Do Cops Know Who to Stop? Assessing Optimizing Models of Police Behavior with a Natural Experiment

Working Paper: NBER ID: w31594

Authors: David Abrams; Hanming Fang; Priyanka Goonetilleke

Abstract: The standard economic model of police stops implies that the contraband hit rate should rise when the number of stops or searches per officer falls, ceteris paribus. We provide empirical corroboration of such optimizing models of police behavior by examining changes in stops and frisks around two extraordinary events of 2020: the COVID-19 pandemic onset and the nationwide protests following the killing of George Floyd. We find that hit rates from pedestrian and vehicle stops generally rose as stops and frisks fell dramatically. Using detailed data, we are able to rule out a number of alternative explanations, including changes in street population, crime, police allocation, and policing intensity. We find mixed evidence about the changes in racial disparities, and evidence that police stops do not decrease crime, at least in the short run. The results are robust to a number of different specifications. Our findings provide quantitative estimates that can contribute to the important goals of improving and reforming policing.

Keywords: policing; stop and frisk; contraband detection; police reform; racial disparities

JEL Codes: J14; K0


Causal Claims Network Graph

Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.


Causal Claims

CauseEffect
decreased police stops (R48)increased hit rates for contraband (K42)
police stops do not decrease crime (K42)no deterrent effect from policing activities (K42)
fewer stops allow officers to focus on the most suspicious individuals (K42)increased hit rates for contraband (K42)
increased hit rates (C41)ambiguous impact on racial bias (J15)

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