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Estimating Gender Differences in Access to Jobs

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  • 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 - PSL - Université Paris sciences et lettres, PSE - Paris School of Economics - ENPC - École des Ponts ParisTech - ENS Paris - École normale supérieure - Paris - PSL - Université Paris sciences et lettres - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique - EHESS - École des hautes études en sciences sociales - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, 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 Paris - 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

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    Cited by:

    1. Anthony B. Atkinson & Alessandra Casarico & Sarah Voitchovsky, 2018. "Top incomes and the gender divide," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 16(2), pages 225-256, June.
    2. Clément Bosquet & Pierre‐Philippe Combes & Cecilia García‐Peñalosa, 2019. "Gender and Promotions: Evidence from Academic Economists in France," Scandinavian Journal of Economics, Wiley Blackwell, vol. 121(3), pages 1020-1053, July.
    3. P. Pora & L. Wilner, 2019. "Child Penalties and Financial Incentives: Exploiting Variation along the Wage Distribution," Documents de Travail de l'Insee - INSEE Working Papers g2019-08, Institut National de la Statistique et des Etudes Economiques.
    4. Gobillon, Laurent & Meurs, Dominique & Roux, Sébastien, 2017. "Differences in Positions along a Hierarchy: Counterfactuals Based on an Assignment Model," IZA Discussion Papers 10726, Institute of Labor Economics (IZA).
    5. Elise Coudin & Sophie Maillard & Maxime Tô, 2018. "Family, Firms and the Gender Wage Gap in France," Working Papers 2018-09, Center for Research in Economics and Statistics.
    6. Field, Laura Casares & Souther, Matthew E. & Yore, Adam S., 2020. "At the table but can not break through the glass ceiling:Board leadership positions elude diverse directors," Journal of Financial Economics, Elsevier, vol. 137(3), pages 787-814.
    7. Laurent Gobillon & Dominique Meurs & Sébastien Roux, 2017. "Differences in positions along a hierarchy: Counterfactuals based on an assignment," Working Papers halshs-01513012, HAL.
    8. Bertrand Garbinti & Jonathan Goupille-Lebret, 2019. "Income and Wealth Inequality in France: Developments and Links over the Long Term," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Études Économiques (INSEE), issue 510-511-5, pages 69-87.
    9. Matthias Collischon, 2019. "Is There a Glass Ceiling over Germany?," German Economic Review, Verein für Socialpolitik, vol. 20(4), pages 329-359, November.
    10. Lamia E. Kandil, 2015. "Disentangling qualitative and quantitative central bank influence," Documents de Travail de l'OFCE 2015-02, Observatoire Francais des Conjonctures Economiques (OFCE).
    11. Fathi Fakhfakh & Annick Vignes & Jihan Ghrairi, 2015. "Youth ! ... How did you find your job ?," Working Papers hal-01253907, HAL.
    12. Bredemeier, Christian, 2019. "Gender Gaps in Pay and Inter-Firm Mobility," IZA Discussion Papers 12785, Institute of Labor Economics (IZA).
    13. Yannick L’Horty & Dominique Meurs, 2016. "Introduction. Analyser les inégalités salariales entre les hommes et les femmes dans la fonction publique avec les données du Système d’information sur les agents des services publics," Économie et Statistique, Programme National Persée, vol. 488(1), pages 89-95.
    14. Lamia Kandil, 2015. "Glass ceiling and belief flipping : theory and evidence from Egypt," Sciences Po publications 2015-02, Sciences Po.

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    More about this item

    Keywords

    Gender; Discrimination; Wages; Quantiles; Job assignment model; Glass ceiling;
    All these keywords.

    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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