Link to most recent draft

Abstract: Around one million U.S. residents experience threats or use of force during encounters with police each year. Understanding the determinants of officer decision-making during patrol is key to policies that regulate police-civilian contact. This paper examines how interactions between officers influence pair-level outcomes in terms of stops, arrests, and use of force. I estimate a team production model with latent, discrete officer types, allowing patrol outcomes to depend flexibly on officer pairings. Leveraging detailed administrative data on officer assignments and outcomes from the Chicago Police Department between 2008 and 2018, I find evidence of interaction effects, particularly in arrests and use of force. Officers who are high arrest or high use of force on solo patrol tend to dominate team outcomes, except when high–use-of-force officers are paired with low–use-of-force officers. Interaction effects capture 11.1% of the model-explained variance in use of force, relative to officer heterogeneity and sorting. Counterfactual reallocation of officer pairings suggest that, depending on the assignment rule, average use of force could decrease by as much as 14.4% or increase by up to 13.7%. Together, these findings underscore the substantial role of officer interactions in shaping patrol outcomes.

Presented at the 2025 Midwest Economics Association Annual Meeting, 2025 IRP Summer Research Workshop, 2025 SOLE-EALE-AASLE World Labor Conference, 2025 Urban Economics Association North American Meeting (scheduled), 2025 Southern Economic Association Annual Meeting (scheduled), 2025 APPAM Fall Research Conference (scheduled).

Link to most recent draft

Abstract: The expansion of police presence in U.S. schools over the past two decades raises ques- tions about the trade-off between student safety and exposure to the criminal justice system. In this paper, we study how school context moderates the effect that School Resource Officers (SROs) have on in-school offenses and school discipline. Using a difference-in-differences design that leverages a federal SRO hiring grant, we estimate bounds on the variance of the treatment effect distribution to detect treatment effect heterogeneity in SRO hiring and dis- cover meaningful differences in how hiring SROs impacts the number of students suspended or referred to law enforcement. To explain the detected treatment effect heterogeneity, we consider observable school characteristics such as student demographics and school staff and unobservable differences in how schools implement their SRO program, measured by training text models to extract themes from grant narratives that describe the problems facing the school. We find that schools whose SRO programs focus on building community have de- creased suspensions and referrals or arrests than schools that focus on the SRO’s fulfillment of traditional law enforcement duties. Our results highlight how a school’s context shapes the impact that SROs have in schools.

Presented at the 2024 APPAM Fall Research Conference, 2025 APPAM Fall Research Conference (scheduled to be presented by Hanna Han).

Abstract: Cities across the United States have adopted nuisance ordinances that hold property owners accountable when multiple 911 calls are made to their properties for nuisance activities (e.g., noise, littering, battery). Enacting these ordinances increases eviction filing rates and may have disparate impacts on people of color and people with disabilities; however, little is known about where affected households move or how frequently they relocate. Using restricted census data on address histories and household characteristics, we employ a staggered difference-in-differences design to examine the impact of nuisance ordinance enactment on residential mobility and neighborhood opportunity in large U.S. cities between 2000 and 2020. This approach allows us to trace the evolution of treatment effects over time and identify heterogeneous effects by household demographic characteristics. We also develop measures of address-level treatment using novel data on 911 calls, which enables us to precisely identify households likely affected by nuisance ordinances and evaluate their subsequent residential mobility.

SSM - Mental Health (2024)  [pdf]

Abstract: Household debt has dramatically increased in the United States in the past four decades, notwithstanding a temporary reprieve during the Covid-19 Pandemic. While debt has expanded across social groups, low-income individuals are most negatively impacted, taking on high-cost debt that they struggle to repay, often simply to meet basic needs. This article explores indebtedness among low- and moderate-income US households, and its association with physical and mental health. While most existing studies explore health effects of specific debt types, or monetary value of total debt, our research proposes a categorization of debt into three types (potential wealth-building, problem short-term, and non-loan debt) that is more meaningful in health research and addresses the experience of managing multiple and intersecting debts, common among low-income households. Using mixed methods, we show how these debts are experienced by debtors, resulting in them feeling overwhelmed, anxious, and stressed, ultimately taking a toll on both their physical and mental health.