Abstract: Economics tends to define and measure discrimination as disparities stemming from the direct (causal) effects of protected group membership. But work in other fields notes that such measures are incomplete, as they can miss important systemic (i.e. indirect) channels. For example, racial disparities in criminal records due to discrimination in policing can lead to di parate outcomes for equally-qualified job applicants despite a race-neutral hiring rule. We develop new tools for modeling and measuring both direct and systemic forms of discrimination. We define systemic discrimination as emerging from group-based differences in non-group characteristics, conditional on a measure of individual qualification. We formalize sources of systemic discrimination as disparities in signaling technologies and opportunities for skill development. Notably, standard tools for measuring direct discrimination, such as audit or correspondence studies, cannot detect systemic discrimination. We propose a measure of systemic discrimination based on a novel decomposition of total discrimination—disparities that condition on underlying qualification—into direct and systemic components. This decomposition highlights the type of data needed to measure systemic discrimination and guides identification strategies in both observational and (quasi-)experimental data. We illustrate these tools in two hiring experiments. Our findings highlight how discrimination in one domain, due to either accurate beliefs or bias, can drive persistent disparities through systemic channels even when direct discrimination is eliminated. 

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Bio: Peter Hull is the Groos Family Assistant Professor of Economics at Brown University. Previously, he was an Assistant Professor of Economics at the University of Chicago, a Research Fellow at the Becker Friedman Institute for Economics, a Post-Doctoral Researcher at Microsoft Research New England, and an Assistant Economist at the Federal Reserve Bank of New York. Hull studies a wide range of topics in discrimination, healthcare, education, and applied econometrics. Most recently he has worked on developing and applying new quasi-experimental tools to measure and potentially reduce disparate impact and systemic discrimination in high-stakes decisions, such as pretrial release and online lending. His research has appeared in the American Economic Review, Quarterly Journal of Economics, Review of Economic Studies, Review of Economics and Statistics, and New England Journal of Medicine. Hull received a PhD in Economics from MIT in 2017 and a BA in Mathematics-Economics from Wesleyan University in 2010.

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