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  5. CSMGEP - Measuring Discrimination
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CSMGEP - Measuring Discrimination

Paper Session

Saturday, Jan. 6, 2024 8:00 AM - 10:00 AM (CST)

Grand Hyatt, Lone Star Ballroom Salon A
This session was streamed live.
Hosted By: American Economic Association & Committee on the Status of Minority Groups in the Economics Profession
  • Chair: Monica Garcia-Perez, St. Cloud State University and Duke University

Shocking Offers: Gender Inequality and Recessions in Online Labor Markets

Belinda Archibong
,
Columbia University
Peter Blair Henry
,
Stanford University

Abstract

Using data from the largest online job portal in Nigeria, we document: (a) gender
differences in salary offers for jobs, and (b) the responses of (a) to recessions. On
average, jobs in sectors that skew heavily female offer lower starting salaries than jobs
in sectors that skew heavily male. During recessions, the number of applications to jobs
that skew female falls, and salary offers rise. In contrast, the number of applications to
jobs that skew male rises, and salary offers fall. In accordance with this relative shift
in the number of applications, there is a decrease in the gap between salary offers to
male-skewed and female-skewed jobs. These stylized facts suggest that recessions may
increase the bargaining power of groups like women who are under-represented in the
labor market, while decreasing the bargaining power of those in the majority.

On Marginal Outcome Tests and Biased Decision Making

Peter Hull
,
Brown University

Abstract

Marginal outcome tests compare the expected effects of a decision across individuals of different groups but at the same indifference point of the decision-maker. I show how such tests can detect biased decision-making, by rejecting the null of (accurate) statistical discrimination under weak conditions. Drivers of such test rejections include canonical taste-based discrimination, biased beliefs, and “systemic” forms of discrimination; I show how these drivers can further be distinguished by extensions of the outcome test. Identification from quasi-experimental variation in decision-making is also discussed.

Systemic Discrimination: Theory and Measurement

Aislinn Bohren
,
University of Pennsylvania
Peter Hull
,
Brown University
Alex Imas
,
University of Chicago

Abstract

Economics often defines and measures discrimination as disparities arising from the direct effect of group identity. We develop new tools to model and measure systemic discrimination, which captures how discriminatory decisions in other domains---past, future, or contemporaneous---contribute to disparities in a given decision. We show that systemic discrimination can be driven by disparate signaling technologies or differential opportunities for skill development. We then propose a new measure based on a decomposition of total discrimination into direct and systemic components, and show how it can be used to estimate systemic discrimination in both experimental and observational data. We illustrate these new tools in three applications, including a novel Iterated Audit experimental paradigm with real hiring managers. The applications also identify behavioral frictions that blunt the impact of individual-level interventions and perpetuate systemic discrimination, suggesting the need for systems-based policy responses to systemic discrimination.

Racial Disparities in the U.S. Mortgage Market

Agustin Hurtado
,
University of Chicago
Jung Sakong
,
Federal Reserve Bank of Chicago

Abstract

We empirically examine the extent and potential drivers of racial disparities in the U.S. mortgage market. Using new data, we present three main findings. First, we document racial disparities in mortgage access between minority and otherwise-identical White borrowers, even within the same bank and loan officer. In contrast, racial disparities in mortgage costs are close to zero. Second, we uncover that the use of purportedly race-blind automated underwriting algorithms is associated with substantially smaller disparities in mortgage access, while individual factors—specifically, loan officers’ race and whether borrowers’ race is observed at application—do not seem to matter much. Third, we show that the use of automated underwriting algorithms is associated with slightly larger cost disparities, while individual factors make little difference. Our approach and findings represent another step toward understanding the factors driving racial disparities and discriminatory forces in the U.S. mortgage market. Structural or organizational factors may also play a role and have been overlooked by previous studies. We study one of these factors next.

We construct the first matched data on bank ownership, employees, and mortgage borrowers to study the effect of racial minority bank ownership on minority credit. We address previous missing data and measurement error issues by introducing numerous novel sources and tools. Using our newly constructed data, we present four findings. First, minority-owned banks specialize in same-race mortgage lending. Almost 70 percent of their mortgages go to borrowers of the same race as their owners. Second, the effect of minority bank ownership on minority credit is large and exceeds that of minority loan officers. We find that minority borrowers applying for mortgages at banks whose owners are of the same minority group are nine percentage points more likely to be approved than otherwise identical minority borrowers at nonminority banks. This effect is over six times that of a minority loan officer. Third, evidence from plausibly exogenous bank failures suggests that the effect of minority bank ownership might reflect an expansion rather than a reallocation of credit to minorities. Fourth, the within-bank default rate of same-race borrowers is much lower than that of otherwise-identical borrowers of other races at minority banks. These findings are consistent with minority bank ownership reducing information asymmetry and inconsistent with owners' preferences driving the observed effects on minority credit. The evidence is also consistent with an organizational phenomenon, suggesting that the effect of banks' organizational culture and design on minority credit might outweigh that of banks' individual employees.

Discussant(s)
Emily Breza
,
Harvard University
Patrick Bayer
,
Duke University
Stephen Ross
,
University of Connecticut
Vikrant Vig
,
Northwestern University
JEL Classifications
  • J7 - Labor Discrimination
  • J1 - Demographic Economics