Personal indebtedness, community characteristics and theft crimes

Becker (1968) and Stigler (1970) provide the germinal works for an economic analysis of crime, and their approach has been utilised to consider the response of crime rates to a range of economic, criminal and socioeconomic factors. Until recently however this did not extend to a consideration of the role of personal indebtedness in explaining the observed pattern of crime. This paper uses the Becker (1968) and Stigler (1970) framework, and extends to a fuller consideration of the relationship between economic hardship and theft crimes in an urban setting. The increase in personal debt in the past decade has been significant, which combined with the recent global recession, has led to a spike in personal insolvencies. In the context of the recent recession it is important to understand how increases in personal indebtedness may spillover into increases in social problems like crime. This paper uses data available at the neighbourhood level for London, UK on county court judgments (CCJ's) granted against residents in that neighbourhood, this is our measure of personal indebtedness, and examines the relationship between a range of community characteristics (economic, socio-economic, etc), including the number of CCJ's granted against residents, and the observed pattern of theft crimes for three successive years using spatial econometric methods. Our results confirm that theft crimes in London follow a spatial process, that personal indebtedness is positively associated with theft crimes in London, and that the covariates we have chosen are important in explaining the spatial variation in theft crimes. We identify a number of interesting results, for instance that there is variation in the impact of covariates across crime types, and that the covariates which are important in explaining the pattern of each crime type are largely stable across the three periods considered in this analysis.

On the Sources of Uncertainty in Exchange Rate Predictability

We analyse the role of time-variation in coefficients and other sources of uncertainty in exchange rate forecasting regressions. Our techniques incorporate the notion that the relevant set of predictors and their corresponding weights, change over time. We find that predictive models which allow for sudden rather than smooth, changes in coefficients significantly beat the random walk benchmark in out-of-sample forecasting exercise. Using innovative variance decomposition scheme, we identify uncertainty in coefficients' estimation and uncertainty about the precise degree of coefficients' variability, as the main factors hindering models' forecasting performance. The uncertainty regarding the choice of the predictor is small.

Tracking cost savings from competitive tendering in the short and long run

A major initiative of the Thatcher and Major Conservative administrations was that public sector ancillary and professional services provided by incumbent direct service organisations [DSOs] be put out to tender. Analyses of this initiative, in the UK and elsewhere, found costs were often reduced in the short run. However, few if any studies went beyond the first round of tendering. We analyze data collected over successive rounds of tendering for cleaning and catering services of Scottish hospitals in order to assess the long term consequences of this initiative. The experience of the two services was very different. Cost savings for cleaning services tended to increase with each additional round of tendering and became increasingly stable. In accordance with previous results in the literature, DSOs produced smaller cost reductions than private contractors: probably an inevitable consequence of the tendering process at the time. Cost savings from DSOs tended to disappear during the first round of tendering, but they appear to have been more permanent in successive rounds. Cost savings for catering, on the other hand, tended to be much smaller, and these were not sustained.