IDEAS home Printed from https://ideas.repec.org/a/adr/anecst/y2022i145p29-74.html

Differences in Positions along a Hierarchy: Counterfactuals Based on an Assignment Model

Author

Listed:
  • Laurent Gobillon
  • Dominique Meurs
  • Sébastien Roux

Abstract

We propose an assignment model in which positions along a hierarchy are attributed to individuals depending on their characteristics. Our theoretical framework can be used to study differences in assignment and pay-offs across groups and we show how it can motivate decomposition and counterfactual exercises. In an application, we study gender disparities in the public and private sectors with a French exhaustive administrative dataset. The gender wage gap in the public sector is 13.3% and it increases by only 0.7 percentage points when workers are assigned to job positions according to the rules of the private sector.

Suggested Citation

  • Laurent Gobillon & Dominique Meurs & Sébastien Roux, 2022. "Differences in Positions along a Hierarchy: Counterfactuals Based on an Assignment Model," Annals of Economics and Statistics, GENES, issue 145, pages 29-74.
    • Handle: RePEc:adr:anecst:y:2022:i:145:p:29-74
    DOI: https://doi.org/10.2307/48655901
    as

    Download full text from publisher

    File URL: https://www.jstor.org/stable/48655901
    Download Restriction: no
    File URL: https://libkey.io/https://doi.org/10.2307/48655901?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Other versions of this item:

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Matthieu Bunel & Dominique Meurs & Élisabeth Tovar, 2024. "Moving apart: job-driven residential mobility and the gender pay gap Evidence from a large industrial firm," Working Papers hal-04461137, HAL.
    2. Bargain, Olivier B. & Etienne, Audrey & Melly, Blaise, 2018. "Public Sector Wage Gaps over the Long-Run: Evidence from Panel Administrative Data," IZA Discussion Papers 11924, Institute of Labor Economics (IZA).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • J45 - Labor and Demographic Economics - - Particular Labor Markets - - - Public Sector Labor Markets

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:adr:anecst:y:2022:i:145:p:29-74. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Secretariat General or Laurent Linnemer (email available below). General contact details of provider: https://edirc.repec.org/data/ensaefr.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.