Personal indebtedness, community characteristics and theft crimes. (August 2017)

• Record Type: Journal Article
• Authors: McIntyre, Stuart G
• Is Part Of: Urban studies. Volume 54:Number 10(2017:Aug.)
• Page Start: 2395
• Page End: 2419
• Publication Date: 2017-08
• Subjects: Spatial econometrics -- urban economies -- crime -- personal debt; 空间经济测量 -- 城市经济 -- 犯罪 -- 个人债务; Cities and towns -- Periodicals; City planning -- Periodicals; 307.1216
• DOI: 10.1177/0042098016647335
• Languages: English
• ISSNs: 0042-0980

Abstract

Debt played a central role in the Great Recession, both in its cause and in its resolution, and once again, concern is rising about household indebtedness. This paper examines the relationship between personal indebtedness and theft crime using information on personal debt default. This paper builds on an established literature examining economic conditions and community crime rates, with an analytical framework provided by 'the market model of crime'. Our paper is motivated from the economic, sociology and criminology literatures, and extends to a fuller consideration of the relationship between economic hardship and theft crimes in an urban setting. In particular, the sociology and criminology literature permit a much deeper understanding of the human behaviour and motivations underpinning the relationships represented in the market model. Using data available at the neighbourhood level for London, UK on county court judgements (CCJs) granted against residents in each neighbourhood as our measure of personal indebtedness, we examine the relationship between this measure and a range of community characteristics, and the observed pattern of theft crimes using spatial econometric methods. Our results confirm that theft crimes in London follow a spatial process, and that personal indebtedness is positively associated with theft crimes in London. 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 period considered in this analysis. 1