Journal of Quantitative Criminology

, Volume 8, Issue 3, pp 265–285 | Cite as

Area characteristics and regional variates as determinants of area property crime levels

  • Denise R. Osborn
  • Alan Trickett
  • Rob Elder


This article seeks to examine the area characteristics that act as determinants of area property crime levels, namely, incidence and prevalence. The crime figures are extracted from the 1984 British Crime Survey. Area characteristics are taken from the 1981 UK census. Initial exploratory analysis considers the non-Gaussian nature of the crime data, the statistical implications of this, and the transformations used to overcome these problems. In addition, possible regional and inner-city/non-inner-city variations are considered. The later stages move from simple individual correlations to multiple regression models. Three regression models are considered and the reasons for refining these are explored, with the results indicating that both area characteristics and regional influences play a role as determinants of the area crime level. In particular, population density and the area population age profile have significant roles to play. The conclusions support the recent revival of the application of ecological concepts in the analysis of crime levels.

Key words

modeling victimization property crime crime survey ecological analysis multiple regression 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Baldwin, J., Bottoms, A. E., and Walker, M. A. (1976).The Urban Criminal, Tavistock, London.Google Scholar
  2. Belsey, D. A., Kuh, E., and Welsch, R. E. (1980).Regression Diagnostics: Identifying Influential Data and Sources of Collinearity, Wiley, New York.Google Scholar
  3. Box, G. E. P., and Cox, D. R. (1964). An analysis of transformations.J. Roy. Stat. Soc. Ser: B 26: 211–243.Google Scholar
  4. Brantingham, P. J., and Brantingham, P. L. (1991).Environmental Criminology, Waveland, Ill.Google Scholar
  5. Doan, T. A. (1989).RATS User's Manual, VAR Econometrics, Evanston, Ill.Google Scholar
  6. Judge, G. G., Griffiths, W. E., Hill, R. C., and Lee, T-C. (1980).The Theory and Practice of Econometrics, Wiley, New York.Google Scholar
  7. Maddala, G. S. (1977).Econometrics, McGraw-Hill, New York.Google Scholar
  8. Marsh, C. (1988).Exploring Data, Polity/Blackwell, Cambridge.Google Scholar
  9. NOP Market Research Limited (1985).1984 British Crime Survey: Technical Report, NOP, Southampton.Google Scholar
  10. Park, R. E. (1936). Human ecology.Am. J. Sociol 42: 1–15.Google Scholar
  11. Sampson, R. J., and Groves, W. B. (1989). Community structure and crime: Testing socialdisorganization theory.Am. J. Sociol. 94: 774–802.Google Scholar
  12. Sampson, R. J., and Lauritsen, J. L. (1990). Deviant lifestyles, proximity to crime, and the offender-victim link in personal violence.J. Res. Crime Deling. 27: 110–139.Google Scholar
  13. Sampson, R. J., and Wooldredge, J. D. (1987). Linking the micro- and macro-level dimensions of lifestyle-routine activity and opportunity models of predatory victimization.J. Quant. Criminol. 3: 371–393.Google Scholar
  14. Scott, A., and Wild, C. (1991). Transformations and R2.Am. Stat. 45: 127–129.Google Scholar
  15. Shaw, C. R., and McKay, M. D. (1942).Juvenile Delinquency and Urban Areas, University Press, Chicago.Google Scholar
  16. Stewart, J. (1991).Econometrics, Philip Allan, New York.Google Scholar
  17. Trickett, A., Osborn, D. R., Seymour, J., and Pease, K. (1992). What is different about high crime areas.Br. J. Criminol. 32: 81–89.Google Scholar

Copyright information

© Plenum Publishing Corporation 1992

Authors and Affiliations

  • Denise R. Osborn
    • 1
  • Alan Trickett
    • 1
  • Rob Elder
    • 1
  1. 1.Department of Econometrics and Social StatisticsUniversity of ManchesterManchesterUK

Personalised recommendations