Who benefited most from the crime drop? Measuring stability and change in victimization inequality across different socio-demographic groups

Citation

Matthews B, McVie S & Norris P (2026) Who benefited most from the crime drop? Measuring stability and change in victimization inequality across different socio-demographic groups. European Journal of Criminology. https://doi.org/10.1177/1477370826142768

Abstract
Understanding victimization inequality is crucial to addressing questions of fairness and justice in exposure to crime. A growing body of research has considered how the global crime drop has affected the distribution of victimization. These studies primarily aim to understand whether different social groups have benefitted equally from overall reductions in rates of victimization; however, much of the existing research is limited by three key methodological shortcomings. Firstly, studies often compare only two discrete points in time, rather than describing dynamic changes in victimization. Secondly, researchers typically focus on either ‘unadjusted’ estimates of victimization (which measure differences between groups without taking account of any other characteristics) or ‘adjusted’ estimates (which take account of additional characteristics), but rarely both, giving only a partial picture. Finally, few studies of victimization inequality account for uncertainty in the victimization estimates which are inherent in analyses of crime survey data. This paper addresses these shortcomings by applying a robust, simulation-based approach to estimating and visualizing temporal change in both unadjusted and adjusted indicators of victimization inequality using ten sweeps of data from the Scottish Crime and Justice Survey between 2008/2009 and 2021/2022. Our analysis focuses on nine socio-demographic variables which include individual, household and community characteristics. While the results show reductions in victimization rates within all groups studied, there was clear evidence of victimization inequality between groups. Moreover, the extent of victimization inequality and how it changed over time varied considerably depending on whether adjusted or unadjusted estimates were used. Overall, rising victimization inequality was most strongly associated with ethnicity, disability and financial hardship. We argue that our methodological approach provides a more nuanced and informative perspective on stability and change in victimization inequality than previously considered, which has important implications for both criminological theory and policy development.

Keywords
Inequality; regression; Scotland; simulation; survey; victimization

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