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Multilevel modelling of the number of property crimes: household and area effects

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  • Andromachi Tseloni

Abstract

Summary. This study examines household and area effects on the incidence of total property crimes and burglaries and thefts. It uses data from the 2000 British Crime Survey and the 1991 UK census small area statistics. Results are obtained from estimated random‐effects multilevel models, with an assumed negative binomial distribution of the dependent variable. Both household and area characteristics, as well as selected interactions, explain a significant portion of the variation in property crimes. There are also a large number of significant between‐area random variances and covariances of household characteristics. The estimated fixed and random effects may assist in advancing victimization theory. The methods have potential for developing a better understanding of factors that give rise to crime and so assist in framing crime prevention policy.

Suggested Citation

  • Andromachi Tseloni, 2006. "Multilevel modelling of the number of property crimes: household and area effects," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(2), pages 205-233, March.
    • Handle: RePEc:bla:jorssa:v:169:y:2006:i:2:p:205-233
    DOI: 10.1111/j.1467-985X.2005.00388.x
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    Cited by:

    1. Mohamed Amara, 2015. "Multilevel Modelling of Individual Fertility Decisions in Tunisia: Household and Regional Contextual Effects," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 124(2), pages 477-499, November.
    2. Daniel Borbely & Gennaro Rossi, 2023. "Urban regeneration projects and crime: evidence from Glasgow," Journal of Economic Geography, Oxford University Press, vol. 23(6), pages 1273-1301.
    3. Johannes Gräb & Michael Grimm, 2008. "Spatial Inequalities Explained: Evidence from Burkina Faso," Discussion Papers of DIW Berlin 843, DIW Berlin, German Institute for Economic Research.
    4. Alex Hirschfield & Mark Birkin & Chris Brunsdon & Nicolas Malleson & Andrew Newton, 2014. "How Places Influence Crime: The Impact of Surrounding Areas on Neighbourhood Burglary Rates in a British City," Urban Studies, Urban Studies Journal Limited, vol. 51(5), pages 1057-1072, April.
    5. Ajide, Folorunsho M., 2021. "Fiscal Policy and Crime Rate in Nigeria," African Journal of Economic Review, African Journal of Economic Review, vol. 9(4), September.
    6. Gonzalo Herranz de Rafael & Juan Sebastián Fernández-Prados, 2019. "Victimization, Social Structure and Psychosocial Variables: The Case of Spain in 1999 and 2016," Social Sciences, MDPI, vol. 8(3), pages 1-10, March.
    7. Nick Malleson & Alison Heppenstall & Linda See & Andrew Evans, 2013. "Using an Agent-Based Crime Simulation to Predict the Effects of Urban Regeneration on Individual Household Burglary Risk," Environment and Planning B, , vol. 40(3), pages 405-426, June.
    8. Cormac O'Dea & Ian Preston, 2012. "The distributional impact of public spending in the UK," IFS Working Papers W12/06, Institute for Fiscal Studies.
    9. Kingsley U. Ejiogu, 2023. "Risk Terrain and Multilevel Modeling of Street Robbery Distribution in Baltimore City," SAGE Open, , vol. 13(4), pages 21582440231, December.
    10. Georgios Papadopoulos, 2013. "Immigration Status and Victimization: Evidence from the British Crime Survey," University of East Anglia Applied and Financial Economics Working Paper Series 042, School of Economics, University of East Anglia, Norwich, UK..

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