Affirmative Action with Multidimensional Identities

29 Pages Posted: 8 Apr 2022 Last revised: 17 Dec 2022

See all articles by Jean-Paul Carvalho

Jean-Paul Carvalho

Department of Economics, University of Oxford

Bary Pradelski

CNRS, Maison Francaise

Cole Williams

University of Vienna

Multiple version iconThere are 2 versions of this paper

Date Written: December 16, 2022

Abstract

Affirmative action policies are widely employed in college admissions, hiring, and other decisions to reduce underrepresentation of disadvantaged groups. When identities are multidimensional, the basic unit of analysis is the intersectional group (i.e., identity vector). Affirmative action policies are, however, predominantly nonintersectional, being based on the identity dimensions, not the intersectional identities. We demonstrate that any nonintersectional policy can almost never achieve a representative outcome. In fact, nonintersectional policies can increase the underrepresentation of underrepresented groups in a manner undetected by standard (nonintersectional) measures. Examples based on race and gender in the United States reveal significant (hidden) losses from nonintersectional policies. Accounting for interactions between identity dimensions, we show how to construct intersectional policies that achieve proportional representation.

Keywords: Affirmative action, education, inequality, underrepresentation, identity, intersectionality

JEL Classification: J7, I24, D02

Suggested Citation

Carvalho, Jean-Paul and Pradelski, Bary and Williams, Cole, Affirmative Action with Multidimensional Identities (December 16, 2022). Available at SSRN: https://ssrn.com/abstract=4070930 or http://dx.doi.org/10.2139/ssrn.4070930

Jean-Paul Carvalho (Contact Author)

Department of Economics, University of Oxford ( email )

10 Manor Rd
Oxford, OX1 3UQ
United Kingdom

Bary Pradelski

CNRS, Maison Francaise ( email )

Cole Williams

University of Vienna ( email )

Bruenner Strasse 72
Vienna, Vienna 1090
Austria

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