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A Characterisation of 'Phelpsian' Statistical Discrimination

Chambers, Christopher P. and Echenique, Federico (2021) A Characterisation of 'Phelpsian' Statistical Discrimination. Economic Journal, 131 (637). pp. 2018-2032. ISSN 0013-0133. doi:10.1093/ej/ueaa107.

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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).

Item Type:Article
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URLURL TypeDescription Paper ItemWorking Paper
Chambers, Christopher P.0000-0001-8253-0328
Echenique, Federico0000-0002-1567-6770
Alternate Title:A characterization of "Phelpsian" statistical discrimination
Additional Information:© 2020 Royal Economic Society. Published by Oxford University Press. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model ( Received: 16 May 2019; Accepted: 17 August 2020; Published: 29 August 2020. Echenique thanks the NSF for support through the grants SES-1558757 and CNS-1518941. We are grateful to Leeat Yariv for comments on a previous draft.
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Issue or Number:637
Record Number:CaltechAUTHORS:20210729-212407084
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Official Citation:Christopher P Chambers, Federico Echenique, A Characterisation of ‘Phelpsian’ Statistical Discrimination, The Economic Journal, Volume 131, Issue 637, July 2021, Pages 2018–2032,
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:110079
Deposited By: Tony Diaz
Deposited On:02 Aug 2021 18:42
Last Modified:02 Aug 2021 18:42

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