Crime rates and contextual characteristics: a case study in Connecticut, USA

Abstract

There is a long-standing interest in the spatial relationship between contextual characteristics and crime rates in the U.S. since such a relationship allows police and stakeholders to design crime prevention programs to better target areas at risk for crime. The objective of this research is to examine the relationships between violent/property crime rates and contextual characteristics at the county-subdivision level in the State of Connecticut. The analysis shows that predictors such as population density, type of housing, education, poverty, and racial/ethnic diversity are significantly associated with violent and property crime rates. The results are discussed in the context of different crime hypotheses, which can explain spatial variations in crime rates. Most importantly, the association between crime rates and the explanatory variables in this study significantly varied over space, highlighting that different crime prevention policies/programs should be implemented in different county subdivisions in Connecticut.

Keywords

• connecticut
• contextual characteristics
• crime rates
• geographically weighted regression