Abstract
ObjectivesGenerally speaking, crime is, fortunately, a rare event. As far as modelling is concerned, this sparsity of data means that traditional measures to quantify concentration are not appropriate when applied to crime suffered by a population. Our objective is to develop a new technique to measure the concentration of crime which takes into account its low frequency of occurrence and its high degree of concentration in such a way that this measure is comparable over time and over different populations.MethodsThis article derives an estimate of the distribution of crime suffered by a population based on a mixture model and then evaluates a new and standardised measurement of the concentration of the rates of suffering a crime based on that distribution.ResultsThe new measure is successfully applied to the incidence of robbery of a person in Mexico and is able to correctly quantify the concentration crime in such a way that is comparable between different regions and can be tracked over different time periods.ConclusionsThe risk of suffering a crime is not uniformly distributed across a population. There are certain groups which are statistically immune to suffering crime but there are also groups which suffer chronic victimisation. This measure improves our understanding of how patterns of crime can be quantified allowing us to determine if a prevention policy results in a crime reduction rather than target displacement. The method may have applications beyond crime science.
Highlights
The risk of suffering a crime is not uniformly distributed over a region (Johnson 2010) and nor is it uniformly distributed across members of the same community (Grove et al 2012), with some regions and some population groups more affected by crime than others (Farrell 2015)
There are certain groups which are statistically immune to suffering crime but there are groups which suffer chronic victimisation
This measure improves our understanding of how patterns of crime can be quantified allowing us to determine if a Electronic supplementary material The online version of this article contains supplementary material, which is available to authorized users
Summary
The risk of suffering a crime is not uniformly distributed over a region (Johnson 2010) and nor is it uniformly distributed across members of the same community (Grove et al 2012), with some regions and some population groups more affected by crime than others (Farrell 2015). In the case of burglary, for example, it has been shown that houses in deprived areas suffer a higher risk of being the target of a crime, whilst other regions appear to be immune to that type of crime (Bowers et al 2005) Whether it is determined by race, age, income or many other factors, it has been found that the risk of suffering a robbery of a person is not uniformly distributed across all the members of the same population. How far away from a homogeneous distribution is the crime suffered by the population in a region and how can we quantify it? Does the distribution of crime, as well as its concentration, change over time? These questions are highly relevant for decision-makers interested in designing policies to reduce the levels of crime
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