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Estimating gender differences in access to jobs: females trapped at the bottom of the ladder

Author

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  • Laurent Gobillon

    (LEA - Laboratoire d'Economie Appliquée - INRA - Institut National de la Recherche Agronomique, CREST - Centre de Recherche en Économie et Statistique - ENSAI - Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz] - CNRS - Centre National de la Recherche Scientifique - X - École polytechnique - ENSAE ParisTech - École Nationale de la Statistique et de l'Administration Économique, CEPR - Center for Economic Policy Research - CEPR, INED - Institut national d'études démographiques, PSE - Paris School of Economics, PJSE - Paris-Jourdan Sciences Economiques - ENS Paris - École normale supérieure - Paris - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique)

  • Dominique Meurs

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

  • Sébastien Roux

    () (LEA - Laboratoire d'Economie Appliquée - INRA - Institut National de la Recherche Agronomique, CREST - Centre de Recherche en Économie et Statistique - ENSAI - Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz] - CNRS - Centre National de la Recherche Scientifique - X - École polytechnique - ENSAE ParisTech - École Nationale de la Statistique et de l'Administration Économique, PSE - Paris School of Economics)

Abstract

In this paper, we propose a job assignment model allowing for a gender difference in access to jobs. Males and females compete for the same job positions. They are primarily interested in the best-paid jobs. A structural relationship of the model can be used to empirically recover the probability ratio of females and males getting a given job position. As this ratio is allowed to vary with the rank of jobs in the wage distribution of positions, barriers in females' access to high-paid jobs can be detected and quantiffed. We estimate the gender relative probability of getting any given job position for full-time executives aged 40-45 in the private sector. This is done using an exhaustive French administrative dataset on wage bills. Our results show that the access to any job position is lower for females than for males. Also, females' access decreases with the rank of job positions in the wage distribution, which is consistent with females being faced with more barriers to high-paid jobs than to low-paid jobs. At the bottom of the wage distribution, the probability of females getting a job is 12% lower than the probability of males. The difference in probability is far larger at the top of the wage distribution and climbs to 50%.

Suggested Citation

  • Laurent Gobillon & Dominique Meurs & Sébastien Roux, 2009. "Estimating gender differences in access to jobs: females trapped at the bottom of the ladder," PSE Working Papers halshs-00575011, HAL.
  • Handle: RePEc:hal:psewpa:halshs-00575011
    Note: View the original document on HAL open archive server: https://halshs.archives-ouvertes.fr/halshs-00575011
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    References listed on IDEAS

    as
    1. Pierre‐Philippe Combes & Gilles Duranton & Laurent Gobillon & Diego Puga & Sébastien Roux, 2012. "The Productivity Advantages of Large Cities: Distinguishing Agglomeration From Firm Selection," Econometrica, Econometric Society, vol. 80(6), pages 2543-2594, November.
    2. Stephen G. Donald & David A. Green & Harry J. Paarsch, 2000. "Differences in Wage Distributions Between Canada and the United States: An Application of a Flexible Estimator of Distribution Functions in the Presence of Covariates," Review of Economic Studies, Oxford University Press, vol. 67(4), pages 609-633.
    3. Pierre Cahuc & André Zylberberg, 2004. "Labor Economics," MIT Press Books, The MIT Press, edition 1, volume 1, number 026203316x, December.
    4. Ridder, Geert & Tunali, Insan, 1999. "Stratified partial likelihood estimation," Journal of Econometrics, Elsevier, vol. 92(2), pages 193-232, October.
    5. Dagsvik, John K, 1994. "Discrete and Continuous Choice, Max-Stable Processes, and Independence from Irrelevant Attributes," Econometrica, Econometric Society, vol. 62(5), pages 1179-1205, September.
    6. 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.
    7. Winter-Ebmer, Rudolf & Zweimuller, Josef, 1997. "Unequal Assignment and Unequal Promotion in Job Ladders," Journal of Labor Economics, University of Chicago Press, vol. 15(1), pages 43-71, January.
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    Cited by:

    1. Laurent Gobillon & Dominique Meurs & Sébastien Roux, 2015. "Estimating Gender Differences in Access to Jobs," Journal of Labor Economics, University of Chicago Press, vol. 33(2), pages 317-363.

    More about this item

    Keywords

    job assignment model; quantiles; gender; discrimination; wages; glass ceiling;

    JEL classification:

    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • J71 - Labor and Demographic Economics - - Labor Discrimination - - - Hiring and Firing

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