Introducing Spatial Configuration in Crime Count Models

The main techniques used for quantitative analyses of urban crime can generally be divided into three categories: descriptive studies of crime dispersion over a specific urban area without any substantial statistical modeling, traditional statistical spatial models whose normality assumptions do not hold and count models which do not take into account the spatial configuration of the urban layouts. In this work we discuss how configurational components can be introduced in the count data modeling of crime illustrating our point with a case study centered on a highly populated area of the City of Genoa on three crime typologies. The statistical modeling of crime at street level is performed using count models which include the usual economic and sociodemographic variables, complemented with a set of configurational variables, built using the techniques of Space Syntax Analysis, in order to include, among the regressors, the graph complexity of the urban structure. The configurational variables included in this model are statistically significant, consistently with the criminological theories stating that the urban layout has a role in crime dispersion over a city and their use among the set of regressors, substantially improves the overall goodness of fit of the models. The configurational variables herein introduced add an implicit spatial correlation structure of crime to the models and give new and useful information to Municipalities to interpret how crime patterns relate to the urban layout and how to intervene through the means of urban planning to reduce or prevent crime.