Journal article
Sex Offender Residential Movement Patterns: A Markov Chain Analysis
The Professional geographer, v 66(1)
02 Jan 2014
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
This article introduces a new approach to the analysis of changes in sex offender residences over time. Using a Markov chain framework, we analyze residential movement patterns of registered sex offenders in Hamilton County, Ohio, over a three-year period (2005-2007). Results indicate a 46 percent reduction in offenders violating spatial restriction zone policy as compared to a counterfactual case where offenders move as a function of housing distributions. Strong legacy effects are also found as offenders previously in violation of restriction policies move into other restricted zones at a higher rate than offenders who were previously in compliance with the policy. Parcels that previously were home to registered offenders also continue to attract offenders in future periods. Although we find differences in the probabilities of attracting offenders for parcels outside and inside restricted zones that are consistent with offender restrictive policies, these differences are actually significantly smaller than what holds under the counterfactual. Parcels in restricted zones continue to attract offenders at a higher rate than expected, despite the policy restrictions.
Metrics
Details
- Title
- Sex Offender Residential Movement Patterns: A Markov Chain Analysis
- Creators
- Sergio J. Rey - Arizona State UniversityAlan T. Murray - Arizona State UniversityTony H. Grubesic - Drexel UniversityElizabeth Mack - Arizona State UniversityRan Wei - Arizona State UniversityLuc Anselin - Arizona State UniversityMarie Griffin - Arizona State University
- Publication Details
- The Professional geographer, v 66(1)
- Publisher
- Taylor & Francis
- Number of pages
- 10
- Resource Type
- Journal article
- Language
- English
- Web of Science ID
- WOS:000329154700012
- Scopus ID
- 2-s2.0-84891558005
- Other Identifier
- 991019357628004721
UN Sustainable Development Goals (SDGs)
This publication has contributed to the advancement of the following goals:
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Geography