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

Arbeitspapier

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.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Diskussionsbeitrag ; No. 503

Classification and Topics

• Classification: Wirtschaft ; Single Equation Models; Single Variables: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions ; Single Equation Models; Single Variables: Truncated and Censored Models; Switching Regression Models; Threshold Regression Models ; Labor Force and Employment, Size, and Structure ; Wage Level and Structure; Wage Differentials
• Subject: Sample selection model ; semiparametric estimation ; copula approach ; composition of the female workforce ; female labor force participation

Contributors, Location and Time

• Event: Geistige Schöpfung
• (who): Schwiebert, Jörg
• Event: Veröffentlichung
• (who): Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät
• (where): Hannover
• (when): 2012

Further information

• Handle: http://hdl.handle.net/10419/73128
• Last update: 10.03.2025, 11:45 AM CET