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.
To our knowledge, this item is not available for
download. To find whether it is available, there are three
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.
Volume (Year): 20 (2004)
Issue (Month): 1 (April)
|Contact details of provider:|| Postal: Oxford University Press, Great Clarendon Street, Oxford OX2 6DP, UK|
Fax: 01865 267 985
Web page: http://jleo.oupjournals.org/
|Order Information:||Web: http://www.oup.co.uk/journals|
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- 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.
- Mohamed Jellal & Nuno Garoupa, 1999. "Dynamic optimal law enforcement with learning," Economics Working Papers 402, Department of Economics and Business, Universitat Pompeu Fabra.
- Sah, Raaj K, 1991.
"Social Osmosis and Patterns of Crime,"
Journal of Political Economy,
University of Chicago Press, vol. 99(6), pages 1272-95, December.
- Sah, R.K., 1990. "Social Osmosis And Patterns Of Crime: A Dynamic Economic Analysis," Papers 609, Yale - Economic Growth Center.
- 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.
- 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, 1968.
"Crime and Punishment: An Economic Approach,"
Journal of Political Economy,
University of Chicago Press, vol. 76, pages 169.
- 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.
- 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.
- 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.
- 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.
When requesting a correction, please mention this item's handle: RePEc:oup:jleorg:v:20:y:2004:i:1:p:192-206. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Oxford University Press)or (Christopher F. Baum)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.