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Does crime depend on the “state” of economic misery?

Troy Lorde (), Mahalia Jackman, Simon Naitram () and Shane Lowe

International Journal of Social Economics, 2016, vol. 43, issue 11, 1124-1134

Abstract: Purpose - It is generally understood that during periods of economic hardship, some persons turn to crime to compensate for income deficiencies. The paper investigates the impact of economic misery on crime. The purpose of this paper is to provide insight into the relationship between economic conditions and economic misery. Design/methodology/approach - An index of misery is employed that takes into account not only the rate of unemployment, but also the rate of inflation. The non-linearity of the relationship between economic misery and crime is modelled using Markov-switching (MS) models and the synchronization of their cycles is measured via the concordance index. Findings - The paper looked at the relationship between economic misery and five types of crime: property crime, theft from motor, theft of motor, fraud and robbery. No evidence of a contemporaneous relationship between economic misery and crime was uncovered. Property and theft of motor crime respond to the state of misery with a lag of one period, supporting the criminal motivation effect. Economic misery is in the same regime as property crime 50 per cent of the time and with theft from motor crime almost 60 per cent of the time. Originality/value - Most of the theoretical and empirical work is based on larger economies. The paper provides some insight into the relationship between economic conditions and economic misery in developing microstates, a niche which has been largely ignored in the literature. The use of MS models in the paper deviates from the tradition of examining linear relationships on the basis that the variables under investigation are inherently cyclical and linear analysis is likely to provide a weak fit under these circumstances.

Keywords: Crime; Misery; Small island states (search for similar items in EconPapers)
Date: 2016
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