Intra-Metropolitan Crime Patterning and Prediction, Final Report

• NCJ Number: 249739
• Author(s): Ralph B. Taylor; Elizabeth R. Groff; David Elesh; Lallen Johnson
• Date Published: July 2014
• Length: 419 pages
• Grant Number(s): 2009-IJ-CX-0026
• Agencies: NIJ-Sponsored
• Publication Type: Research (Applied/Empirical); Report (Study/Research); Report (Grant Sponsored)
• Award: Forecasting Municipality Crime Counts within a Metropolitan Area

Annotation

This study examined the patterning and predictability of jurisdictional-level reported crime in the Philadelphia-Camden primary metropolitan statistical area.

Abstract

The crime patterns in this statistical area were examined from three complementary perspectives: the ecology of crime, the geography of crime, and the political economy of crime. Based on these analyses of crime, researchers examined the extent to which crime shifts are predictable for the next 1 year or 3 years. The study drew four conclusions about crime differences among jurisdictions within the statistical area. First, the crime dynamics in one jurisdiction were linked to crime levels in nearby jurisdictions. Second, for every year examined, distinctive crime levels were found by geographic sub-regions. Third, the geographic patterning of crime differences, at least for violent crimes, roughly matched what researchers expected, given geographically distinctive structural inequalities. An unexpected related finding was that sub-regions with the lowest levels of violent crime were in the Pennsylvania side of the metro area. A fourth finding was that community crime rates affected community structure. Regarding community structure, the study found that socioeconomic status, residential stability, and racial composition linked with crime levels or crime changes in the ways anticipated by the systemic model of crime forecasting. Crime levels reflected current inequalities in community structure, which were linked to disparities in community quality of life and government services. Policy-related implications drawn are relevant to State and local governments as well as police. 4 figures