Gender Segregation: From Birth To Occupation
This paper offers a framework to study the gender segregation induced, not only by occupational choices among the employed population, but also by human capital characteristics and labor market participation decisions in the population consisting of non-students of working age. For that purpose, an additively decomposable gender segregation index related to the entropy notion in information theory is used. The approach is illustrated with Labor Force Survey data for Spain in 1977 and 1992. It is found that gender differences in labor market participation behavior is the most important source generating gender segregation in a given moment in time and the reduction in overall gender segregation during this period.
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- Ricardo Mora & Javier Ruiz-Castillo & Neus Herranz, 2005.
"An algorithm to reduce the occupational space in gender segregation studies,"
Journal of Applied Econometrics,
John Wiley & Sons, Ltd., vol. 20(1), pages 25-37.
- Neus Herranza & Ricardo Mora & Javier Ruiz-Castillo, 2003. "An Algorithm To Reduce The Occupational Space In Gender Segregation Studies," Economics Working Papers we031402, Universidad Carlos III, Departamento de Economía.
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- Ricardo Mora & Javier Ruiz-Castillo, 2003.
"Additively Decomposable Segregation Indexes. The Case Of Gender Segregation By Occupations And Human Capital Levels In Spain,"
Economics Working Papers
we031503, Universidad Carlos III, Departamento de Economía.
- Ricardo Mora & Javier Ruiz-Castillo, 2003. "Additively Decomposable Segregation Indexes. The Case of Gender Segregation by Occupations and Human Capital Levels in Spain," Journal of Economic Inequality, Springer, vol. 1(2), pages 147-179, August.
- Ricardo Mora & Javier Ruiz-Castillo, 2003. "An Evaluation Of An Entropy Based Index Of Segregation," Economics Working Papers we034014, Universidad Carlos III, Departamento de Economía.
- Silber, Jacques, 1989. "Factor Components, Population Subgroups and the Computation of the Gini Index of Inequality," The Review of Economics and Statistics, MIT Press, vol. 71(1), pages 107-15, February.
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