ecm and nep-lma
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