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Relationship Between Crime and Socioeconomic Factors in Urban Areas: Methodological Problems and a Solution by GIS

NCJ Number
190157
Journal
Reports of the National Research Institute of Police Science Volume: 39 Issue: 2 Dated: March 1999 Pages: 20-34
Author(s)
Takahito Shimada; Yutaka Harada
Date Published
March 1999
Length
15 pages
Annotation
This study examined relationships between crime and socioeconomic factors in the urban areas of Japan, based on aggregate statistics that used municipalities as building units.
Abstract
The study first reviewed previous studies conducted in the 1960's when Japan experienced significant economic growth and population migrations into urban areas. These studies found positive correlations between the crime rate and population density. This review identified two methodological problems in these studies. First, the effects of adjacent aggregation units were not considered in correlation analysis. Second, differences in daytime and nighttime populations were not considered. The current study sought to correct these methodological flaws by complementing conventional correlation analysis with geographic information systems (GIS), which enabled the confirmation of spatial patterns of offending and socioeconomic factors. The data consisted of 224,363 official records of crime that occurred in the 50 jurisdictions in Tokyo in 1996. The relations between crime and socioeconomic factors were examined by both conventional correlation analysis and visualization in GIS. Findings showed that the visualized spatial patterns of offending differed, whether they were expressed as raw count or rate. Regarding almost all crime subclasses, crime counts correlated with both daytime and nighttime populations. From 18 socioeconomic variables, factor analysis identified three factors: population, mobility, and economy. Aggregation by city units and district units found that a prefecture contained some cities in which offenses were concentrated and that each city contained some districts in which offenses were concentrated. This was confirmed through visualization by GIS. 12 figures and 8 tables