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Reducing Fear of Crime for Sustaining Cities; A Case Study from Turkey


  • Deniz Deniz



In urban areas, fear of crime constitutes as much a problem as crime itself. Fear of crime is often associated with fear for one's personal safety, particularly, safety from violent crimes and physical or sexual harassment in public areas. The fear of crime and feelings of insecurity keeps people off the public places where crime or anti-social behaviour are likely to occur and also limits people's behaviour to access to opportunities and facilities in their public environment. In other words, it creates a barrier to participation in the public life which reduces the liveability and sustainability of the city. It is obvious that, level of the fear of crime is unequally distributed considering the varied user profiles and places of cities. This paper is aimed to analyse how fear of crime is influenced by a variety of factors including actual crime rate, physical and social characteristics of the environment etc. with a specific case study from Izmir, Turkey in order to create safer and livable cities. Note: The alternative choice was to put this abstract under : ZW-SS 'Turkish cases in Contemporary issues/dimensions for regional development'

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  • Deniz Deniz, 2011. "Reducing Fear of Crime for Sustaining Cities; A Case Study from Turkey," ERSA conference papers ersa11p1176, European Regional Science Association.
  • Handle: RePEc:wiw:wiwrsa:ersa11p1176

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    References listed on IDEAS

    1. Lee, Lung-fei & Yu, Jihai, 2010. "Estimation of spatial autoregressive panel data models with fixed effects," Journal of Econometrics, Elsevier, vol. 154(2), pages 165-185, February.
    2. Kelejian, Harry H & Prucha, Ingmar R, 1998. "A Generalized Spatial Two-Stage Least Squares Procedure for Estimating a Spatial Autoregressive Model with Autoregressive Disturbances," The Journal of Real Estate Finance and Economics, Springer, vol. 17(1), pages 99-121, July.
    3. J. Elhorst, 2010. "Applied Spatial Econometrics: Raising the Bar," Spatial Economic Analysis, Taylor & Francis Journals, vol. 5(1), pages 9-28.
    4. Lee, Lung-fei & Liu, Xiaodong, 2010. "Efficient Gmm Estimation Of High Order Spatial Autoregressive Models With Autoregressive Disturbances," Econometric Theory, Cambridge University Press, vol. 26(01), pages 187-230, February.
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