Can Hot Spots Policing Reduce Crime In Urban Areas? An Agent-Based Simulation

Over the past two decades, there has been a growing consensus among researchers that hot spots policing is an effective strategy to prevent crime. Although strong evidence exists that hot spots policing will reduce crime at hot spots without immediate spatial displacement, we know little about its possible jurisdictional or large-area impacts. We cannot isolate such effects in previous experiments because they (appropriately) compare treatment and control hot spots within large urban communities, thus confounding estimates of area-wide impacts. In this chapter an agent-based model is used to estimate area-wide impacts of hot spots policing on street robbery. We test two implementations of hot spots policing (representing different levels of resource allocation) in a simulated borough of a city, and we compare them with two control conditions, one model with constant random patrol and another with no police officers. Our models estimate the short- and long-term impacts on large-area robbery levels of these different schemes of policing resources. These experiments reveal statistically significant effects for hot spots policing beyond both a random patrol model and a landscape without police. These simulations suggest that wider application of hot spots policing can have significant impacts on overall levels of crime in urban areas.