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Discerning the Effects of Rural to Urban Migrants on Burglaries in ZG City with Structural Equation Modeling

Author

Listed:
  • Fangye Du

    (Key Laboratory of Regional Sustainable Development Modelling, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China)

  • Lin Liu

    (Center of Geographic Information Analysis for Public Security, School of Geographic Sciences, Guangzhou University, Guangzhou 510006, China
    Department of Geography, University of Cincinnati, Cincinnati, OH 45221-0131, USA)

  • Chao Jiang

    (Institute of Remote Sensing and Geographic Information Systems, School of Earth and Space Sciences, Peking University, Beijing 100871, China)

  • Dongping Long

    (Center of Geographic Information Analysis for Public Security, School of Geographic Sciences, Guangzhou University, Guangzhou 510006, China)

  • Minxuan Lan

    (Department of Geography, University of Cincinnati, Cincinnati, OH 45221-0131, USA)

Abstract

Both rural to urban migration and urban crime are well researched topics in China. But few studies have attempted to explore the possible relationships between the two. Using calls for service data of ZG city in 2014, the Sixth Census data in 2010, this study examines relationships between migrants and crime by using structural equation models. Two hypotheses were tested: (1) the distribution of migrants has direct effects on the spatial distribution of burglaries, and (2) migrants also indirectly affect burglary rate through mediating variables such as residential mobility and socio-economic disadvantage of their resident communities. The results showed that migrants have significant direct and indirect effects contributing to burglaries, although the indirect effect is much larger than the direct effect, indicating that community characteristics play a more important role than the migrants themselves.

Suggested Citation

  • Fangye Du & Lin Liu & Chao Jiang & Dongping Long & Minxuan Lan, 2019. "Discerning the Effects of Rural to Urban Migrants on Burglaries in ZG City with Structural Equation Modeling," Sustainability, MDPI, vol. 11(3), pages 1-13, January.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:3:p:561-:d:199770
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    References listed on IDEAS

    as
    1. Dongping Long & Lin Liu & Jiaxin Feng & Suhong Zhou & Fengrui Jing, 2018. "Assessing the Influence of Prior on Subsequent Street Robbery Location Choices: A Case Study in ZG City, China," Sustainability, MDPI, vol. 10(6), pages 1-16, May.
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    7. Guangwen Song & Lin Liu & Wim Bernasco & Luzi Xiao & Suhong Zhou & Weiwei Liao, 2018. "Testing Indicators of Risk Populations for Theft from the Person across Space and Time: The Significance of Mobility and Outdoor Activity," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 108(5), pages 1370-1388, September.
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    Cited by:

    1. Minxuan Lan & Lin Liu & Andres Hernandez & Weiyi Liu & Hanlin Zhou & Zengli Wang, 2019. "The Spillover Effect of Geotagged Tweets as a Measure of Ambient Population for Theft Crime," Sustainability, MDPI, vol. 11(23), pages 1-17, November.

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