Research

Job Market Paper

Does Distance from Home Matter in Prison? Effects on Visitation and Recidivism

This paper studies how the distance between prison and an incarcerated individual’s home affects their likelihood of recidivism. Leveraging a unique dataset covering more than 20,000 incarcerated individuals and over 200,000 prison visits, I exploit quasi-random variation in home-to-prison distance generated by facility assignment rules. I find that a 100-mile increase in placement distance raises prison readmission within 3 years by almost 4 percent. This effect is driven by a reduction in visitation, with individuals placed farther from home receiving significantly less visits. While social support is theorized to reduce recidivism, there is limited causal evidence on how maintaining these connections through visitation during incarceration affects recidivism. To address this, I use distance as an instrument for visitation, and find that an additional visit per month lowers the likelihood of re-incarceration by roughly 14 percent within one year post-release and 7 percent within three years post-release. I also show that an additional visit per month shortens the fraction of sentence served by one percent and reduces housing instability by 12 percent, the former consistent with a reduction in misconduct and the latter an important mechanism for successful post-release outcomes. Counterfactual estimates suggest assigning individuals closer to home could reduce recidivism by 2 to 4 percent.

Current Projects

An Evaluation of Crisis-Intervention Team Training

Police officers in the United States are often the first responders to mental health crises, despite growing concerns about whether traditional policing is well-suited to these encounters. One response has been crisis-intervention team (CIT) training for police. Unlike alternatives such as unarmed responders or co-responder models, CIT seeks to improve outcomes by training officers to de-escalate mental health crises themselves. This paper provides causal evidence on whether CIT training reduces police use of force and arrests during mental health incidents. I construct a comprehensive administrative dataset linking calls for service, police reports, use-of-force records, officer demographics, and detailed training records from the New Orleans Police Department from 2017 through 2023. To estimate the causal effect of CIT training, I use a difference-in-differences framework that exploits variation in the timing of training across officers. Specifically, I compare changes in propensity to use force and make an arrest for officers before and after they receive training to those of officers who are not-yet-trained but will be trained in the future. I find no evidence that CIT training reduces officers’ use of force or likelihood of making an arrest in mental health incidents. I also find no spillover effects on officer behavior in other types of calls. Importantly, officers who select into training are officers who are already less likely to use force even prior to training, indicating strong positive selection. Taken together, these results suggest that voluntary training programs, as currently implemented, may not meaningfully change officer behavior and instead primarily attract officers who are already less prone to use force.

Prison Diversion for Parents (Arnold Ventures Research Grant, PI)

This project studies Washington State’s Parental Sentencing Alternative, which allows eligible parents to be diverted from prison to community supervision. Using newly collected administrative and court data, I estimate the causal effect of diversion on future criminal behavior through a judge leniency design. I will also examine affects on the children’s long-term outcomes.

Pre-PhD Publications

The Distributional Financial Accounts of the United States with Michael Batty, Jesse Bricker, Joseph Briggs, Sarah Friedman, Eric Nielsen, Kamila Sommer and Alice Henriques Volz (Chapter in NBER Books Series Studies in Income and Wealth 2020)

This paper describes the construction of the Distributional Financial Accounts (DFA), a dataset containing quarterly estimates of the distribution of US household wealth since 1989. The DFA builds on two existing Federal Reserve Board statistical products—quarterly aggregate measures of household wealth from the Financial Accounts of the United States, and triennial wealth distribution measures from the Survey of Consumer Finances—to incorporate distributional information into a national accounting framework. The DFA complements other sources by generating distributional statistics that are consistent with macro aggregates by providing quarterly data on a timely basis, and by constructing wealth distributions across demographic characteristics. We encourage policymakers, researchers, and other interested parties to use the DFA to better understand issues related to the distribution of US household wealth.

The Stability of Safe Asset Production with Sara Almasani, Michael Batty, and Wayne Passmore (FEDS Note 2020)