On the Use of Outcome Tests for Detecting Bias in Decision Making

47 Pages Posted: 14 Sep 2020 Last revised: 18 Nov 2021

See all articles by Ivan A Canay

Ivan A Canay

Northwestern University - Department of Economics

Magne Mogstad

University of Chicago

Jack Mountjoy

University of Chicago - Booth School of Business

Date Written: September 2020

Abstract

The decisions of judges, lenders, journal editors, and other gatekeepers often lead to disparities in outcomes across affected groups. An important question is whether, and to what extent, these group-level disparities are driven by relevant differences in underlying individual characteristics, or by biased decision makers. Becker (1957) proposed an outcome test for bias leading to a large body of related empirical work, with recent innovations in settings where decision makers are exogenously assigned to cases and vary progressively in their decision tendencies. We carefully examine what can be learned about bias in decision making in such settings. Our results call into question recent conclusions about racial bias among bail judges, and, more broadly, yield four lessons for researchers considering the use of outcome tests of bias. First, the so-called generalized Roy model, which is a workhorse of applied economics, does not deliver a logically valid outcome test without further restrictions, since it does not require an unbiased decision maker to equalize marginal outcomes across groups. Second, the more restrictive "extended" Roy model, which isolates potential outcomes as the sole admissible source of analyst-unobserved variation driving decisions, delivers both a logically valid and econometrically viable outcome test. Third, this extended Roy model places strong restrictions on behavior and the data generating process, so detailed institutional knowledge is essential for justifying such restrictions. Finally, because the extended Roy model imposes restrictions beyond those required to identify marginal outcomes across groups, it has testable implications that may help assess its suitability across empirical settings.

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Suggested Citation

Canay, Ivan A and Mogstad, Magne and Mountjoy, Jack, On the Use of Outcome Tests for Detecting Bias in Decision Making (September 2020). NBER Working Paper No. w27802, Available at SSRN: https://ssrn.com/abstract=3692158 or http://dx.doi.org/10.2139/ssrn.3692158

Ivan A Canay (Contact Author)

Northwestern University - Department of Economics ( email )

2003 Sheridan Road
Evanston, IL 60208
United States

Magne Mogstad

University of Chicago ( email )

1101 East 58th Street
Chicago, IL 60637
United States

Jack Mountjoy

University of Chicago - Booth School of Business ( email )

5807 S. Woodlawn Avenue
Chicago, IL 60637
United States

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