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A Resource-Constrained Optimal Control Model for Crackdown on Illicit Drug Markets


Author Info

  • Baveja, A.
  • Feichtinger, G.
  • Hartl, R.F.
  • Haunschmied, J.L.
  • Kort, P.M.

    (Tilburg University, Center for Economic Research)


In 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 Info

Paper provided by Tilburg University, Center for Economic Research in its series Discussion Paper with number 1999-85.

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Date of creation: 1999
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Handle: RePEc:dgr:kubcen:199985

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Keywords: crackdown enforcement; illicit drug markets; optimal control;

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  1. 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.
  2. Baveja, Alok & Caulkins, Jonathan P. & Liu, Wensheng & Batta, Rajan & Karwan, Mark H., 1997. "When haste makes sense: Cracking down on street markets for illicit drugs," Socio-Economic Planning Sciences, Elsevier, vol. 31(4), pages 293-306, December.
  3. 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.
  4. Baveja, Alok & Batta, Rajan & Caulkins, Jonathan P. & Karwan, Mark H., 1993. "Modeling the response of illicit drug markets to local enforcement," Socio-Economic Planning Sciences, Elsevier, vol. 27(2), pages 73-89, June.
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Cited by:
  1. Serge-Christophe Kolm, 2011. "Inequality, new directions: full ethical foundation and consequences," Journal of Economic Inequality, Springer, vol. 9(3), pages 329-352, September.
  2. 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.
  3. 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.
  4. 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.
  5. 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.
  6. 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.


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