Estimating Police Anti-Black Bias in Use of Force Decisions

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statistics
causal inference
policing
racial bias
force
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Abstract

Police anti-Black discrimination in use of force decisions is a growing, prevalent problem in American cities. This project explores the dual problem of mediation and selection when estimating bias using police administrative datasets. Using data from the Chicago Police Department, I calculate the racial risk ratio of experiencing police force for Black people compared to non-Black people. This study employs a new technique for correcting bias arising from administrative records, in particular, estimating the racial encounter odds through a weighted composite of police shift deployments and the Black residential rate of police beats, finding that police are significantly more likely to use force against Black people. Furthermore, police district-specific analyses show police are more violent towards Black people in districts with a greater white population.

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Dylan Small
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2023-01-01
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Supplementary and replication materials available at: osf.io/n4xmg/files/osfstorage
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