UC Berkeley

This dissertation explores policy-relevant issues in the economics of crime and health economics. In the first study, I explore the impact of public scrutiny generated by high-profile, officer-involved fatalities on police officer effort. The second chapter provides a synthesis of the evidence on whether police reduce crime, a timely review during a national discussion on policing—prompted by the "Defund the Police" movement. Finally, the last chapter explores the impacts of rural hospital closings on rural patient welfare, an increasing likely phenomenon as the COVID-19 virus has rendered numerous healthcare facilities insolvent.

The first chapter explores whether public scrutiny of police officers reduces their level of effort—empirically testing the Ferguson Effect. Leveraging the quasi-random timing of high-profile, officer-involved fatalities (OFs), this paper provides the first national analysis of this question with department-level data on arrests and crime. To address the simultaneous effects that could occur after an OF—(1) greater scrutiny of police, (2) reduced community cooperation with identifying and locating suspects, (3) reduced civilian crime reporting, and (4) changes in offending behavior—I develop a theoretical model of policing behavior to provide empirical predictions of the changes in arrests due to each of the four possible channels. Following a high-profile OF, theft arrests drop by 4-13%, while arrests for the least serious offenses (e.g., marijuana possession and disorderly conduct) see sharp declines of up to 33%. Notably, arrest rates do not change for violent crime or more serious property crimes. These findings are consistent with scrutiny as the causal channel for the reduction in arrests. While the decline in arrests for theft is temporary, it persists for the least serious offenses, representing a sustained transition to a lower equilibrium effort. Reductions in arrests occur for both black and white suspects, but reductions for black suspects are suggestively larger in cases of theft and marijuana possession.

The second chapter, co-authored with Justin McCrary, discusses the role that the police have in deterring and reducing crimes. After a brief overview of deterrence theory, we discuss the empirical evidence on the efficacy of police staffing and various policing strategies on crime reduction. Using a framework developed in Weisburd and Eck (2004), we quickly evaluate the model of standard policing and then mainly focus on evidence behind three current policing practices: hot spots, problem-oriented, and proactive. Finally, we use the empirical evidence of police staffing to provide a basis for a theoretical model on the optimal level of policing. Using the Chalfin and McCrary (2018) framework, we discuss how one could estimate how much crime could be reduced if additional funds were directed to hire more law enforcement officers, and if crime-reduction were the sole policing objective, how many cities are in fact underpoliced. We conclude by postulating whether we could implement additional policing without resulting in unwarranted and excessive social costs for the community as discussed by Manski and Nagin (2017).

The third chapter, co-authored with Dave Jones and Peter Orazem, estimates a model of rural patient hospital choice between the nearest rural hospital, the nearest urban hospital, or the nearest research hospital. We present separate estimates for inpatient and outpatient visits, for different diagnoses, and for emergency and nonemergency admissions. The analyses illustrate the tradeoffs between hospital quality and distance in deciding whether to choose the nearest hospital or to travel farther for an alternative. The model parameters are used to simulate two hospital closing scenarios for both outpatient and inpatient data: 1) closing 25% of lowest quality rural hospitals and 2) closing 15% of the least used rural hospitals. Closing 25% of the lowest quality rural hospitals results in a 20.7% increase in expected distance and a 7.7% increase in expected hospital quality for those with inpatient ailments. Closing the least used hospitals modestly increases average distance but lowers average quality. We conclude that closing the lowest quality rural hospitals is a better policy prescription than closing the least used hospitals since closing low quality hospitals results in a substantial increase in average quality of hospital with only a slight increase in distance traveled for chosen hospitals.