Research

This paper provides the first national analysis of how public scrutiny from high-profile police killings affect local policing and crime. These killings reduce arrests for low-level offenses without affecting arrests for serious crimes. They also result in a significant increase in serious offenses, particularly murders and robberies. The effects appear after communities become aware of the incident and are larger when media coverage is higher. The findings suggest that scrutiny drives the reductions in arrests, while the incidents themselves—not reduced police activity—prompt the increases in crime. To mitigate crime, localities should focus on reducing police use of force.

Racial disparities within the criminal justice system continue to be a pressing issue, especially after the recent passage of California’s Racial Justice Act, which allows for a broader set of legal challenges based on racially disparate treatment. In this article, we analyze data for almost four million stops by California’s fifteen largest law enforcement agencies in 2019, examining the extent to which people of color experience searches, enforcement, intrusiveness, and use of force differently from white people. Black Californians are more likely to be searched than white Californians, but searches of Black civilians reveal less contraband and evidence. Black people are overrepresented in stops not leading to enforcement as well as in stops leading to an arrest. While differences in location and context for the stop significantly contribute to racial disparities, notable inequities remain after accounting for such factors. These disparities are concentrated in traffic stops. A notable proportion of which lead to no enforcement or discovery—suggesting that gains in efficiency and equity are possible. Through a “veil of darkness” analysis, we find evidence that racial bias may be a contributing factor to disparities in traffic stops for Black and Latino drivers. These findings suggest that traffic stops for non-moving violations deserve consideration for alternative enforcement strategies.

This chapter discusses the essential role that the police have in deterring and reducing crimes, particularly the most violent and costly ones to society, such as murder. We begin by providing a brief overview of deterrence theory before discussing 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 (2017b) 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 efficacy and fairness of cash bail in promoting public safety has been a prominent policy question in recent years, but it is difficult to rigorously estimate the effects of bail, particularly at the state level, because of a lack of exogenous variation. California responded to the COVID pandemic by setting bail at zero dollars for many misdemeanors and felonies, increasing the number of people who were immediately released after being arrested. Until July 2022, most Californians lived in a county with an emergency bail order in place. We separately estimate the impact of the implementation and revocation of these zero-bail orders on rearrests using a triple difference framework that relies on the staggered timing across counties and uses offenses that did not qualify for zero bail as a control group. The implementation of emergency bail orders significantly increased the likelihood and number of rearrests within 30 days of the initial arrest. The increase in rearrests was driven by felony offenses, but we find no evidence of an increase for violent felonies, a concern raised by some observers. For the counties that had an emergency bail order for at least a year, there was a statistically significant increase on rearrests initially, but the effect diminished over time. The average effect over the first year of implementation in these counties was not statistically significant. Notably, the rise in felony rearrests did not subside for these counties that extended an emergency order past 2020. Though the initiation of emergency bail orders led to increases in rearrests, lifting these orders had no significant effect on rearrests, regardless of offense type.

This study 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 non-emergency 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.