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Estimating Gender Differences in Access to Jobs

Author

Listed:
  • Laurent Gobillon

    (PSE - Paris-Jourdan Sciences Economiques - CNRS - Centre National de la Recherche Scientifique - ENPC - École des Ponts ParisTech - EHESS - École des hautes études en sciences sociales - INRA - Institut National de la Recherche Agronomique - ENS Paris - École normale supérieure - Paris, PSE - Paris School of Economics, INED - Institut national d'études démographiques, CEPR - Center for Economic Policy Research - CEPR, IZA - Institute for the Study of Labor - IZA)

  • Dominique Meurs

    (INED - Institut national d'études démographiques, EconomiX - UPN - Université Paris Nanterre - CNRS - Centre National de la Recherche Scientifique)

  • Sébastien Roux

    () (CREST - Centre de Recherche en Économie et Statistique - ENSAI - Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz] - X - École polytechnique - ENSAE ParisTech - École Nationale de la Statistique et de l'Administration Économique - CNRS - Centre National de la Recherche Scientifique, DARES - Direction de l'animation de la recherche, des études et des statistiques - Ministère du Travail, de l'Emploi et de la Santé)

Abstract

This paper proposes a new measure of gender di¤erences in access to jobs based on a job assignment model. This measure is the probability ratio of getting a job for females and males at each rank of the wage ladder. We derive a non-parametric estimator of this access measure and estimate it for French full-time executives aged 40 - 45 in the private sector. Our results show that the gender di¤erence in the probability of getting a job increases along the wage ladder from 9% to 50%. Females thus have a signi.cantly lower access to high-paid jobs than to low-paid jobs.

Suggested Citation

  • Laurent Gobillon & Dominique Meurs & Sébastien Roux, 2013. "Estimating Gender Differences in Access to Jobs," Working Papers halshs-00849072, HAL.
  • Handle: RePEc:hal:wpaper:halshs-00849072
    Note: View the original document on HAL open archive server: https://halshs.archives-ouvertes.fr/halshs-00849072
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    References listed on IDEAS

    as
    1. Sattinger, Michael, 1993. "Assignment Models of the Distribution of Earnings," Journal of Economic Literature, American Economic Association, vol. 31(2), pages 831-880, June.
    2. Gobillon, Laurent & Meurs, Dominique & Roux, Sébastien, 2009. "Estimating Gender Differences in Access to Jobs: Females Trapped at the Bottom of the Ladder," CEPR Discussion Papers 7475, C.E.P.R. Discussion Papers.
    3. John M. Abowd & Francis Kramarz & Sébastien Roux, 2006. "Wages, Mobility and Firm Performance: Advantages and Insights from Using Matched Worker-Firm Data," Economic Journal, Royal Economic Society, vol. 116(512), pages 245-285, June.
    4. Ridder, Geert & Tunali, Insan, 1999. "Stratified partial likelihood estimation," Journal of Econometrics, Elsevier, vol. 92(2), pages 193-232, October.
    5. Robert M. Costrell & Glenn C. Loury, 2004. "Distribution of Ability and Earnings in a Hierarchical Job Assignment Model," Journal of Political Economy, University of Chicago Press, vol. 112(6), pages 1322-1363, December.
    6. Cornell, Bradford & Welch, Ivo, 1996. "Culture, Information, and Screening Discrimination," Journal of Political Economy, University of Chicago Press, vol. 104(3), pages 542-571, June.
    7. James Albrecht & Anders Bjorklund & Susan Vroman, 2003. "Is There a Glass Ceiling in Sweden?," Journal of Labor Economics, University of Chicago Press, vol. 21(1), pages 145-177, January.
    8. Teulings, Coen N, 1995. "The Wage Distribution in a Model of the Assignment of Skills to Jobs," Journal of Political Economy, University of Chicago Press, vol. 103(2), pages 280-315, April.
    9. Phelps, Edmund S, 1972. "The Statistical Theory of Racism and Sexism," American Economic Review, American Economic Association, vol. 62(4), pages 659-661, September.
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