Empirical research suggests that traffic enforcement is the most common type of proactive activity police officers engage in on a daily basis. Further, agencies often use traffic enforcement to achieve both traffic safety and crime control. Given these goals, the purpose of this paper is to investigate whether (and to what extent) officers are accurately targeting their proactive traffic enforcement with crime and vehicle crashes in two agencies.
The study examines traffic enforcement patterns in two agencies to see whether proactive traffic enforcement aligns spatially with crime and vehicle crashes. This study employs negative binomial regression models with clustered standard errors to investigate this alignment at the micro-spatial level. Key variables of interest are measured with police calls for service data, traffic citation data and vehicle crash data from two law enforcement jurisdictions.
High levels of spatial association are observed between traffic accidents and crime in both agencies, lending empirical support to the underlying theories of traffic enforcement programs that also try to reduce crime (i.e. “DDACTS”). In both agencies, traffic accidents also appear to be the most prominent predictor of police proactive traffic enforcement activities, even across different times of day. However, when vehicle crashes are accounted for, the association between crime and traffic stops is weaker, even during times of day when agencies believe they are using proactive traffic enforcement as a crime deterrent.
No prior study to authors knowledge has examined the empirical association between police proactive traffic activities and crime and traffic accidents in practice. The current study seeks to fill that void by investigating the realities of traffic stops as practiced daily by police officers, and their alignment with crime and vehicle crashes. Such empirical inquiry is especially important given the prevalent use of traffic enforcement as a common proactive policing tool by police agencies to control both traffic and crime problems.
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