Time Aggregation and Time Lag in Macro‐level Deterrence Research

Bibliographic Data

ID9680951
AuthorsMitchell B Chamlin (University of Oklahoma, corresponding author), Harold G Grasmick (University of Oklahoma), Robert J Bursik (University of Oklahoma), John K Cochran (0000-0001-5227-1564, University of Oklahoma)
Year1992
Volume30
Issue3
Pages377-396
Publication date1992-08-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueCriminology (JOURNAL)
Journal identifiersISSN: 0011-1384 • E-ISSN: 1745-9125
PublisherWiley (PUBLISHER • GB)
DOI10.1111/j.1745-9125.1992.tb01109.x
OpenAlexW2037270434
LanguageEN
Citations received16
References cited51

Recent arguments in research on individual‐level deterrence suggest that the effect of perceived sanction risk on illegal behavior might occur over a shorter time period than the yearly lags typically incorporated in panel studies. This study raises the same issue for macro‐level deterrence research by suggesting that panel studies using yearly data might have failed to capture the deterrent effect. The analysis uses ARIMA models with data aggregated monthly, quarterly, and semiannually to estimate the reciprocal effects between arrests and crimes for robbery, burglary, larceny, and auto theft in Oklahoma City from 1967 through 1989. No effect of crimes on arrests is found, but significant effects of arrests on crimes appear for three of the four offenses in the shorter temporal aggregations. The results suggest a need to reconsider conclusions based on panel studies that have used time aggregations and time lags that might be too long to uncover deterrent effects

Autoregressive integrated moving average · Criminology · Demographic economics · Deterrence (psychology · Econometrics · Economics · Lag · Macro · Panel data · Statistics · Time lag · Time series · Computer Science · Crime Patterns and Interventions · Crime, Illicit Activities, and Governance · Criminal Justice and Corrections Analysis · Mathematics · Psychology

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