Population inequality: the case of repeat

This paper employs data from the 2000 British Crime Survey for England and Wales to discuss ways of illustrating the degree of inequality in the distribution of crime victimisation. In particular, Lorenz curves are presented for major crime categories, i.e. property, personal and vehicle crime, and their components are presented. They are fitted both nationally (i.e. to victimised and non-victimised people) and amongst victims. Crime Lorenz curves over victims illustrate repeat victimisation. Additional repeat victimisation statistics, such as concentration, the percentage of repeat crimes and the percentage of repeat victims, are also shown. Threats and assaults are the most recurring crimes whereas theft of vehicles shows low rates of repetition within a year

Securing the premises

How effective are different home security devices, on their own and in combination with others? Andromachi Tseloni and Rebecca Thompson analyse crime survey data in search of answers

Fear of crime and victimisation: a multivariate multilevel analysis of competing measurements

This study models simultaneously three commonly used indicators of fear of crime: feeling unsafe alone at home after dark, feeling unsafe walking alone after dark and worry about becoming victim of crime, over direct (being a victim) and indirect (knowing a victim) victimisation controlling for demographic and socio-economic characteristics of individuals via multivariate, i.e. multiple responses, multilevel analysis of data from Athens, Greece. The results show that: (a) the association of the three indicators weakens as key explanatory factors of fear of crime are accounted for, (b) crime experiences are related to feeling unsafe at home alone after dark only via its association with feeling unsafe walking alone after dark and worry about becoming victim of crime and (c) indirect and direct prior victimisation and crime exposure shapes predominately perceived future risk

The global crime drop and changes in the distribution of victimisation.

world, have fallen. Less attention has been paid to the distribution of crime across households, though this is crucial in determining optimal distribution of limited policing resources in pursuing the aim of distributive justice. The writers have previously demonstrated that in England and Wales the distribution of crime victimisation has remained pretty much unchanged over the period of the crime drop. The present paper seeks to extend the study of changes in the distribution of victimisation over time using data from 25 countries contributing data to the International Crime Victimisation Survey (ICVS) sweeps (1989-2000). While fragmentary, the data mirror the trends discerned in England and Wales. The trends are not an artefact of the inclusion of particular countries in particular sweeps. The demographic, economical, geographical and social household characteristics associated with victimisation are consistent across time. The suggested policy implication is the need for greater emphasis on preventing multiple victimisation

Income disparities of burglary risk and security availability during the crime drop. British Journal of Criminology, 51(2), 296-313.

In the past fifteen years volume crimes dropped substantially in most countries with reliable crime trend estimates. In England and Wales domestic burglary fell by 58% between 1995 and 2008/09, the trend levelling off after 2005/6. Wider use of more and better security arguably contributed to these drops. The availability of enhanced and especially basic security increased between 1997 and 2005/06, while burglary risk fell for all population income groups. Considering, however, the financial cost of burglary protection devices it is not surprising that enhanced security continues to be more accessible to better off households. In 2005/06 the most affluent households were 60% more likely to have such devices compared to the poorest. This is consistent with the finding that nationally burglary drops have occurred least amongst the poorest segments of population. The better off continue to benefit most in terms of crime protection: burglary risk differentials between the lowest and all other income groups widened during the decade up to 2005/06. Security Impact Assessment Tool analysis however shows that enhanced security confers greatest burglary protection for those who can least afforded it. These results suggest that making enhanced security available to the poorest would further reduce national burglary rates

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

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 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 victimisation 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

Fear of crime, perceived disorders and property crime: a multivariate analysis at the area level [In: Farrell, G., Bowers, K., Johnson, S.D. and Townsley, M., eds., Imagination for crime prevention: essays in honor of Ken Pease]

This work estimates associated models of areas’ fear of crime, perceived disorders and property crime rates over area characteristics and region of England and Wales via multivariate (multilevel) modelling. This statistical model, which draws upon data from the 2000 British Crime Survey and the 1991 (U.K.) Census at the postcode sector-level, allows for the estimation of any interdependence among the three dependent variables. The study shows that the effects of area characteristics and region on fear of crime, disorders and property crime rates are not uniform. Roughly half of the between-areas covariance of property crime rates, fear of crime and perceived disorders is explained by the areas’ characteristics and regional dummy variables. The estimated multivariate models of this work, apart from expanding theoretical knowledge, may assist crime prevention efforts via identifying the most efficient measure for a set of targets as well as any diffusion or displacement effects between crime reduction and public reassurance initiatives

Concentration of personal and household crimes in England and Wales

Crime is disproportionally concentrated in few areas. Though long-established, there remains uncertainty about the reasons for variation in the concentration of similar crime (repeats) or different crime (multiples). Wholly neglected have been composite crimes when more than one crime types coincide as parts of a single event. The research reported here disentangles area crime concentration into repeats, multiple and composite crimes. The results are based on estimated bivariate zero-inflated Poisson regression models with covariance structure which explicitly account for crime rarity and crime concentration. The implications of the results for criminological theorizing and as a possible basis for more equitable police funding are discussed