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Sex Offenders and Residential Location: A Predictive–Analytical Framework

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  • Elizabeth A Mack
  • Tony H Grubesic

Abstract

Despite the growing body of research examining the collateral consequences of legislation governing sex offenders, a complete understanding of their residential choices post release remains elusive. This paper develops a predictive–analytical framework that helps determine which demographic and socioeconomic factors best forecast the residential choices of convicted sex offenders. Specifically, a derived index of social disorganization (ISDOR) is implemented in both statistical and nonlinear data mining approaches to predict the presence of sex offenders in a community. The results of the analysis are encouraging, predicting nearly 75% of registered offender locations correctly. The utility of this framework as a tool for public policy and law enforcement is discussed.

Suggested Citation

  • Elizabeth A Mack & Tony H Grubesic, 2010. "Sex Offenders and Residential Location: A Predictive–Analytical Framework," Environment and Planning A, , vol. 42(8), pages 1925-1942, August.
    • Handle: RePEc:sae:envira:v:42:y:2010:i:8:p:1925-1942
    DOI: 10.1068/a42370
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    References listed on IDEAS

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    1. S Openshaw, 1998. "Neural Network, Genetic, and Fuzzy Logic Models of Spatial Interaction," Environment and Planning A, , vol. 30(10), pages 1857-1872, October.
    2. Lance Lochner & Enrico Moretti, 2004. "The Effect of Education on Crime: Evidence from Prison Inmates, Arrests, and Self-Reports," American Economic Review, American Economic Association, vol. 94(1), pages 155-189, March.
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