In the last decades, the interest in the relationship between crime and business cycle has widely increased. It is a diffused opinion that a causal relationship goes from economic variables to criminal activities, but this causal effect is observed only for some typology of crimes, such as property crimes. In this work we examine the possibility of the existence of some common factors (interpreted as cyclical components) driving the dynamics of Gross Domestic Product and a large set of criminal types by using the nonparametric version of the dynamic factor model. A first aim of this exercise is to detect some comovements between the business cycle and the cyclical component of some typologies of crime, which could evidence some relationships between these variables; a second purpose is to select which crime types are related to the business cycle and if they are leading, coincident or lagging. Italy is the case study for the time span 1991:1–2004:12; the crime typologies are constituted by the 22 official categories classified by the Italian National Statistical Institute. The study finds that most of the crime types show a counter-cyclical behavior with respect to the overall economic performance, and only a few of them have an evident relationship with the business cycle. Furthermore, some crime offenses, such as bankruptcy, embezzlement and fraudulent insolvency, seem to anticipate the business cycle, in line with recent global events.
Cycles in Crime and Economy: Leading, Lagging and Coincident Behaviors
DETOTTO, CLAUDIO;
2012-01-01
Abstract
In the last decades, the interest in the relationship between crime and business cycle has widely increased. It is a diffused opinion that a causal relationship goes from economic variables to criminal activities, but this causal effect is observed only for some typology of crimes, such as property crimes. In this work we examine the possibility of the existence of some common factors (interpreted as cyclical components) driving the dynamics of Gross Domestic Product and a large set of criminal types by using the nonparametric version of the dynamic factor model. A first aim of this exercise is to detect some comovements between the business cycle and the cyclical component of some typologies of crime, which could evidence some relationships between these variables; a second purpose is to select which crime types are related to the business cycle and if they are leading, coincident or lagging. Italy is the case study for the time span 1991:1–2004:12; the crime typologies are constituted by the 22 official categories classified by the Italian National Statistical Institute. The study finds that most of the crime types show a counter-cyclical behavior with respect to the overall economic performance, and only a few of them have an evident relationship with the business cycle. Furthermore, some crime offenses, such as bankruptcy, embezzlement and fraudulent insolvency, seem to anticipate the business cycle, in line with recent global events.
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