Dynamic Law Enforcement with Learning
This article modifies a standard model of law enforcement to allow for learning by doing. We incorporate the process of enforcement learning by assuming that the agency's current marginal cost is a decreasing function of its past experience of detecting and convicting. The agency accumulates data and information (on criminals, on opportunities of crime), enhancing the ability of future apprehension at a lower marginal cost. We focus on the impact of enforcement learning on optimal compliance rules. In particular, we show that the optimal fine could be less than maximal and the optimal probability of detection could be higher than otherwise. It is also suggested that the optimal imprisonment sentence could be higher than otherwise. Copyright 2004, Oxford University Press.
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Volume (Year): 20 (2004)
Issue (Month): 1 (April)
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- Rubinstein, Ariel, 1980. "On an anomaly of the deterrent effect of punishment," Economics Letters, Elsevier, vol. 6(1), pages 89-94.
- Emons, Winand, 2003.
"A note on the optimal punishment for repeat offenders,"
International Review of Law and Economics,
Elsevier, vol. 23(3), pages 253-259, September.
- Winand Emons, 2001. "A Note on the Optimal Punishment for Repeat Offenders," Diskussionsschriften dp0104, Universitaet Bern, Departement Volkswirtschaft.
- Leung, S.F., 1991.
"How to Make the Fine Fit the Corporate Crime? An Analysis of Static and Dynamic Optimal Punishment Theories,"
RCER Working Papers
261, University of Rochester - Center for Economic Research (RCER).
- Leung, Siu Fai, 1991. "How to make the fine fit the corporate crime? : An analysis of static and dynamic optimal punishment theories," Journal of Public Economics, Elsevier, vol. 45(2), pages 243-256, July.
- Ziggy MacDonald, 2002. "Official Crime Statistics: Their Use and Interpretation," Economic Journal, Royal Economic Society, vol. 112(477), pages F85-F106, February.
- Gary S. Becker, 1974.
"Crime and Punishment: An Economic Approach,"
in: Essays in the Economics of Crime and Punishment, pages 1-54
National Bureau of Economic Research, Inc.
- Nuno Garoupa & Daniel Klerman, 2002. "Optimal Law Enforcement with a Rent-Seeking Government," American Law and Economics Review, Oxford University Press, vol. 4(1), pages 116-140, January.
- Marcel Boyer & Tracy R. Lewis & Wei Lin Liu, 2000.
"Setting standards for credible compliance and law enforcement,"
Canadian Journal of Economics,
Canadian Economics Association, vol. 33(2), pages 319-340, May.
- Marcel Boyer & Tracy Lewis & Wei Lin Liu, 1996. "Setting Standards for Credible Compliance and Law Enforcement," CIRANO Working Papers 96s-27, CIRANO.
- Davis, Michael L, 1988. "Time and Punishment: An Intertemporal Model of Crime," Journal of Political Economy, University of Chicago Press, vol. 96(2), pages 383-90, April.
- Mohamed Jellal & Nuno Garoupa, 1999. "Dynamic optimal law enforcement with learning," Economics Working Papers 402, Department of Economics and Business, Universitat Pompeu Fabra.
- Sah, R.K., 1990.
"Social Osmosis And Patterns Of Crime: A Dynamic Economic Analysis,"
609, Yale - Economic Growth Center.
- O'Flaherty, Brendan, 1998. "Why Repeated Criminal Opportunities Matter: A Dynamic Stochastic Analysis of Criminal Decision Making," Journal of Law, Economics and Organization, Oxford University Press, vol. 14(2), pages 232-55, October.
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