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A Study of Over-Dispersed Household Victimizations in South Korea: Zero-Inflated Negative Binomial Analysis of Korean National Crime Victimization Survey

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Abstract

Analyzing the Korean Crime Victim Survey data with employing zero-inflated negative binomial (ZINB) regression, the current study aims to identify the effect of immunity from criminal victimization and the determinants of household victimization in South Korea. The results show that there is a significant immunity effect on the distribution of household victimizations. Furthermore, lack of considering an immune effect may result in a misleading conclusion. As main determinants of victimizations in South Korea, communal efforts are found to be important. Theoretical explanation and policy implications are discussed.

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References

  • Bennett, T., & Wright, R. (1984). Burglars on burglary: prevention and the offender. Hampshire: Gower.

    Google Scholar 

  • Berk, R., & MacDonald, J. M. (2008). Overdispersion and Poisson regression. Journal of Quantitative Criminology, 24, 269–284.

    Article  Google Scholar 

  • Breitenbecher, K. H., & Christine, G. A. (1998). An empirical evaluation of a program designed to reduce the risk of multiple sexual victimization. Journal of Interpersonal Violence, 13, 472–488.

    Article  Google Scholar 

  • Budd, T. (1999). Burglary of Domestic Dwellings: Findings from the British Crime Survey. Home Office Statistical Bulletin, Research Development Statistics, Issue 4.

  • Cohen, L., Kleugal, J., & Land, K. (1981). Social inequality and predatory criminal victimization: an exposition and test of a formal theory. American Sociological Review, 46, 505–524.

    Article  Google Scholar 

  • Coleman, S. (1964). Introduction to mathematical sociology. New York: Free Press.

    Google Scholar 

  • Cromwell, P., Olson, J., & D’Aunn Wester, A. (1991). Breaking and entering: an ethnographic analysis of burglary. Newbury Park: Sage.

    Google Scholar 

  • Davis, R., Maxwell, C., & Taylor, B. (2006). Preventing repeat incidents of family violence: analysis of data from three field experiments. Journal of Experimental Criminology, 2, 183–210.

    Article  Google Scholar 

  • Deams, T. (2005). Repeat victimization and the study of social control. International Journal of the Sociology of Law, 33, 85–100.

    Article  Google Scholar 

  • Eaton, W. W., & Fortin, A. (1978). A third interpretation for the generating process of the negative binomial distribution. American Sociological Review, 43, 264–267.

    Article  Google Scholar 

  • Ellingworth, D., Hope, T., Osborn, D. R., Trickett, A., & Pease, K. (1997). Prior victimization and crime risk. International Journal of Risk, Security and Crime Prevention, 3, 35–42.

    Google Scholar 

  • Farrell, G. (1995). Preventing repeat victimization. In M. Tonry & D. P. Farrigton (Eds.), Building a safer society: strategic approaches to crime prevention. Crime and justice: a review of research 19 (pp. 469–534). Chicago: University of Chicago Press.

    Google Scholar 

  • Farrell, G. (2003). Bibliography of Studies on or Incorporating Repeat Victimization. Retrieved from www.victimology.nl/onlpub/otherdocs/rv-bibliography.pdf.

  • Farrell, G. (2005). Progress and prospects in the prevention of repeat victimization. In N. Tilley (Ed.), Handbook of crime prevention and community safety (pp. 143–170). Portland: Willan Publishing Ltd.

    Google Scholar 

  • Farrell, G., & Pease, K. (1993). Once bitten, twice bitten: repeat victimization and its implications for crime prevention. Crime Prevention Unit Paper No. 46. London: Home Office.

    Google Scholar 

  • Forrester, D., Chatterton, M., & Pease, K. (1988). The Kirkholt burglary prevention project. London: Home Office.

    Google Scholar 

  • Forrester, D., Frenz, S., O’Connell, M., & Pease, K. (1990). The Kirkholt burglary prevention project: phase II, Crime Prevention Unit Paper 23. London: Home Office.

    Google Scholar 

  • Garofalo, J., & Clark, D. (1992). Guardianship and residential burglary. Justice Quarterly, 9, 443–463.

    Article  Google Scholar 

  • Gottfredson, M. R. (1984). Victims of crime: the dimension of risk, Home Office Research Study 81. London: Home Office.

    Google Scholar 

  • Hanmer, J., Griffiths, S., & Jerwood, D. (1999). Arresting evidence: domestic violence and repeat victimization. Police Research Series Paper 104. London: Home Office.

    Google Scholar 

  • Hindelang, M., Gottfredson, M., & Garafalo, J. (1978). Victims of personal crime. Cambridge: Ballinger.

    Google Scholar 

  • Hope, T. (1984). Building design and burglary. In R. Clarke & T. Hope (Eds.), Coping with burglary: research perspectives on policy (pp. 45–59). Boston: Kluwer.

    Chapter  Google Scholar 

  • Hope, T. (2007). Theory and method: the social epidemiology of crime victims. In S. Walklate (Ed.), Handbook on victims and victimology. Cullompton: Willan.

    Google Scholar 

  • Hope, T., & Trickett, A. (2008). The distribution of crime victimization in the population. International Review of Victimology, 15, 37–58.

    Article  Google Scholar 

  • Hope, T., & Norris, P. (2012). Heterogeneity in the frequency distribution of crime victimization. Journal of Quantitative Criminology. Published online: 05 November 2012. Retrieved from http://link.springer.com/content/pdf/10.1007%2Fs10940-012-9190-x.pdf

  • Hough, M. (1984). Residential burglary: a profile from the British Crime Survey. In R. Clarke & T. Hope (Eds.), Coping with burglary: research perspectives on policy (pp. 15–28). Boston: Kluwer.

    Chapter  Google Scholar 

  • Kim, J., & Hong, Y. (2011). Korean Crime Victim Survey in 2010. Retrieved from http://www.kic.re.kr/html/pub_data/publication_download.asp?file=/savedata/research_report/11-23_전국범죄피해조사2010.pdf&idx=969

  • Lambert, D. (1992). Zero-inflated Poisson regression, with an application to defects in manufacturing. Technometics, 34, 1–14.

    Article  Google Scholar 

  • Lauritsen, J. L., & Davis-Quinet, K. F. (1995). Repeat victimization among adolescents and young adults. Journal of Quantitative Criminology, 11(2), 143–166.

    Article  Google Scholar 

  • Lloyd, S., Farrell, G., & Pease, K. (1994). Preventing repeated domestic violence: a demonstration project on Merseyside. Police Research Group, Crime Prevention Unit Paper 49. London: Home Office.

    Google Scholar 

  • Meier, R., & Miethe, T. (1993). Understanding theories of criminal victimization. In M. Tonry (Ed.), Crime and justice: a review of research. Chicaho: University of Chicago Press.

    Google Scholar 

  • Miethe, T. D., & McDowall, D. (1993). Contextual effects in models of criminal victimization. Social Forces, 71, 741–760.

    Article  Google Scholar 

  • Miethe, T. D., & Meier, R. F. (1990). Opportunity, choice, and criminal victimization: a test of a theoretical model. Journal of Research in Crime and Delinquency, 27, 243–266.

    Article  Google Scholar 

  • Miethe, T. D., Stafford, M. C., & Long, J. S. (1987). Social differentiation in criminal victimization: a test of routine activities/lifestyle theories. American Sociological Review, 52, 184–194.

    Article  Google Scholar 

  • Nelson, J. (1980). Multiple victimization in American cities: a statistical analysis of rare events. American Journal of Sociology, 85, 870–891.

    Article  Google Scholar 

  • Osborn, D. R., Ellingworth, D., Hope, T., & Trickett, A. (1996). Are repeatedly victimized households different? Journal of Quantitative Criminology, 12, 223–245.

    Article  Google Scholar 

  • Osborn, D. R., & Tseloni, A. (1998). The distribution of household property crimes. Journal of Quantitative Criminology, 14(3), 307–330.

    Article  Google Scholar 

  • Osgood, W. (2000). Poisson-based regression analysis of aggregate crime rates. Journal of Quantitative Criminology, 16, 21–43.

  • Ousey, G. C., Wilcox, P., & Brummel, S. (2008). Déjà vu all over again: investigating temporal continuity of adolescent victimization. Journal of Quantitative Criminology, 24, 307–336.

    Article  Google Scholar 

  • Park, S., & Eck, J. (2013). Understanding the random effect on victimization distributions: a statistical analysis of random repeat victimizations. Victims and Offenders, 8, 399–415.

    Article  Google Scholar 

  • Paternoster, R., & Brame, R. (1997). Multiple routes to delinquency? A test of developmental and general theories of crime. Criminology, 35, 45–84.

  • Pease, K. (1991). The Kirkholt project: preventing burglary on a British public housing estate. Security Journal, 2, 73–77.

    Google Scholar 

  • Pease, K. (1992). The Kirkholt project: preventing burglary on a British public housing estate. In R. V. Clarke (Ed.), Situational crime prevention: successful case studies. Monsey: Harrow and Heston.

    Google Scholar 

  • Pease, K. (1998). Repeat victimization: taking stock. Crime Detection and Prevention series No. 90. London: Home Office.

    Google Scholar 

  • Roh, S., Kim, E., & Yun, M. (2010). Criminal victimization in South Korea: a multilevel approach. Journal of Criminal Justice, 38, 301–310.

    Article  Google Scholar 

  • Sampson, A., & Phillips, C. (1992). Multiple victimization: racial attacks on an East London Estate, Home Office Crime Prevention Unit Paper 36. London: Home Office.

    Google Scholar 

  • Short, M. B., D’Orsogna, M. R., Brantingham, P. J., & Tita, G. E. (2009). Measuring and modeling repeat and near-repeat burglary effects. Journal of Quantitative Criminology, 25, 325–339.

    Article  Google Scholar 

  • Shury, J., Speed, M., & Vivian, D. (2005). Crime against retail & manufacturing premises: findings from the 2002 Commercial Victimisation Survey. London: Home Office Research.

    Google Scholar 

  • Skogan, W. G. (1999). Victim surveys at century’s end. In J. J. M. van Dijk, R. G. H. van Kaam, & J.-A. M. Wemmers (Eds.), Caring for crime victims: selected proceedings of the ninth International Symposium on Victimology (pp. 41–53). Amsterdam: Criminal Justice Press.

    Google Scholar 

  • Sparks, R., Genn, H., & Dodd, D. (1977). Surveying victims: a study of the measurement of criminal victimization, perceptions of crime, and attitudes to criminal justice. London: Wiley.

    Google Scholar 

  • Sparks, R. F. (1981). Multiple victimization: Evidence, theory, and future research. Journal of Criminal Law & Criminology, 72, 762–778.

  • Tilley, N., & Laycock, G. (2002). Working out what to do: evidence-based crime reduction. Crime Reduction Series Paper 11. London: Home Office.

    Google Scholar 

  • Tseloni, A., & Farrell, G. (2002). Burglary victimization across Europe: the roles of prior victimization, micro- and macro-level routine activities. In P. Nieuwbeerta (Ed.), Crime victimization in comparative perspective: results from the International Crime Victims Survey, 1989–2000 (pp. 141–161). Amsterdam: BOOM-publishers.

    Google Scholar 

  • Tseloni, A., & Pease, K. (2003). Repeat personal victimization: boost or flags? British Journal of Criminology, 43, 196–212.

    Article  Google Scholar 

  • Tseloni, A., & Pease, K. (2004). Repeat personal victimization: random effects, event dependence and unexplained heterogeneity. British Journal of Criminology, 44, 931–945.

    Article  Google Scholar 

  • Tseloni, A., Wittebrood, K., Farrell, G., & Pease, K. (2004). Burglary victimization in England and Wales, the United States and the Netherlands: a cross-national comparative test of routine activities and lifestyle theories. British Journal of Criminology, 44, 66–91.

    Article  Google Scholar 

  • Vuong, Q. H. (1989). Likelihood ratio tests for model selection and non-nested hypotheses. Econometrica, 57(2), 307–333.

    Article  Google Scholar 

  • Weisel, D. L. (2005). Analyzing Repeat Victimization. Problem-Oriented Guides for Police Problem-Solving Tools Series, No. 4. COPS: US Department of Justice. Retrieved from http://www.cops.usdoj.gov/files/ric/Publications/e07055803.pdf

  • Winkelmann, R. (2008). Econometric analysis of count data. Heidelberg: Springer.

    Google Scholar 

  • Zahm, D. (2007). Using Crime Prevention Through Environmental Design in Problem Solving: Tool Guide No. 8. Retrieved from http://www.popcenter.org/tools/cpted/

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  1. Department of Criminal Justice, University of Tennessee at Chattanooga, 615 McCallie Avenue, Chattanooga, TN, 37403-2598, USA

    Seong min Park

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  1. Seong min Park
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min Park, S. A Study of Over-Dispersed Household Victimizations in South Korea: Zero-Inflated Negative Binomial Analysis of Korean National Crime Victimization Survey. Asian Criminology 10, 63–78 (2015). https://doi.org/10.1007/s11417-015-9206-1

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