A Dynamic Theory of Deterrence and Compliance

C Bekar and K Carlaw

No 2022-06, Working Papers from Department of Economics, University of Calgary

Abstract: Bentham understood the deterrence of antisocial behavior to be a dynamic process. The widely observed positive autocorrelation in time series of violations suggest he was correct. Yet there are no fully dynamic models of deterrence. Following Bentham, we assume that subjective probabilities of apprehension are determined by the recent history of violations and apprehensions and that the objective probability of appre- hension is increasing in the quantity of enforcement resources and decreasing in the number of violations. These assumptions imply that deterrence is a dynamic stochastic process, that the time series of violations exhibits positive autocorrelation, and that there can be disruptive positive feedback that generates waves of high and low crime. We nd that managing positive feedback is the essential policy problem. Our dynamic framework uni es aspects of research on the optimal quantity of enforcement resources and pro-active policing strategies like crackdowns and hot-spot policing.

Keywords: Deterrence; Perceptual Deterrence; Crime; Dynamics of Crime; Regulation; Markov Chains; Crime Waves; Proactive Policing; Crackdo (search for similar items in EconPapers)
JEL-codes: C63 C73 K42 (search for similar items in EconPapers)
Date: 2022-09-12
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Persistent link: https://EconPapers.repec.org/RePEc:clg:wpaper:2022-06

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