IDEAS home Printed from https://ideas.repec.org/a/oup/econjl/v131y2021i637p2018-2032..html

A Characterisation of ‘Phelpsian’ Statistical Discrimination

Author

Listed:
  • Christopher P Chambers
  • Federico Echenique

Abstract

We establish that a type of statistical discrimination—that based on informativeness of signals about workers’ skills and the ability appropriately to match workers to tasks—is possible if and only if it is impossible uniquely to identify the signal structure observed by an employer from a realised empirical distribution of skills. The impossibility of statistical discrimination is shown to be equivalent to the existence of a fair, skill-dependent, remuneration for workers. Finally, we connect the statistical discrimination literature to Bayesian persuasion, establishing that if discrimination is absent, then the optimal signalling problem results in a linear pay-off function (as well as a kind of converse).

Suggested Citation

  • Christopher P Chambers & Federico Echenique, 2021. "A Characterisation of ‘Phelpsian’ Statistical Discrimination," The Economic Journal, Royal Economic Society, vol. 131(637), pages 2018-2032.
  • Handle: RePEc:oup:econjl:v:131:y:2021:i:637:p:2018-2032.
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1093/ej/ueaa107
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or

    for a different version of it.

    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. Jean-Paul Carvalho & Bary S. R. Pradelski & Cole Williams, 2025. "Intersectionality: Affirmative Action with Multidimensional Identities," Management Science, INFORMS, vol. 71(5), pages 4495-4509, May.

    More about this item

    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:oup:econjl:v:131:y:2021:i:637:p:2018-2032.. 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: Oxford University Press or the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/resssea.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.