Faculty Details

Photo of Jonathan P. Caulkins

Jonathan P. Caulkins

H. Guyford Stever Professorship of Operations Research and Public Policy

Full-time Faculty

Voice: n/a
Email: caulkins@andrew.cmu.edu
View curriculum vitae (.pdf)

Biography

Jon Caulkins has been on the Heinz School faculty since 1990, with leaves of absence to be co-director of RAND’s Drug Policy Research Center in Santa Monica (1994-1996), to found RAND’s Pittsburgh Office (1999-2001), and to teach at Carnegie Mellon’s campus in Doha, Qatar (2005-2011). At the Heinz School he was director of the Masters of Science in Public Policy and Management (MSPPM) program and served as interim Associate Dean for Faculty. He did his undergraduate work in engineering and computer science at Washington University in St. Louis. He earned masters degrees in Systems Science and Mathematics (Washington University, 1987) and Electrical Engineering and Computer Science (MIT, 1989) and a Ph.D. in Operations Research (MIT, 1990).

Caulkins serves or has served on the editorial board of Management Science, Operations Research, Mathematical and Computer Modelling, the Journal of Drug Issues, Socio-Economic Planning Sciences, and I/S: A Journal of Law and Policy for the Information Society, and has refereed for over 85 different journals.

Honors

  • Barash Lecturer, Purdue University, 2012
  • Plenary speaker, EURO, 2012
  • British Medical Association, Best Public Health Book of the Year (co-author), 2010
  • INFORMS President’s Award, 2010
  • INFORMS Fellow, 2010
  • H. Guyford Stever Chair of Operations Research, 2010
  • IFORS Distinguished Lecturerat APORS, 2009
  • National Academy of Engineering’s Frontiers of Engineering, 2008
  • Robert Wood Johnson Foundation Health Investigator Award, 2006
  • INFORMS Plenary speaker at ORPA-1 Conference in Ouagadougou, 2005
  • Marschak Colloquium at UCLA, 2001
  • Pittsburgh’s Forty Under Forty Award, 2000
  • David N. Kershaw Award, Association for Public Policy Analysis & Management, 1999
  • Carnegie Mellon University Heinz School Martcia Wade Teaching Award, 1999
  • National Young Investigator, 1993 – 1999

Teaching

Caulkins has taught decision making, mathematical, and spreadsheet modeling on four continents to students from over 50 countries, including those at the Heinz School (masters students in public policy, medical management, biotechnology management, healthcare policy, information systems, and network security) and elsewhere, including undergraduates in mathematics at the Vienna Technical University, business and computer science students at Carnegie Mellon’s Qatar campus, and PhD students at the RAND Graduate School, as well as executive education for Carnegie Mellon (CIO Institute) and Harvard (Crime and Drug Policy).

Books and Monographs

Caulkins, Jonathan P., Angela Hawken, Beau Kilmer and Mark A.R. Kleiman (2012).  Marijuana Legalization: What Everyone Needs to Know.Oxford University Press.

Kleiman, Mark A.R., Jonathan P. Caulkins, and Angela Hawken (2011).  Drugs and Drug Policy: What Everyone Needs to Know.  Oxford University Press.

Thomas Babor, Jonathan Caulkins, Griffith Edwards, David Foxcroft, Keith Humphreys, Maria Medina Mora, Isidore Obot, Jurgen Rehm, Peter Reuter, Robin Room, Ingeborg Rossow, and John Strang.  2010.  Drug Policy and the Public Good.  Oxford University Press.

Grass, Dieter, Jonathan P. Caulkins, Gustav Feichtinger, Gernot Tragler, and Doris Behrens. 2008. Optimal Control of Nonlinear Processes: With Applications in Drugs, Corruption, and Terror.  Springer.

Caulkins, Jonathan P., Rosalie Pacula, Susan Paddock, and James Chiesa. 2002. School-Based Drug Prevention: What Kind of Drug Use Does it Prevent? MR-1459-RWJ. RAND, Santa Monica, CA.

Caulkins, Jonathan P., Jay Cole, Melissa Hardoby, and Donna Keyser. 2002. Intelligent Giving: Insights and Strategies for Higher Education Donors. MR-1427-CAE. RAND, Santa Monica, CA.

Gill, Brian P., Jake Dembosky, Caulkins, and Jonathan P. 2002. A “Noble Bet” in Early Childcare and Education: Lessons from One Community’s Experience. MR-1544. RAND, Santa Monica, CA.

Karoly, Lynn A., M. Rebecca Kilburn, James H. Bigelow, Jonathan P. Caulkins, and Jill Cannon. 2000. Assessing Costs and Benefits of Early Childhood Intervention Programs: Overview and Application to the Starting Early Starting Smart Program. MR-1336-CFP. RAND, Santa Monica, CA.

Caulkins, Jonathan P., C. Peter Rydell, Susan S. Everingham, James Chiesa, and Shawn Bushway. 1999. An Ounce of Prevention, a Pound of Uncertainty: The Cost-Effectiveness of School-Based Drug Prevention Program MR-923-RWJ, RAND, Santa Monica, CA.

Caulkins, Jonathan P., C. Peter Rydell, William L. Schwabe, and James Chiesa. 1997. Mandatory Minimum Drug Sentences: Throwing Away the Key or the Taxpayers’ Money? MR-827-DPRC, RAND, Santa Monica, CA.

Articles Published in Refereed Journals (2010 – present)

Caulkins, Jonathan P., Gustav Feichtinger, Dieter Grass, Richard F. Hartl, Peter M. Kort, Andrea Seidl (forthcoming). When to Make Proprietary Software Open Source.  Journal of Economic Dynamics and Control.

Caulkins, Jonathan P., Gustav Feichtinger, Dieter Grass, Richard F. Hartl, Peter M. Kort, Andreas J. Novak, Andrea Seidl (forthcoming). Leading Bureaucracies to the Tipping Point: An Alternative Model of Multiple Stable Equilibrium Levels of Corruption.  European Journal of Operations Research. 225: 541-546, Doi:10.1016/j.ejor.2012.10.026.

Paddock, Susan M., Beau Kilmer, Jonathan P. Caulkins, Marika J. Booth and Rosalie L. Pacula (2012). An Epidemiological Model for Examining Marijuana Use over the Life Course.  Epidemiology Research International. Article ID: 520894.  Doi:10.1155/2012/520894. PMCID: PMC3518305.

Caulkins, Jonathan P., Gustav Feichtinger, Richard F. Hartl, Peter M. Kort, Andreas J. Novak, Andrea Seidl (forthcoming).  Multiple Equilibria and Indifference-Threshold Points in a Rational Addiction Model.  Central European Journal of Operations Research.

Caulkins, Jonathan P., Anna Kasunic, and Michael A.C. Lee (2012).  Marijuana Legalization: Lessons from the 2012 State Proposals.  World Medical and Health Policy.  4(3):4-34.

Caulkins, Jonathan P.; Coulson, Carolyn C.; Farber, Christina; and Vesely, Joseph V. (2012) Marijuana Legalization: Certainty, Impossibility, Both, or Neither?, Journal of Drug Policy Analysis, 5(1):1-27.

Strang, John, Thomas Babor, Jonathan P. Caulkins, Benedikt Fischer, David Foxcroft, and Keith Humphreys (2012). Drug Policy and the Public Good: evidence for effectivenss of interventions.  Lancet. 379(9810):71-83.

Coulson, Carolyn and Jonathan P. Caulkins (2012).  Scheduling of Newly Emerging Drugs:  A Critical Review of Decisions Over 40 Years.Addiction.  107(4):766-773.

Caulkins, Jonathan P. and Brittany Bond (2012).  Marijuana Price Gradients: Implications for Exports and Export-Generated Tax Revenue for California After Legalization.  Journal of Drug Issues.  42(1):28-45.

Caulkins, Jonathan P., Beau Kilmer, Robert J. MacCoun, Rosalie Liccardo Pacula, and Peter Reuter.  2012.  Design Considerations for Legalizing Cannabis: Lessons Inspired by Analysis of California’s Proposition 19.  Addiction. 107(5): 865-871 (Response to commentaries also published as pp.876-877.

Caulkins, Jonathan P., Peter Reuter, and Carolyn Coulson.  2011.  Basing Scheduling Decisions on Scientific Rankings of Drugs’ Harmfulness: False Promise from False Premises.  Addiction.  106: 1886-1890 (Response to commentaries also published.)

Caulkins, Jonathan P. and Carolyn Coulson (2011).  To Schedule or not to Schedule: How Well Do We Decide? Journal of Global Drug Policy and Practice.  5(4).

Kilmer, Beau, Jonathan P., Caulkins, Rosalie Liccardo Pacula, and Peter Reuter.  2011.  Bringing Perspective to Illicit Markets: Estimating the Size of the U.S. Marijuana Market.  Drug and Alcohol Dependence. 119, 153-160.

Caulkins, Jonathan P., Gustav Feichtinger, Dieter Grass, Richard F. Hartl, Peter M. Kort, and Andrea Seidl.  2011. Optimal Pricing of a Conspicuous Product During a Recession that Freezes Capital Markets.  Journal of Economic Dynamics and Control.  35:163-174.

Zeiler, Irmgard, Jonathan P. Caulkins, and Gernot Tragler.  2011.  Optimal Control of Interacting Systems with DNSS Property: The Case of Illicit Drugs.  Journal of Economic Behavior and Organizations, 78:60-73.  DOI: 10.1016/j.jebo.2010.12.008.

Reuter, Peter, Rosalie Liccardo Pacula, and Jonathan P. Caulkins.  2011.  RAND’s Drug Policy Research Center. Addiction. 106(2):253-259. DOI: 10.1111/j.1360-0443.2010.03017.x.

Caulkins, Jonathan P. (2011). The Global Recession’s Effect on Drug Demand – Diluted by Inertia.  International Journal of Drug Policy, 22:374-375.  doi:10.1016/j.drugpo.2011.02.005.

Zeiler, Irmgard, Jonathan P. Caulkins, Dieter Grass, and Gernot Tragler.  2010.  Keeping Options Open: an Optimal Control Model with Trajectories that Reach a DNSS Point in Positive Time.  SIAM Journal on Control and Optimization.  48(6):3698-3707.

Caulkins, Jonathan P. and Robert L. DuPont.  2010. Is 24/7 Sobriety a Good Goal for Repeat DUI Offenders? Addiction.  105:575-577.

Caulkins, Jonathan P. and David Baker.  2010. Cobweb Dynamics and Price Dispersion in Illicit Drug Markets.  Socio-Economic Planning Sciences.  44(4): 220-230.  doi:10.1016/j.seps.2010.06.001.

Caulkins, Jonathan P. 2010.  Might Randomization in Queue Discipline Be Useful When Waiting Cost is a Concave Function of Time?  Socio-Economic Planning Sciences. 44:19-24, DOI: 10.1016/j.seps.2009.04.001.

Caulkins, Jonathan P., Richard F. Hartl, and Peter M. Kort.  2010.  Delay Equivalence in Capital Accumulation Models. Journal of Mathematical Economics.  46: 1243-1246.  DOI:10.1016/j.jmateco.2010.08.021.

Caulkins, Jonathan P. and Nancy Nicosia.  2010. What Economics Can Contribute to the Addiction Sciences.  Addiction, 105(7):1156-1163. DOI: 10.1111/j.1360-0443.2010.02915.x.

Gallupe, Owen, Martin Bouchard, and Jonathan P Caulkins.  2010. No change is a good change? Restrictive deterrence in illegal drug markets.  Journal of Criminal Justice. 39:81-89 doi:10.1016/j.jcrimjus.2010.12.002.

Caulkins, Jonathan P., Gustav Feichtinger, Gernot Tragler, and Dagmar Wallner.   2010.  “When in a Drug Epidemic Should the Policy Objective Switch from Use Reduction to Harm Reduction.”  European Journal of Operational Research.  Vol. 201, 301-318. DOI: 10.1016/j.ejor.2009.03.015.

Chapters in Edited Volumes Published (2010 – present)

Caulkins, Jonathan P. and Beau Kilmer (2013).  Criminal Justice Costs of Prohibiting Marijuana in California.  In Something’s in the Air: Race and the Legalization of Marijuana, eds. Katherine Tate, James Lance Taylor, and Mark Q. Sawyer.  Routledge.

Caulkins, Jonathan P., Anna Kasunic, and Michael A.C. Lee (forthcoming).  Estimating the Societal Burden of Substance Abuse: Advantages and Limitations of Current Methodologies.  In Substance Abuse in Adolescents and Young Adults: A Critical Conundrum for Society, eds. Donale E. Greydanus, Gabriel Kaplan, Dilip Patel, and Joav Merrick.

Caulkins, Jonathan P., Anna Kasunic, Mark A.R. Kleiman, and Michael A.C. Lee (forthcoming).  The Pros and Cons of Legalization.  In Substance Abuse in Adolescents and Young Adults: A Critical Conundrum for Society, eds. Donale E. Greydanus, Gabriel Kaplan, Dilip Patel, and Joav Merrick.

Lievens, Delfine, Freya Vander Laenen, Jonathan Caulkins, and Brice De Ruyer.  Drugs in Figures III: Study of Public Expenditures on Drug Control and Drug Problems.  In European Criminal Justice and Policy, eds. Marc Cools, Brice De Ruyer, Marleen Easton, Lieven Pauwels, Paul Ponsaers, Gudrun Vande Walle, Tom Vander Beken, Freya Vander Laenen, Antoinette Verhage, Gert Vermeulen, and Gerwinde Vynckier.  Maklu Publishers, pp.41-64.

Caulkins, Jonathan P. and Mark A.R. Kleiman (2011).  Drugs and Crime.  In Oxford Handbook of Crime and Criminal Justice, ed. Michael Tonry. Oxford University Press, pp.275-320.

Boyum, David, Jonathan P. Caulkins, and Mark A.R. Kleiman (2011).  Drugs, Crime, and Public Policy.  In Crime and Public Policy, eds. James Q. Wilson and Joan Petersilia. Oxford University Press, pp.368-410.

Reuter, Peter H. and Jonathan P. Caulkins (2011).  Purity, Price, and Production: Are Drug Markets Different?  In Illicit Trade and Globalization, ed. Paul De Grauwe. MIT Press.

Caulkins, Jonathan P. and Peter Reuter (2010).  How Drug Enforcement Affects Drug Prices.  In Crime and Justice – A Review of Research, vol. 39, ed. Michael Tonry. University of Chicago Press, pp.213-272.

Caulkins, Jonathan P., Vasundhara Garg, and Victor Pontines (2010)  Benefits of Including an Asian Currency Unit (ACU) in an Optimized World Currency Basket.  In Global Operations Management, Lee R. Hockley (Ed.), Nova Science Publishers, New York, pp.73-84.

Caulkins, Jonathan P. and Rosalie Liccardo Pacula. 2010.  Drug Policy Research.  In Addiction Research Methods, Peter G. Miller, John Strang, and Peter M. Miller (Eds.), Wiley-Blackwell Publishing, pp.355-371

RAND Publications (2010 – present)

Kilmer, Beau, Jonathan P. Caulkins, Rosalie Liccardo Pacula, and Peter Reuter (2012).  The U.S. Drug Policy Landscape: Insights and Opportunities for Improving the View.  RAND OP-393, Santa Monica, CA.

Kilmer, Beau, Jonathan P. Caulkins, Brittany M. Bond, and Peter Reuter (2010).  Reducing Drug Trafficking Revenues and Violence in Mexico: Would Legalizing Marijuana in California Help?  RAND OP-325-RC, Santa Monica, CA.

Kilmer, Beau, Jonathan P. Caulkins, Rosalie Liccardo Pacula, Robert MacCoun, Peter Reuter (2010).  Altered State? Assessing how marijuana legalization in California could influence marijuana consumption and public budgets.  RAND OP-315-RC, Santa Monica, CA.

Caulkins, Jonathan P., Eric Morris, and Rhajiv Ratnatunga (2010).  Smuggling and Excise Tax Evasion for Legal Marijuana.  RAND WR-766-RC, Santa Monica, CA, http://www.rand.org/pubs/working_papers/2010/RAND_WR764.pdf.

Bond, Brittany M. and Jonathan P. Caulkins (2010).  Potential for Legal Marijuana Sales in California to Supply Rest of U.S.  RAND WR-765-RC, Santa Monica, CA, http://www.rand.org/pubs/working_papers/2010/RAND_WR764.pdf.

Caulkins, Jonathan P. (2010).  Estimated Cost of Production for Legal Cannabis.  RAND WR-764-RC, Santa Monica, CA,http://www.rand.org/pubs/working_papers/2010/RAND_WR764.pdf.

Caulkins, Jonathan P. (2010).  Cost of Marijuana Prohibition on the California Criminal Justice System.  RAND WR-763-RC, Santa Monica, CA, http://www.rand.org/pubs/working_papers/2010/RAND_WR763.pdf.

Caulkins, Jonathan P., Sudha S. Rajderkar, and Shruti Vasudev.  2010.  Creating Price Series without Price Data: Harnessing the Power of Forensic Data.  Appendix A in B. Kilmer and S. Hoorens (Eds.) RAND TR-755-EC Understanding Illicit Drug Markets, Supply Reduction Efforts, and Drug-Related Crime in the European Union (pp.165-196).  Cambridge U.K.: RAND.

Other Professional Publications (2010 – present) 

Caulkins, Jonathan P. and Michael Lee.  2012.  Legalizing Drugs in the U.S.: A Solution to Mexico’s Problems for Which Mexico Should Not Wait.   Counter-Terror Operations,” in Ernesto Zedillo and Haynie Wheeler (eds.), Rethinking the “War on Drugs” Through the US-Mexico Prism, pp.108-124.

Hawken, Angela, Caulkins, Jonathan P., Beau Kilmer, and Mark A.R. Kleiman.  2013.  “Quasi-Legal Cannabis in Colorado and Washington: Local and National Implications.” Editorial in Addiction.

Caulkins, Jonathan P. and Beau Kilmer (with Marlon Graf).  2013.  Estimating the Size of the EU Cannabis Market.

Pacula, Rosalie Liccardo, Russell Lundberg, Jonathan P. Caulkins, Beau Kilmer, Sarah Greathouse, and Terry Fain. Forthcoming. Recommendations for Improving the Measurement of Drug-Related Crime.

Caulkins, Jonathan P. and Michael A.C. Lee.  2012.  The Drug-Policy Roulette.  National Affairs.  12, pp.35-51.

Caulkins, Jonathan P., Angela Hawken, Beau Kilmer, and Mark A.R. Kleiman.  2012.  Marijuana Legalization 2012 Style: The Brewing Conflict Between State and Local Laws.  American Interest.

Kleiman, Mark A.R., Jonathan P. Caulkins, and Angela Hawken.  2012.  Rethinking the War on Drugs.  Wall Street Journal.  Saturday Essay, April 20, 2012.

Kleiman, Mark A.R., Jonathan P. Caulkins, Angela Hawken, and Beau Kilmer.  2012.  Eight Questions for Drug Policy Research. Issues in Science and Technology.  Summer.  http://www.issues.org/28.4/kleiman.html.

Humphreys, Keith and Jonathan P. Caulkins.  2012.  Towards a smarter drugs policy.  The Guardian, January 6th (http://www.guardian.co.uk/commentisfree/cifamerica/2012/jan/06/towards-smarter-drugs-policy).

Kleiman, Mark, Jonathan Caulkins, and Angela Hawken.  2010.  Algo de lo que hay que saber sobre las drogas y nadie sabe ni pregunta ni puede responder.  Nexos, September 1st (downloaded from http://www.nexos.com.mx/?P=leerarticulo&Article=2099491 on October 8, 2011).

Caulkins, Jonathan P. Medical marijuana: The Justice Department speaks – again.  Christian Science Monitor, August 8th, 2011.www.csmonitor.com/Commentary/Opinion/2011/0808/Medical-marijuana-The-Justice-Department-speaks-again.

Caulkins, Jonathan P., Jonathan Kulick, and Mark A.R. Kleiman.  2011.  Think Again: The Afghan Drug Trade. Foreign Policy.

Caulkins, Jonathan P. (2012). The Term and the Vision (Comment on Victoria A. Greenfield and Letizia Paoli’s If supply-oriented drug policy is broken, can harm reduction help fix it?)  International Journal of Drug Policy. 23: 19-20.http://dx.doi.org/10.1016/j.drugpo.2011.07.006.

Caulkins, Jonathan P.  2011.  Can We Treat Our Way Out of Incarcerating Drug-Involved Offenders?  Comment on Pollack et al.’s If Drug Treatment Works So Well, Why Are So Many Drug Users In Prison?  In Phil Cook, Jens Ludwig, and Justin McCrary (eds.) Controlling Crime: Strategies and Tradeoffs, University of Chicago Press, Chicago, pp.160-65.

Caulkins, Jonathan P. and Eric Sevigny (2010).  The Effects of Drug Enforcement and Imprisonment on Source Countries: The Case of the U.S. and Mexico.  Appendix C to Cooperative Mexico-U.S. Antinarcotics Efforts, Sidney Weintraub and Duncan Wood, pp.99-127.  Center for Strategic and International Studies, Washington, DC.

Caulkins, Jonathan P., Mark A.R. Kleiman, and Jonathan Kulick.  2010.  Drug Production and Trafficking, Counterdrug Policies, and Security and Governance in Afghanistan.  New York University’s Center on International Coopertion, New York.

Beau Kilmer and Jonathan P. Caulkins (2010).  Filtering the Smoke: Legalizing Marijuana Would Slash the Price, But Effects On Use and Revenues Are Hazy.  RAND Review, 34(2). http://www.rand.org/publications/randreview/issues/summer2010/marijuana.html.

Beau Kilmer, Stijn Hoorens, and Jonathan P. Caulkins (2010).  Do Drug Arrests Work?  The Effectiveness of Drug Enforcement in Europe. RAND Review, 34(2).  www.rand.org/publications/randreview/issues/summer2010/arrest.html.

Caulkins, Jonathan P.  2010.  “Systems Modeling to Inform Drug Policy.”  Entry in Encyclopedia of Operations Research and Management Science, James J. Cochran (ed.).  Wiley.

Drugs and Public Policy Group (2010), Drug Policy and the Public Good: a summary of the book. Addiction, 105: 1137–1145. doi: 10.1111/j.1360-0443.2010.03049.x

Caulkins, Jonathan P., Gustav Feichtinger, Dieter Grass, and Gernot Tragler.  2010.  “Optimizing Counter-Terror Operations,” in Proceedings of the International Federation of Automatic Control 

Research Interest(s)


Modeling the effectiveness of interventions related to drugs, crime, violence, delinquency, and prevention

Education


B.S., Systems Science and Engineering, Computer Science, and Engineering & Policy, Washington University, 1987
M.S., Systems Science and Mathematics, Washington University, 1987
M.S., Electrical Engineering and Computer Science, M.I.T., 1989
PhD, Operations Research, Massachusetts Institute of Technology, 1990

Working Papers


Do Spreadsheet Errors Lead to Bad Decisions: Perspectives of Executives and Senior Managers

Spreadsheets are commonly used and commonly flawed, but it is not clear how often spreadsheet errors lead to bad decisions. We interviewed 45 executives and senior managers / analysts in the private, public, and non-profit sectors about their experiences with spreadsheet quality control and with errors affecting decision making. Almost all said spreadsheet errors are common. Quality control was usually informal and applied to the analysis and/or decision, not just the spreadsheet per se. Most respondents could cite instances of errors directly leading to bad decisions, but opinions differ as to whether the consequences of spreadsheet errors are severe. Some thought any big errors would be so obvious as to be caught by even informal review. Others suggest that spreadsheets inform but do not make decisions, so errors do not necessarily lead one for one to bad decisions. Still, many respondents believed spreadsheet errors were a significant problem and that more formal spreadsheet quality control could be beneficial.

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Drug Policy Research

Drug policy research is the application of policy analysis in the substance abuse domain with a level of rigor that merits publication in academic journals on the grounds that the methods and/or results can provide foundational insights upon which subsequent analyses might draw. Policy analysis in turn is an interdisciplinary field that strives to objectively and empirically understand the consequences of different public policy interventions, including both retrospective evaluation of past interventions and prospective projections of contemplated interventions. It is useful to distinguish three types of policy analysis:
1)Analysis of net effects on society as a whole (a "social planner’s perspective"),
2)Distributive analysis of effects on each significant group of stakeholders, and
3)Political analysis of what convergence of forces can push through a piece of legislation or other policy change.

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Optimal Timing of Use vs. Harm Reduction in an SA Model of Drug Epidemics

A debate in drug policy rankles between proponents of use reduction and harm reduction. This paper presents a stylized two-state, one-control dynamic optimization model of this choice based on a social cost related definition of harm reduction, and parameterize it both for cocaine in the U.S. and for Australia's population of injection drug users. Static analysis of a binary choice between pure harm reduction and pure use reduction suggests that whether or not harm reduction is a good strategy can depend on various factors such as the particular drug, the country, the social cost structure, or the stage of the "epidemic". The optimal dynamic control version of the model involves boundary solutions with respect to the control variable with several switches in the optimal policy. The results have interesting interpretations for policy. Even for the U.S. parameterization, harm reduction turns out to have a potential role when drug use is either already pervasive or when use is so rare that there is no danger of explosive increases in initiation, but perhaps not when drug use is near a "tipping point". In contrast, in the parameterization for Australian IDU, where effective harm reduction tactics exist and budgetary cost for harm reduction measures are small, harm reduction appears preferable starting from any initial state. Furthermore, an interesting feature of our simple model is the occurence of indifference curves, consisting of points where the decision maker is indifferent between two transients that will approach the same steady state in the long run. These transients result in the same social cost for the decision maker, but are characterized by quite different optimal policies.

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Understanding Inertia: Inherent Limitations on Evaluating "Upstream" Prevention Interventions

When different types of policy interventions are available, there is an understandable desire to evaluate all alternatives using common metrics so scare resources can be allocated in the most efficient manner. However, systems that display significant lags in their response to some interventions can confound such an empirical approach. This paper provides a parsimonious mathematical representation of some of the challenges confronted when trying to evaluate upstream interventions on lagged systems to help clarify when it is and when it is not practical to expect those interventions to meet the same standard of proof as downstream interventions. Implications for drug policy and delinquency prevention are elaborated.
 

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Implications of Inertia for Assessing Drug Control Policy: Why Upstream Interventions May Not Receive Due Credit

There is ongoing interest in assessing the effectiveness of various drug control strategies, including policy intended to reduce initiation and prevalence. Compartmental models of trajectories of drug use have been developed that demonstrate that drug "systems" display significant inertia; interventions on systems with high inertia can be difficult to evaluate. The implications of inertia are illustrated by combining a new empirically-derived model of national drug initiation with a compartment model of trends in illicit drug use parameterized for Australia.
 

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Is Objective Risk All That Matters When It Comes to Drugs?

Mokdad et al. (2004) estimate that each year in the United States, 435,000 people die from tobacco use, 85,000 from alcohol, and 17,000 from all illicit substances combined. Yet American public appears far more concerned about illegal drugs than it is about tobacco and alcohol use, driving expansions in control efforts far beyond that which is part and parcel of prohibition. The central thesis of this paper is that some of this mismatch in concern may stem from differences in the types of deaths created, with deaths associated with illicit drugs being, on average, "scarier" to the public than are the deaths associated with legal substances in a way that can be grounded in the risk perception and communication literatures. We summarize literature documenting that people care about more than actual death risk. Factors such as voluntariness, control, and familiarity also play a crucial role in determining the perceived risk of an event, and some of those factors seem to be more salient for the illicit drugs than for tobacco and alcohol. Social amplification of risk may also play a role in explaining these perceptions, but may not by itself be the full explanation.
 

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Might Randomization in Queue Discipline Be Useful When Waiting Cost is a Concave Function of Waiting Time?

This paper raises the question of whether some degree of randomization in queue discipline might be welfare enhancing in certain queues for which the cost of waiting is a concave function of waiting time, so that increased variability in waiting times may be good not bad for aggregate customer welfare. Such concavity may occur if the costs of waiting asymptotically approach some maximum (e.g., for patients seeking organ transplants who will not live beyond a certain threshold time) or if the customer incurs a fixed cost if there is any wait at all (e.g., for knowledge workers seeking a service or piece of information that is required to proceed with their current task, so any delay forces them to incur the "set up charge" associated with switching tasks).
 

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Cost-Benefit Analyses of Investments to Control Illicit Substance Abuse and Addiction

This paper gives an overview of what is known concerning illicit drug control interventions’ “return on investment” performance from a social planner’s perspective. It is organized by broad type of intervention (supply control, prevention, treatment, harm reduction, and integration across intervention types). The discussion is primarily US-centric, with somewhat greater reliance on international literature vis a vis harm reduction.

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Heroin and Methamphetamine Seizures in Victoria, Australia: Purity Changes Associated with the Heroin "Drought"

The Australian heroin "drought" was a singular event deserving of the considerable scholarly attention it has engendered. The best way to understand market disruption is to examine both supply and demand side indicators, yet data on the former have been relatively neglected. Here we explore a rich data set on heroin and methamphetamine purity from 1998-2002 in Victoria that support monthly and even fortnightly time series. These series show that the drought was characterized by abrupt and substantial declines in heroin purity (from ~40% to as low as 10-15%), but those steep declines followed an extended period of substantial erosion in purity (from 70-75% in early 1999 to ~40% by the end of 2000). Purity rebounded from its post-drought lows but far from completely, stabilizing at ~20% for 2002. The heroin purity declines do not appear to stem from “cutting” at lower market levels. The declines did increase the purity variability per pure unit of heroin. There was no comparable evidence of contemporaneous effects in the methamphetamine purity series.

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Incentive Stackelberg Strategies for a Dynamic Game on Terrorism

This paper presents a dynamic game model of international terrorism. The time horizon is finite, about the size of one presidency, or infinite. Quantitative and qualitative analysis of incentive Stackelberg strategies for both decision-makers of the game ("The West" and "International Terror Organization") allows statements about the possibilities and limitations of terror control interventions. Recurrent behavior is excluded with monotonic variation in the frequency of terror attacks whose direction depends on when the terror organization launches its terror war. Even optimal pacing of terror control operations does not greatly alter the equilibrium of the infinite horizon game, but outcomes from the West’s perspective can be greatly improved if the game is only "played" for brief periods of time and if certain parameters could be influenced, notably those pertaining to the terror organization’s ability to recruit replacements.

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Optimizing Counter-Terror Operations: Should One Fight Fire with "Fire" or "Water"?

This paper deals dynamically with the question of how recruitment to terror organizations is influenced by counter-terror operations. This is done within a optimal control model, where the key state is the (relative) number of terrorists and the key controls are two types of counter-terror tactics, one ("water") that does not one ("fire") that does provoke recruitment of new terrorists. The model is nonlinear and does not admit analytical solutions, but an efficient numerical implementation of Pontryagin’s Minimum Principle allows for solution with base case parameters and considerable sensitivity analysis. Generally this model yields two different steady states, one where the terror-organization is nearly eradicated and one with a high number of terrorists. Whereas water strategies are used at almost any time, it can be optimal not to use fire strategies if the number of terrorists is below a certain threshold.

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Using Integer Programming to Optimize Investments in Security Countermeasures: A Practical Tool for Fixed Budgets

Software engineers and businesses must make the difficult decision of how much of their budget to spend on software security mitigation for the applications and networks on which they depend. This article introduces a novel method of optimizing, using Integer Programming (IP), the combination of security countermeasures to be implemented in order to maximize system security under fixed resources. The article describes the steps involved in our approach, and discuss recent results with a case study client.
 

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Bifurcating DNS Thresholds in a Model of Organizational Bridge Building

A simple optimal control model is introduced, where "bridge building" positions are rewarded. The optimal solutions can be classified in regards of the two extern parameters, (1) costs for the control staying at such an exposed position and (2) the discount rate. A complete analytical description of the bifurcation lines in parameter space is derived, which separates regions with different optimal behavior. These are resisting the influence from inner and outer forces, always fall off from the boundaries or decide based on one’s initial state. This latter case gives rise to the emergence of so-called Dechert-Nishimura-Skiba (DNS) points describing optimal solution strategies. Furthermore the bifurcation from a single DNS point into two DNS points has been analyzed in parameter space. All these strategies have a funded interpretation within the limits of the model.

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Brand Image and Brand Dilution in the Fashion Industry

This paper develops dynamic optimal control model of a fashion designer's challenge of maintaining brand image in the face of short-term profit opportunities through expanded sales that risk brand dilution in the longer-run. The key state variable is the brand's reputation, and the key decision is sales volume. Depending on the brand's capacity to command higher prices, one of two regimes is observed. If the price mark-ups relative to production costs are modest, then the optimal solution may simply be to exploit whatever value can be derived from the brand in the short-run and retire the brand when that capacity is fully diluted. However, if the price markups are more substantial, then an existing brand should be preserved. It may even be worth incurring short-term losses while increasing the brand's reputation, even if starting a new brand name from scratch is not optimal.

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Can Housing Mobility Programs Make a Long-Term Impact on the Lives of Poor Families and the Health of Middle-Class Communities: A Policy Simulation

Housing mobility programs enable families living in high-poverty neighborhoods to relocate to lower- poverty neighborhoods using tenant-based subsidies. Recent research indicates that these programs improve participant outcomes on a number of economic and social outcomes. This paper applies policy simulation to a stylized representation of a housing mobility program to give a sense of scale and proportion for what a "full scale" mobility program might entail. Results indicate that this system model reaches steady-state fairly quickly, that rates of concentrated poverty decrease more quickly than those for system-wide poverty, consistent with the notion of a housing mobility program as primarily a tool for poverty deconcentration. Destination communities absorb a substantial number of mobility in- movers without suffering substantial adverse demographic impacts, indicating that the "carrying capacity" of these communities may sufficient to support large-scale mobility initiatives. Middle-class flight per mobility family is moderately high and almost independent of housing mobility program intensity; selected sprawl-related social costs are relatively small. Sensitivity analyses show that the model behaves in predictable ways in response to changes to structural parameters. A "worst-case" scenario of parameter values still generates modest poverty reductions with moderate levels of poverty in destination communities but very high rates of middle-class "flight".
 

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Explaining Fashion Cycles: Imitators Chasing Innovators in Product Space

This paper considers the problem of a fashion trend-setter confronting an imitator who can produce the same product at lower cost. A one- dimensional product space is considered, which is an abstraction of the key attribute of some consumer good. Three broad strategies can be optimal for the fashion-leader: (1) Never innovate; milk profits from the initially advantageous position but ulti- mately concede the market without a fight. (2) Innovate once but only once, which just temporarily defers conceding the market. (3) Cycle in- finitely around product space, never letting the imitator catch up and capture the market. Sometimes the cycles start immediately; sometimes the innovator should wait for a time before beginning the cycles. The optimal solution exhibits strong state-dependency, with so-called Skiba curves separating regions in state space where various of these strategies are optimal. There are even instances of intersecting Skiba curves. In most cases, analytical expressions can be stated that characterize these Skiba curves.

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High and Low Frequency Oscillations in Drug Epidemics

This paper extends the two-dimensional model of drug use introduced in Behrens et al. [1999, 2000, 2002] by introducing two additional states that model in more detail newly initiated ("light") users’ response to the drug experience. Those who dislike the drug quickly "quit" and briefly suppress initiation by others. Those who like the drug progress to ongoing ("moderate") use, from which they may or may not escalate to "heavy" or dependent use. Initiation is spread contagiously by light and moderate users, but is moderated by the drug’s reputation, which is a function of the number of unhappy users (recent quitters + heavy users). The model reproduces recent prevalence data from the U.S. cocaine epidemic reasonably well, with one pronounced peak followed by decay toward a steady state. However, minor variation in parameter values yields both long-run periodicity with a period akin to the gap between the first U.S. cocaine epidemic (peak ~1910) and the current one (peak ~1980), as well as short-run periodicity akin to that observed in data on youthful use for a variety of substances. The combination of short- and long-run periodicity is reminiscent of the elliptical burstors described by Rubin and Terman [2002]. The existence of such complex behavior including cycles, quasi periodic solutions, and chaos is proven by means of bifurcation analysis.
 

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How studies of the cost-of-illness of substance abuse can be made more useful for policy analysis

An elementary step in drug policy analysis is comparing the cost of an intervention to its benefit in the form of the social cost averted because of reduced drug use and associated consequences. One would think that cost of illness (COI) studies would provide a solid foundation for quantifying the benefits of reduced drug use, but at present they do not. This paper suggests ways the COI studies could be adapted to serve better policy analytic purposes.

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Illicit Drug Markets and Economic Irregularities

Markets for illicit drugs present an interesting case study for economics, combining non-standard characteristics such as addiction and product illegality. One response has been to argue the generality of economic principles by suggesting that they apply even in the extreme case of markets for addictive substances, e.g., by showing that demand for illicit goods is responsive to price [1] and even by modeling addiction as rational [2]. This paper sketches examples of an alternative reaction, focusing on idiosyncrasies of drug markets that might plausibly create counter-intuitive effects, including supply curves that slope downward because of enforcement swamping and/or a good serving as the only available store of wealth for its producer, demand reduction programs that increase demand, and consumption by “jugglers” possibly increasing rather than decreasing as prices rise. This analysis yields non-obvious policy recommendations; for example, source country control programs should concentrate on growing regions with a healthy banking sector.

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Long-Run Trends in Incarceration of Drug Offenders in the US

Estimates are developed for the number of people incarcerated in the US for drug-law violations between 1972-2002, broken down by type of institution (federal prison, state prison, or jail) and to the extent possible by nature of drug offense (possession/use, trafficking, or other). These time series are compared to trends in drug use indicators, revealing at best weak correlations, and the absolute levels are compared to different market indicators to draw various inferences. For example, even though about 480,000 people are incarcerated for drug-law violations, on average retail sellers spend less than two hours behind bars per sale. Still, full time sellers might expect to spend three months incarcerated per year of selling, suggesting that there are roughly four active drug sellers for every one who is incarcerated.

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Marijuana Markets: Inferences from Reports by the Household Population

Generally more is known about drug use and demand than about markets and supply, in large part because population survey data are available while market data are not. Although the household population represents a relatively small proportion of users of hard drugs, it represents a large proportion of the population using marijuana and participating in marijuana markets. This paper provides a description of marijuana market and acquisition patterns as reported by participants in the 2001 National Household Survey on Drug Abuse. We find that most respondents obtain marijuana indoors (87%), from a friend or relative (89%), and for free (58%). Retail marijuana distribution appears to be embedded in social networks, rather than being dominated by "professional" sellers. Despite these contrasts with stereotypical street markets for cocaine and heroin, there are also similarities, such as evidence of quantity discounts and a minority of users accounting for the majority of purchases. It is estimated that there are on the order of 400 million retail marijuana purchases in the U.S. each year and that the average purchase size is small, about 6-7 joints.
 

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Modelling the spread of hepatitis C via commercial tattoo parlours: Implications for public health interventions

Hepatitis C (HCV) is a serious infection caused by a blood-borne virus. It is a contagious disease spreading rapidly via a variety of transmission mechanisms including contaminated tattoo equipment. Effectively regulating commercial tattoo parlours can greatly reduce this risk. This paper models the cost-effectiveness and optimal timing of such interventions, and parameterizes the model with data for Vienna, Austria. This dynamic model of the contagious spread of HCV via tattooing and other mechanisms accounts for secondary infections and shows that regulation can be highly cost-effective.
 

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Operations Research & Public Policy for Africa: Harnessing the Revolution in Management Science Instruction

Operations research (OR) has made major contributions in the developed world to public policy domains that are of great relevance to Africa. Inasmuch as OR has failed to live up to its potential for addressing such issues in Africa, a principal barrier may have been distance between OR analysts and decision makers. However, the revolution in management science instruction and potential to train end user modelers has democratized OR. This makes training for policy makers and mangers in the public and non-profit sectors in Africa both feasible and highly beneficial. Existing Management Science courses for public and non-profit leaders, such as those that taught at Carnegie Mellon, could be adapted to fit the needs of educators and policy makers in Africa and disseminated via a “train the trainers” approach. A plan is sketched whereby 800,000 end-user modelers might be trained in Africa (1 for every 1,000 people) at an annual cost of about $5M per year. Such budgets are well within the range of investments in human capital formation currently being made in Africa.

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Price and Purity Analysis for Illicit Drug: Data and Conceptual Issues

Data on illicit drug purity and prices are invaluable but problematic. Purists argue they are unsuitable for economic analysis (Manski et al., 2001; Horowitz, 2001), but in reality they are used frequently (ONDCP 2001a, 2001b, 2004; Grossman, 2004). This paper reviews data and conceptual issues that people producing, analyzing, and consuming drug price and purity series should understand in order to reduce the likelihood of misinterpretation. It also identifies aspects of drug markets that are both poorly understood and relevant to some of these issues. They constitute a useful research agenda for health and law enforcement communities who would benefit from better data on the supply, availability, and use of illicit drugs.

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Spreadsheet Errors and Decision Making:

There is consensus in the literature that spreadsheets are both ubiquitous and error-prone, but little direct evidence concerning whether spreadsheet errors frequently lead to bad decision making. As part of research, 45 executives and senior managers/analysts in the private, public, and non-profit sectors were interviewed about their experiences with spreadsheet errors and quality control procedures. Differences across sectors do not seem pronounced. Almost all respondents report that spreadsheet errors are common. Most can report instances in which the errors directly led to losses or bad decisions, but opinions differ as to whether the consequences of spreadsheet errors are severe. Error checking and quality control procedures are in most cases informal. A significant minority of respondents believe such ad hoc processes are sufficient because the "human in the loop" can detect any gross errors. Others thought more formal spreadsheet quality control processes could be beneficial.
 

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The Need for Dynamic Drug Policy

Drug use in a population varies dramatically over time in no small measure due to nonlinear feedback among factors endogenous to the drug system. This suggests that drug policy ought likewise to be dynamic, varying the mix of strategies over time as drug use waxes and wanes. A growing literature that models drug "epidemics" mathematically supports this hypothesis and offers perspectives that may break policy logjams. For example, supply control may be most effective early, in the explosive growth stage of an epidemic. Conversely, treatment and measures to mitigate the consequences of dependent use and flagrant drug markets may have their comparative advantage later, in the endemic stage. Fully harnessing the power of dynamic drug policy will require more research and collection of new types of data, but the promise is worth the effort.
 

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Hidden Strategic Challenges Posed by Housing Mobility Policy: An Application of Dynamic Policy Modeling

Over the past decade, shifts in subsidized and affordable housing policy have led to a greater role for market dynamics and individual choice on the part of program participants and their new neighbors, and a greater awareness of the importance of neighborhood on family outcomes. Given these trends, there is an opportunity for innovative prescriptive planning models to assist in the design of policy related to regional housing mobility. The goal of this paper is to identify, and answer, some housing policy analytic questions with these models.

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Sell First Fix Later: Impact of Patching on Software Quality

This paper presents an economic model of fixing or patching a software problem after the product has been released in the market. Specifically, a software firm’s trade-off in releasing a buggy product early and investments in fixing it later is modelled. It is first shown that patching investments and time to enter the market are strategic complements such that higher investments in patching capability allow the firm to enter the market earlier. Just as the marginal cost of producing software can be effectively zero, so can be the marginal cost of repairing multiple copies of defective software by issuing patches. It is shown that due to the fixed cost nature of investments in patching, a vendor has incentives to release a buggier product early and patch it later in a larger market. This result is contrasted with other physical good markets. Thus, it is shown that a monopolist releases a product with fewer bugs but later than what is socially optimal. The model is extended to incorporate duopoly competition and show that in competition, the high value firm always enters earlier than the monopolist. Ironically the firm offering greater value to customers releases a product that initially is of lower quality (more bugs), but provides the greater value by releasing early (so customers can use the product sooner) and by investing more in patching so it can provide better after-sale support to its customers.
 

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A Model of Chaotic Drug Markets and Their Control

Drug markets are often described informally as being chaotic, and there is a tendency to believe that control efforts can make things worse, not better, at least in some circumstances. This paper explores the idea that such statements might be literally true in a mathematical sense by considering a discrete-time model of populations of drug users and drug sellers for which initiation into either population is a function of relative numbers of both populations. The structure of the system follows that considered in an arms control context by Behrens et al. (1997). In this context, the model suggests that depending on the market parameter values, the uncontrolled system may or may not be chaotic. Static application of either treatment or enforcement applied to a system that is not initially chaotic can make it chaotic and vice versa, but even if static control would create chaos, dynamic controls can be crafted that avoid it. So called OGY controls seem to work well for this example.

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A Model of Moderation: Finding Skiba Points on a Slippery Slope

A simple model is considered that rewards "moderation" - finding the right balance between sliding down either of two "slippery slopes". Optimal solutions are computed as a function of two key parameters: (1) the cost of resisting the underlying uncontrolled dynamics and (2) the discount rate. Analytical expressions are derived for bifurcation lines separating regions where it is optimal to fight to stay balanced, to give in to the attraction of the "left" or the "right", or to decide based on one’s initial state. The latter case includes situations both with and without so-called Dechert- Nishimura-Skiba (DNS) points defining optimal solution strategies. The model is unusual for having two DNS points in a one-state model, having a single DNS point that bifurcates into two DNS points, and for the ability to explicitly graph regions within which DNS points occur in the 2-D parameter space. The latter helps give intuition and insight concerning conditions under which these interesting points occur.

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An Age-Structured Single-State Initiation Model -- Cycles of Drug Epidemics and Optimal Prevention Programs

This paper introduces a mode for drug initiation that extends traditional dynamic models by considering explicitely the age distribution of the users. On the basis of a 2-groups model in which the population is split into a user and a non-user group the advantage of a continuous age distribution is shown by considering more details and by yielding new results. Neglecting death rates reduces the model to a single state (1-group) descriptive model which can still simulate some of the complex behavious of drug epidemics such as repeated cycles. Further more, prevention programs, especially school-based programs can be targeted to certain age classes. So in order to discover how best to allocate resources to prevention programs over different age classes we formulate and solve optimal control models.

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Counterterror and Counterdrug policies: Comparisons and Contrasts

Counterterror and Counterdrug policies: Comparisons and Contrasts

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Cycles of Violence: A Dynamic Control Model

This paper introduce and analyze a simple model of cycle of violence in which oscillations are generated when surges in lethal violence shrink the pool of active violent offenders. Models with such endogenously induced variation may help explain why historically observed trends in violence are generally not well correlated with exogenous forcing functions, such as changes in the state of the economy. The analysis includes finding the optimal dynamic trajectory of incarceration and violence prevention inteverventions. Those trajectories yield some surprising results, including situations in which myopic decision makers will invest more in prevention than will far-sighted decision makers.
 

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Drug Policy: Insights from Mathematical Analysis

Illicit drug use is clearly an important health problem. There are some 600,000 emergency department episodes in the US every year that are related to illicit drugs (SAMHSA, 2002a). National mortality estimates are not available, but there are probably on the order of 20,000 drug-induced deaths a year (SAMHSA, 2002b), with many more indirectly related to drug use. Some 5 million Americans are in need of drug treatment, and less than 40% get it (Epstein and Gfroerer, 1998; Woodward et al., 1997). Injection drug use is a leading cause of the spread of infectious diseases such as HIV/AIDS and Hepatitis C (CDCP, 2001). The social costs of illicit drug use approach those of alcohol and tobacco (Rice et al., 1990; Bartlett et al., 1994; Harwood et al., 1998). No one has estimated how many quality adjusted life years are lost due to illicit drug use, but the number is no doubt substantial, particularly since those who die from illicit drug use are younger than those who die from most other causes. Not surprisingly there is an energetic debate concerning how best to control drug use and related consequences, to which Operations Research/Management Science has made important contributions. Nevertheless, drug policy is unlike other health policy domains in important ways, and this article begins with a review of some important differences. The following sections then highlight key insights quantitative models have generated concerning the relative effectiveness of different interventions, including how that effectiveness varies over the course of a drug epidemic.
 

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Estimating the Relative Efficiency of Various Forms of Prevention at Different Stages of a Drug Epidemic

Drug use and problems change dramatically over time in ways that are often described as reflecting an "epidemic cycle". We use simulation of a model of drug epidemics to investigate how the relative effectiveness of different types of prevention varies over the course of such an epidemic. Specifically we use the so-called LHY model (see Behrens et al., 2000b) which includes both "contagious" spread of initiation (a positive feedback) and memory of past use (a negative feedback), which dampens initiation and, hence, future use. The analysis confirms the common sense intuition that prevention is more highly leveraged early in an epidemic, although the extent to which this is true in this model is striking, particularly for campaigns designed to leverage awareness of the drug’s dangers. The findings also suggest that the design of "secondary" prevention programs should change over the course of an epidemic.

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The Dynamic Character of Drug Problems

This paper makes three points. (1) Drug-related measures, such as the number of users, have changed rapidly over time, suggesting that they are not merely symptoms of underlying trends in the economy, demographics, or other aggregates that change more slowly. (2) Drug markets are subject to a wide range of feedback effects that can induce non-linearity into dynamic behavior. (3) There are at least five classes of epidemic models that reflect such non-linear dynamic behavior. Some of those classes tend to be optimistic about the ability of drug control interventions to reduce use; others are pessimistic. It is hoped that this discussion and, in particular, the typology, can inform and elevate the debate about drug policy, but it is unlikely to resolve that debate because of the inability to demonstrate empirically which class(es) are most accurate.

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Distinguishing Between Effects of Criminality and Drug Use on Violent Offending

The alarming increase in lethal violence among young people in the U.S.-which is often attributed to drug use and drug trafficking-has prompted re-examination of the relationship between drugs and violent offending. While no national data exist, numerous local studies find a high prevalence of homicide deaths among identified drug addicts, a high prevalence of substance use-typically alcohol-among victims of homicide, and a high proportion of persons testing positive for drug use among arrestees for violent offenses. Other studies report large increases in drug-related homicides or other violence associated with drug distribution. In a departure from previous research that contrasts users and nonusers of drugs, or compares broad periods of heavy and light drug use during long addiction careers, the present study attempts to isolate more direct effects of drug use near the time of offending. The data are for a sample of adults arrested in Washington, DC from July 1, 1985 to June 30, 1986, and include their longitudinal arrest histories along with the results of urine drug screens administered following arrest.

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How Large Should the Strike Zone Be in "Three Strikes and You're Out" Sentencing Laws?

So-called "three strikes and you’re out" sentencing laws for criminal offenders have proliferated in the United States in the 1990s. The laws vary considerably in their definitions of what constitutes a "strike". This paper adapts the classic Poisson Process model of criminal offending to investigate how varying sentence lengths and definitions of what constitutes a strike affect the effectiveness and cost-effectiveness of these sentencing laws. In particular, it asks whether by using different definitions for the first, second, and third strikes or different sentence lengths, one can make the resulting incarceration more "efficient" in the sense of incapacitating more crimes per cell-year served.
 

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How Effective is Micro Harm Reduction in Reducing Macro Harm?

MacCoun (1996) distinguishes between micro and macro harm reduction and notes that reducing micro harm (harm per unit of use) may or may not reduce macro (aggregate) harm depending on its effect on use. We present a simple model that relates micro and macro harm through five parameters: price, quantity, elasticity of demand, elasticity of supply, and the social cost of drug use. Parameterizing the relationship for the US cocaine market in 1992 suggests that about 75% of the apparent benefit of reducing micro harm experienced by users would be offset by increases in use. This suggests that reducing micro harm experienced by users has merit but that reducing the costs drugs impose on non-users may merit greater attention, since reducing those costs carries no risk of being offset by increases in use.
 

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How Should Low-Level Drug Dealers Be Punished?

The US pursues a number of drug control strategies, but the it invests the most resources in arresting, prosecuting, and incarcerating low-level drug dealers. Thus, it is important to reflect on what is the appropriate and expedient punishment for these offenders. Currently punishments vary from nothing to very long prison sentences; substantial variation is appropriate because not all low-level dealers are equally destructive. Unfortunately the current system does not punish most severely the most culpable offenders. A stronger correlation between severity of sanction and culpability could be achieved by: (1) moving decisions concerning length of incarceration from the state level to the local level, (2) reducing minimum sanction severity to expand the variation between minimum and maximum sanctions for all defendants except those who meet locally established definitions of what constitutes unusually destructive forms of dealing, and (3) allowing judges to depart from presumptive sentences instead of computing sentence length from fixed formulas based on readily observable - but only marginally relevant - criteria such as quantity possessed. The goal would be to allow police, prosecutors, and judges to work together to identify and target long sentences on the minority of most vicious dealers. This would serve the interests of justice, by making the punishment better fit the crime, and efficiency, by making more effective use of scarce and expensive punishment capacity.
 

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Adjusting GPA to Reflect Course Difficulty

The computation of Graduate Point Average (GPA) incorrectly assumes that grades are comparable across courses and instructors. GPA overstates the performance of students who elect an "easier" course of study relative to those who choose a more "difficult" course of study. This paper proposes a method of adjusting GPA and applies it to data from one cohort of undergraduates at Carnegie Mellon University. Adjusted GPAs are more highly correlated with students’ high school Grade Point Average and with SAT scores than are the raw GPAs or GPAs adjusted using a prominent alternative method, Item Response Theory. A survey of students finds that the new methods’ estimates of relative course difficulty are consistent with students’ perceptions of relative course difficulty.
 

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Estimating Elasticities of Demand for Cocaine and Heroin with Data from the Drug Use Forecasting System

Estimating Elasticities of Demand for Cocaine and Heroin with Data from the Drug Use Forecasting System

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ONDCP's First Four Years as a Policy Agency

ONDCP's First Four Years as a Policy Agency

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