Should the study find such a link exists, it would imply that shifting ecologies of crime apparent after a year are driven in part by dynamics emerging from structural differentials. To the best of the authors' knowledge, this question has not yet been addressed. For all crime types investigated, except rape and homicide, crime plus demographics resulted in the best combination of prediction/simplicity based on the Bayesian Information Criterion. Socioeconomic status (SES) and racial composition linked as expected theoretically to crime changes. Intercommunity structural differences in power relationships, as reflected in SES and racial composition, link to later crime shifts at the same time that ongoing crime continuities link current and future crime levels. The main practical implication is that crime analysts tasked with long-term, one-year-look-ahead forecasting may benefit by considering demographic structure as well as current crime. For Philadelphia (PA) census block groups, 2005 to 2009 data from the American Community Survey and 2009 crime counts were used to predict spatially smoothed 2010 crime counts in three different models: crime only, demographics only, and crime plus demographics. Models were tested for major personal (murder, rape-aggravated assault, and robbery) and property (burglary and motor vehicle theft) crimes. (Publisher abstract modified)
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