NCJ Number
193672
Journal
Journal of Quantitative Criminology Volume: 17 Issue: 4 Dated: December 2001 Pages: 391-407
Editor(s)
David McDowall
Date Published
December 2001
Length
17 pages
Annotation
This article presented the author’s opinions, thoughts, and questions regarding David Cantor and Kenneth Land’s 1985 theory on unemployment and crime relating changes in the business cycle and the aggregate rate of crime, and David Greenberg’s use of cointegration within the context of unemployment and crime.
Abstract
In discussing the ongoing debate between Cantor and Land (C-L) and Greenberg’s theories on unemployment and crime relationship and the use of time series analysis models, this article begins with a review of the C-L macro-level theory and a review of the original paper, followed by an argument for the use of more structured models or approaches in theory testing, and concluding with a discussion on Greenberg’s use of cointegration. The C-L theory had proven highly controversial both theoretically and empirically. Greenberg’s negative assessment of C-L was based on the theory’s ambiguousness and his articulation of a different theory. C-L had consistently argued their desire to explain the association between unemployment and changes in crime rates. C-L was credited with laying out a semi-structured model of the unemployment and crime relationship. However, one question raised was how C-L operationalized their theory. It was argued that C-L suggested a theory of short-term changes in the business cycle and its effect on aggregate fluctuations in crime. On the other hand, Greenberg suggested the use of cointegration, a time series that was cointegrated with crime rates controlling for long-term trends without first-differencing. Greenberg’s cointegration was seen as not capturing the effect of business cycle changes on crime rates. It was seen as potentially appropriate for other settings. It has been suggested that there should be increased communication between economists and criminologists in the area of unemployment and crime. Future work should concentrate on lower levels of aggregation with theoretically and substantively interesting data sets. References