Research in Progress
Racial Bias in Police Stopping Decisions (with Jeffrey Fagan)
This paper explores whether racial disparities in pedestrian stops reflect true racial differences in criminal behavior or result from unfair targeting by patrol officers. We exploit a court-ordered reform that sharply reduced stop rates across New York City to estimate outcomes of marginal stops – stops that would have occurred absent the reform. As a test for racial bias, we compare estimates of marginal stop outcomes across races. Our analysis is motivated by a model of officer stopping decisions where statistically rational officers face diminishing marginal returns to stops and seek to maximize the detection of criminal behavior less race-specific costs to conducting stops. Using a LATE framework, we instrument for neighborhood stop rates with the timing of the reform, circumventing common pitfalls of outcomes tests, such as omitted variables bias and infra-marginality bias. Pairwise comparisons of marginal stop outcomes in the first year of the reform find that Black and Hispanic pedestrians were over-stopped; marginal Black (Hispanic) stops detect criminal behavior 24% (34%) less frequently than marginal white stops. Shifting stops from minority pedestrians to white pedestrians would have improved efficiency. Estimating marginal stop outcomes over the three years after the reform, we trace out a marginal return curve for each racial group. To equate marginal returns across races, we estimate that the police had to reduce stops of Black and Hispanic pedestrians by an additional 298,000 stops per year. Since our approach allows officers to statistically discriminate or “rationally” racial profile, we interpret these results as conservative estimates of racial discrimination.
Supporting Pathways out of Poverty: Randomized Evaluation of Mobility Mentoring (with Larry Katz and Liz Engle)
Current public support services tend to address a particular symptom of poverty rather than central causes. This paper explores whether holistic, individualized mentoring combined with monetary incentives can help low-income public housing residents achieve economic self-sufficiency. The intervention called Mobility Mentoring includes an individualized coaching plan, weekly meetings to set and assess goals, and temporary financial assistance to incentivize goals or help participants overcome financial obstacles. We evaluate the intervention through a randomized experiment. With the assistance of the Boston Housing Authority (BHA), we recruited public housing and voucher recipients who are able to work and randomly assign half to treatment. Treatment group participants can receive three years of Mobility Mentoring Services, while the control group receives the services usually available to them in the community. Drawing on administrative tax data, our primary outcomes explore the impact of the program on employment, earnings, and household income. We will also examine impacts on financial health, housing stability, public benefit receipt, and survey measures of health and well-being. We plan to follow study participants for ten years from random assignment in administrative data sources, allowing us to assess whether the intervention generates economic self-sufficiency in the long-run.
Academics and Athletics: A Randomized Trial of Multi-Faceted Mentorship (with Noam Angrist)
This study evaluates a novel mentorship program combining athletics and academics to close achievement gaps among urban public high school students in the U.S., a setting where racial achievement gaps have persisted for over 20 years. We estimate the causal effect on GPAs – a consequential outcome capturing both academic and non-academic performance in school – by leveraging randomized lotteries run to determine program admission. Results from a pilot show large effects on standardized GPAs of 0.50 standard deviation (p-value= 0.016). This translates to students moving from a “C+” to “B” average. The majority of students are Black and Hispanic, and a single semester of attending the program closes 45-70% of the racial achievement gap. The program ranks among the most cost-effective education interventions in the literature, since it reduces cost by leveraging college volunteer mentors and boosts impact by coupling both cognitive and non-cognitive skill acquisition. We plan to collect additional administrative records to expand this analysis to a larger sample and broader array of outcomes, including high school attendance and disciplinary actions, on-time grade progression and graduation, and college going and completion.
Mentoring Across Lines of Difference: Evidence from A Comprehensive Mentorship Program for Students At Risk of Dropping Out of High School (with Bill Evans and Sarah Kroeger)
The Effect of Low-level Arrests on the Early-life Trajectory of Urban Men: Evidence from Tax and Arrest Records (with Benny Goldman)
We study the downstream effects of a teenage arrest or citation for a minor offense on adult earnings, employment, and incarceration. Prior research on the effects of criminal justice interactions on economic outcomes tends to use judge IV designs which focus on the effects of judge decisions (e.g. bail, incarceration, etc.) on defendants who, in many cases, are already tied up in the criminal justice (CJ) system. In this paper, we focus on teenagers who are plausibly interacting with the CJ system for the first time and ask whether interactions with the police for low-level offenses can trap people in the CJ system with detrimental impacts on long-run outcomes. We use the drawdown of stop and frisk policies in New York, which prior research has shown leads to no change in crime but to a large reduction in the number of citations and arrests for low-level offenses, to study the effects on long-run outcomes for exposed teenagers. Using administrative tax records linked to arrest and policing data, we will estimate impacts on earnings, incarceration, and unemployment in an exposed teenager’s mid-20s. We will complement these findings with an analysis of the dynamic effects of police surges, which simultaneously increased low-level arrests and citations but deterred future serious crime. Using maps of police surges linked to residential addresses, we will match teenagers on opposite sides of the police surge borders to identify causal effects for cohorts that directly experience the police crackdown and those that also experience crime reductions. We will examine heterogeneous impacts by race, sex, and predicted criminality, and will quantify the extent to which low-level interactions with the police mediate neighborhood rates of upward mobility by race and sex.