A Resource-Constrained Optimal Control Model for Crackdown on Illicit Drug Markets
AbstractIn this paper we present a budget-constrained optimal control model aimed at finding the optimal enforcement profile for a street-level, illicit drug crackdown operation. The objective is defined as minimizing the number of dealers dealing at the end of the crackdown operation, using this as a surrogate measure of residual criminal activity. Analytical results show that optimal enforcement policy will invariably use the budget resources completely. Numerical analysis using realistic estimates of parameters shows that crackdowns normally lead to significant results within a matter of a week, and if they do not, it is likely that they will be offering very limited success even if pursued for a much longer duration. We also show that a ramp-up enforcement policy will be most effective in collapsing a drug market if the drug dealers are risk-seeking, and the policy of using maximum enforcement as early as possible is usually optimal in the case when the dealers are risk averse or risk neutral. The work then goes on to argue that the underlying model has some general characteristics that are both reasonable and intuitive, allowing possible applications in focussed, local enforcement operations on other similar illegal activities.
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Bibliographic InfoPaper provided by Tilburg University, Center for Economic Research in its series Discussion Paper with number 1999-85.
Date of creation: 1999
Date of revision:
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Web page: http://center.uvt.nl
crackdown enforcement; illicit drug markets; optimal control;
Other versions of this item:
- Baveja, A. & Feichtinger, G. & Hartl, R.F. & Haunschmied, J.L. & Kort, P.M., 2000. "A resource-constrained optimal control model for crackdown on illicit drug markets," Open Access publications from Tilburg University urn:nbn:nl:ui:12-84066, Tilburg University.
- C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
- K42 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - Illegal Behavior and the Enforcement of Law
This paper has been announced in the following NEP Reports:
- NEP-ALL-1999-11-08 (All new papers)
- NEP-IND-1999-11-08 (Industrial Organization)
- NEP-LAW-1999-11-08 (Law & Economics)
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.:
- Caulkins, Jonathan P. & Larson, Richard C. & Rich, Thomas F., 1993. "Geography's impact on the success of focused local drug enforcement operations," Socio-Economic Planning Sciences, Elsevier, vol. 27(2), pages 119-130, June.
- Kort, P.M. & Feichtinger, G. & Hartl, R.F. & Haunschmied, J.L., 1996. "Optimal Enforcement Policies (Crackdowns) on a Drug Market," Discussion Paper 1996-29, Tilburg University, Center for Economic Research.
- Gopalan, Ram & Narayan, Bindu, 2010. "Improving customer experience in tourism: A framework for stakeholder collaboration," Socio-Economic Planning Sciences, Elsevier, vol. 44(2), pages 100-112, June.
- Yunker, James A., 2012. "Estimated optimal drug law enforcement expenditures based on U.S. annual data," Journal of Policy Modeling, Elsevier, vol. 34(3), pages 356-371.
- Kaya, C. Yalcin, 2004. "Time-optimal switching control for the US cocaine epidemic," Socio-Economic Planning Sciences, Elsevier, vol. 38(1), pages 57-72, March.
- Serge-Christophe Kolm, 2011. "Inequality, new directions: full ethical foundation and consequences," Journal of Economic Inequality, Springer, vol. 9(3), pages 329-352, September.
- Redmond, Michael & Baveja, Alok, 2002. "A data-driven software tool for enabling cooperative information sharing among police departments," European Journal of Operational Research, Elsevier, vol. 141(3), pages 660-678, September.
- Bondarev, Anton, 2014. "Endogenous specialization of heterogeneous innovative activities of firms under the technological spillovers," Journal of Economic Dynamics and Control, Elsevier, vol. 38(C), pages 235-249.
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