Heterogeneous Causal Effects of Neighborhood Policing in New York City with Staggered Adoption of the Policy

• Activity Number: 503 - Causal Inference for Spatiotemporal Data
• Type: Invited
• Date/Time: Thursday, August 11, 2022 : 8:30 AM to 10:20 AM
• Sponsor: Section on Statistics and the Environment
• Author(s): Joseph Antonelli*
• Companies: University of Florida
• Keywords: Causal inference; High-dimensional statistics; Bayesian inference

Abstract

In New York City, neighborhood policing was adopted at the police precinct level over the years 2015-2018, and it is of interest to both (1) evaluate the impact of the policy, and (2) understand what types of communities are most impacted by the policy, raising questions of heterogeneous treatment effects. We develop novel statistical approaches that are robust to unmeasured confounding bias to study the causal effect of policies implemented at the community level. We find that neighborhood policing decreases discretionary arrests in certain areas of the city, but has little effect on crime or racial disparities in arrest rates.