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.

The Market for "Rough Diamonds": Information, Finance and Wage Inequality

During the past four decades both between and within group wage inequality increased significantly in the US. I provide a microfounded justification for this pattern, by introducing private employer learning in a model of signaling with credit constraints. In particular, I show that when financial constraints relax, talented individuals can acquire education and leave the uneducated pool, this decreases unskilled inexperienced wages and boosts wage inequality. This explanation is consistent with US data from 1970 to 1997, indicating that the rise of the skill and the experience premium coincides with a fall in unskilled-inexperienced wages, while at the same time skilled or experienced wages do not change much. The model accounts for: (i) the increase in the skill premium despite the growing supply of skills; (ii) the understudied aspect of rising inequality related to the increase in the experience premium; (iii) the sharp growth of the skill premium for inexperienced workers and its moderate expansion for the experienced ones; (iv) the puzzling coexistence of increasing experience premium within the group of unskilled workers and its stable pattern among the skilled ones. The results hold under various robustness checks and provide some interesting policy implications about the potential conflict between inequality of opportunity and substantial economic inequality, as well as the role of minimum wage policy in determining the equilibrium wage inequality.