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Crime and Arrests: An Autoregressive Integrated Moving Average (ARIMA) Approach

NCJ Number
114908
Journal
Journal of Quantitative Criminology Volume: 4 Issue: 3 Dated: (September 1988) Pages: 247-258
Author(s)
M B Chamlin
Date Published
1988
Length
12 pages
Annotation
Various theoretical perspectives suggest that marginal changes in the quantity of crime and arrests are related to one another.
Abstract
Unfortunately, they provide little guidance as to the amount of time that is required for these effects to be realized. In this paper, autoregressive integrated moving average (ARIMA) time-series modeling techniques, which necessitate making minimal assumptions concerning the lag structure one expects to find, are used to examine crime-arrest relationships in 1967-1980 aggregate data for robbery, burglary, grand larceny, and auto theft in Tulsa and Oklahoma City, Oklahoma. Consistent with deterrence and incapacitation theses, robbery arrests had a negative effect on robbery offenses in both areas; but no other significant relationships between crimes and arrests were found. These results add to a growing body of research that raises serious doubts about the efficacy of cross-sectional studies of the crime-arrest relationship. 3 tables and 25 references. (Author abstract modified)