Spatial, Temporal, and Explanatory Analyses of Urban Crime

This study assessed the influence of socioeconomic and demographic indicators on different types of crime and explored the spatial and temporal dynamics of crime. Between 2014 and 2020, 174,365 criminal events registered in Quito, Ecuador, were collected and aggregated at an administrative area level. Time-series decompositions, spatial autocorrelations, and regression models were applied, considering different types of crime as dependent variables. A marked seasonal component of crime and crime hotspots in the center of the study area was identified. Crime events are likely to increase significantly by 2025. We also found that unemployment, schooling, unsatisfied basic needs, and especially the density of bars and night clubs are socioeconomic indicators influencing crime. Urban crimes present specific spatial and temporal patterns, and crime events can be explained by urban socioeconomic conditions.