Built Environment and Property Crime in Seattle, 1998–2000: A Bayesian Analysis
Stephen A Matthews,
Tse-Chuan Yang,
Karen L Hayslett and
R Barry Ruback
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Stephen A Matthews: Department of Sociology, Pennsylvania State University, University Park, PA 16802, USA
Tse-Chuan Yang: Social Science Research Institute, Pennsylvania State University, University Park, PA 16802, USA
Karen L Hayslett: School of Economic, Political and Policy Sciences, University of Texas at Dallas, Richardson, TX 75080, USA
R Barry Ruback: Crime, Law and Justice Program, Department of Sociology, Pennsylvania State University, University Park, PA 16802, USA
Environment and Planning A, 2010, vol. 42, issue 6, 1403-1420
Abstract:
The past decade has seen a rapid growth in the use of a spatial perspective in studies of crime. In part this growth has been driven by the availability of georeferenced data, and the tools to analyze and visualize them: geographic information systems, spatial analysis, and spatial statistics. In this paper we use exploratory spatial data analysis (ESDA) tools and Bayesian models to help better understand the spatial patterning and predictors of property crime in Seattle, Washington for 1998–2000, including a focus on built environment variables. We present results for aggregate property crime data as well as models for specific property crime types: residential burglary, nonresidential burglary, theft, auto theft, and arson. ESDA confirms the presence of spatial clustering of property crime and we seek to explain these patterns using spatial Poisson models implemented in WinBUGS. Our results indicate that built environment variables were significant predictors of property crime, especially the presence of a highway on auto theft and burglary.
Date: 2010
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Persistent link: https://EconPapers.repec.org/RePEc:sae:envira:v:42:y:2010:i:6:p:1403-1420
DOI: 10.1068/a42393
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