Dynamic Law Enforcement

The main purpose of the project was to develop `dynamic` models of so-called `victimless crime` (like, e.g., illicit drug consumption, corruption), analyse these models (in particular with the powerful tools of nonlinear dynamical systems theory and optimal control theory), validate them with empirical data, and derive appropriate policy conclusions. Due to the richness of the models in the area of illicit drug consumption and the high interest of well- established international institutions such as the EMCDDA (European Monitoring Centre on Drugs and Drug Addiction, Lisbon, Portugal), RAND`s DPRC (Drug Policy Research Center, Santa Monica, CA, U.S.A.), or the UNDCP (United Nations International Drug Control Programme, Vienna, Austria), the main focus was on research in that particular area. Crucial throughout the project were international co-operations, in particular the one with Prof. Ph.D. Jonathan P. Caulkins (H. John Heinz III School of Public Policy and Management, Carnegie Mellon University, Pittsburgh, PA, U.S.A., and RAND) and those with the above-mentioned institutions. It is definitely justified to claim that a huge progress has been made in modelling drug use mathematically, where the main innovative aspect brought in by this project was to develop and analyse optimisation models of drug use that were `dynamic`, i.e. taking into account the fact that drug use - both in individual and aggregate terms - changes over time (cf. the notion of a `drug epidemic`). In the analysis of these models, drug control interventions such as prevention, treatment, and price-raising law enforcement were determined so as to minimise the discounted stream of the sum of social costs arising from drug use and the overall drug control budget over a given planning horizon. A straightforward - but still previously mostly ignored - policy recommendation from all these models is that optimal drug policy involves substantially varying the mix of interventions over time. The restricted space here does not allow going into details. To mention just one particular example, one of the many models investigated explains that when policy makers become aware of the existence of a new drug problem, they must decide whether to pursue a policy of moderating its growth or more aggressively attempt to `eradicate` the use of the new drug. For eradication to succeed, policy makers must have the political capital needed to obtain massive funding - even if the specific drug problem is still relatively small - and the will to do so, although they may never receive recognition for averting an epidemic that remained invisible to the public eye. Apart from a series of publications in top journals (like, e.g., Journal of Economic Dynamics and Control, Journal of Economics, Management Science, Mathematical Biosciences, Operations Research), this project has also produced Master Theses and Dissertations that received awards from the ÖGOR (Österreichische Gesellschaft für Operations Research). A workshop on "Dynamic Drug Policy" was held in Vienna in the final project year, which was attended by national and international experts; the proceedings of this workshop will appear in the UNDCP`s Bulletin on Narcotics, which is translated into five languages and will hence provide large dissemination of project- based research results. For details see http://www.eos.tuwien.ac.at/OR/research/EoC/.