Our team develops cutting-edge statistical techniques to measure racial bias in policing, evaluate policing policy reforms, and improve the performance of policing organizations.
Diversification is a widely proposed policing reform, but its impact is difficult to assess. We used records of millions of daily patrol assignments, determined through fixed rules and preassigned rotations that mitigate self-selection, to compare the average behavior of officers of different demographic profiles working in comparable conditions. Relative to white officers, Black and Hispanic officers make far fewer stops and arrests, and they use force less often, especially against Black civilians. These effects are largest in majority-Black areas of Chicago and stem from reduced focus on enforcing low-level offenses, with greatest impact on Black civilians. Female officers also use less force than males, a result that holds within all racial groups. These results suggest that diversity reforms can improve police treatment of minority communities.
We show that if police racially discriminate when choosing whom to investigate, analyses using administrative records to estimate racial discrimination in police behavior are statistically biased, and many quantities of interest are unidentified – even among investigated individuals – absent strong and untestable assumptions. Using principal stratification in a causal mediation framework, we derive the exact form of the statistical bias that results from traditional estimation. We develop a bias-correction procedure and nonparametric sharp bounds for race effects, replicate published findings, and show the traditional estimator can severely underestimate levels of racially based policing or mask discrimination entirely. We conclude by outlining a general and feasible design for future studies that is robust to this inferential snare.
Using a rare geocoded census of SWAT team deployments from Maryland, we show that militarized police units are more often deployed in communities with large shares of African American residents, even after controlling for local crime rates. Using nationwide panel data on local police militarization, we demonstrate that militarized policing fails to enhance officer safety or reduce local crime. Finally, using survey experiments – one of which includes a large oversample of African American respondents – we show that seeing militarized police in news reports may diminish police reputation in the mass public.
RoPRA gratefully acknowledges financial support from Analytics at Wharton.