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Neighborhood social capital and crime victimization: Comparison of spatial regression analysis and hierarchical regression analysis

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  • Takagi, Daisuke
  • Ikeda, Ken’ichi
  • Kawachi, Ichiro

Abstract

Crime is an important determinant of public health outcomes, including quality of life, mental well-being, and health behavior. A body of research has documented the association between community social capital and crime victimization. The association between social capital and crime victimization has been examined at multiple levels of spatial aggregation, ranging from entire countries, to states, metropolitan areas, counties, and neighborhoods. In multilevel analysis, the spatial boundaries at level 2 are most often drawn from administrative boundaries (e.g. Census tracts in the U.S.). One problem with adopting administrative definitions of neighborhoods is that it ignores spatial spillover. We conducted a study of social capital and crime victimization in one ward of Tokyo city, using a Spatial Durbin Model with an inverse-distance weighting matrix that assigned each respondent a unique level of “exposure” to social capital based on all other residents’ perceptions. The study is based on a postal questionnaire sent to 20–69 years old residents of Arakawa Ward, Tokyo. The response rate was 43.7%. We examined the contextual influence of generalized trust, perceptions of reciprocity, two types of social network variables, as well as two principal components of social capital (constructed from the above four variables). Our outcome measure was self-reported crime victimization in the last five years. In the Spatial Durbin Model, we found that neighborhood generalized trust, reciprocity, supportive networks and two principal components of social capital were each inversely associated with crime victimization. By contrast, a multilevel regression performed with the same data (using administrative neighborhood boundaries) found generally null associations between neighborhood social capital and crime. Spatial regression methods may be more appropriate for investigating the contextual influence of social capital in homogeneous cultural settings such as Japan.

Suggested Citation

  • Takagi, Daisuke & Ikeda, Ken’ichi & Kawachi, Ichiro, 2012. "Neighborhood social capital and crime victimization: Comparison of spatial regression analysis and hierarchical regression analysis," Social Science & Medicine, Elsevier, vol. 75(10), pages 1895-1902.
  • Handle: RePEc:eee:socmed:v:75:y:2012:i:10:p:1895-1902
    DOI: 10.1016/j.socscimed.2012.07.039
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    References listed on IDEAS

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    4. Francesco Bogliacino & Camilo Gómez & Gianluca Grimalda, 2019. "Crime-related Exposure to Violence and Social Preferences: Experimental Evidence from Bogotá," Documentos de Trabajo, Escuela de Economía 17345, Universidad Nacional de Colombia, FCE, CID.
    5. Domínguez, Magdalena & Montolio, Daniel, 2021. "Bolstering community ties as a mean of reducing crime," Journal of Economic Behavior & Organization, Elsevier, vol. 191(C), pages 916-945.
    6. Ghalambordezfooli Rama & Hosseini Fatemeh, 2019. "The spatial correlation between social capital and crime: A case study of the new town of Pardis, Iran," Environmental & Socio-economic Studies, Sciendo, vol. 7(4), pages 62-68, December.
    7. Villalonga-Olives, E. & Kawachi, I., 2017. "The dark side of social capital: A systematic review of the negative health effects of social capital," Social Science & Medicine, Elsevier, vol. 194(C), pages 105-127.
    8. Luciano Lavecchia, 2015. "A note on social capital, space and growth in Europe," Temi di discussione (Economic working papers) 1017, Bank of Italy, Economic Research and International Relations Area.
    9. Dean, Lorraine T. & Hillier, Amy & Chau-Glendinning, Hang & Subramanian, S.V. & Williams, David R. & Kawachi, Ichiro, 2015. "Can you party your way to better health? A propensity score analysis of block parties and health," Social Science & Medicine, Elsevier, vol. 138(C), pages 201-209.

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