855 results on '"Caulkins, Jonathan P."'
Search Results
2. Changing dynamics of drug overdoses in the United Kingdom: An attempt to replicate the Jalal et al. findings of steady exponential growth
3. When prohibition works: Comparing fireworks and cannabis regulations, markets, and harms
4. COVID-19 and Optimal Lockdown Strategies: The Effect of New and More Virulent Strains
5. Changes in self‐reported cannabis use in the United States from 1979 to 2022
6. Rating the comparative efficacy of state-level cannabis policies on recreational cannabis markets in the United States
7. Should drug use trends be studied holistically, or piece by piece?
8. How much demand for money laundering services does drug selling create? Identifying the key parameters
9. Responding to the opioid crisis in North America and beyond: recommendations of the Stanford–Lancet Commission
10. Community perspectives on supervised consumption sites: Insights from four U.S. counties deeply affected by opioids
11. Radical technological breakthroughs in drugs and drug markets: The cases of cannabis and fentanyl
12. Outcomes associated with scheduling or up-scheduling controlled substances
13. COVID-19 and Optimal Lockdown Strategies: The Effect of New and More Virulent Strains
14. The optimal lockdown intensity for COVID-19
15. Intensity of cannabis use: Findings from three online surveys
16. A detailed study of a prominent dark web fentanyl trafficking organization
17. Triangulating web & general population surveys: Do results match legal cannabis market sales?
18. A detailed study of a prominent dark web fentanyl trafficking organization.
19. Modeling cartel size to inform violence reduction in Mexico
20. Opioids of the Masses: Stopping an American Epidemic From Going Global
21. Assessing Costs and Benefits of Early Childhood Intervention Programs: Overview and Application to the Starting Early Starting Smart Program [with] Executive Summary.
22. An Ounce of Prevention, a Pound of Uncertainty: The Cost-Effectiveness of School-Based Drug Prevention Programs.
23. Big data on a big new market: Insights from Washington State’s legal cannabis market
24. Serious strategy for the makers of fun: Analyzing the option to switch from pay-to-play to free-to-play in a two-stage optimal control model with quadratic costs
25. Lanchester model for three-way combat
26. Dealing More Effectively and Humanely with Illegal Drugs
27. Dynamic Drug Policy: Optimally Varying the Mix of Treatment, Price-Raising Enforcement, and Primary Prevention Over Time
28. Using Models That Incorporate Uncertainty
29. Recognizing and regulating cannabis as a temptation good
30. Interaction of pricing, advertising and experience quality: A dynamic analysis
31. Optimal Dynamic Allocation of Treatment and Enforcement in Illicit Drug Control
32. Noticing the Micro-Distributional Consequences of Cigarette Taxation and Its Equivalents
33. Optimal Control of Drug Epidemics: Prevent and Treat -- But Not at the Same Time?
34. Systems Modeling to Inform Drug Policy: A Personal Odyssey
35. Limited Rationality and the Limits of Supply Reduction
36. Lessons to be Drawn from U.S. Drug Control Policies
37. Modeling the Domestic Distribution Network for Illicit Drugs
38. Differential Terror Queue Games
39. The virtues of bans on high‐THC content cannabis products?
40. Enforcement or Treatment? Modeling the Relative Efficacy of Alternatives for Controlling Cocaine
41. Modeling the structure and operation of drug supply chains: The case of cocaine and heroin in Italy and Slovenia
42. Optimal control of a terror queue
43. Economic Analysis and Policy Studies: Special Challenges in the Prevention Sciences
44. Capital stock management during a recession that freezes credit markets
45. Skiba points in free end-time problems
46. How much of the cocaine market are we missing? Insights from respondent-driven sampling in a mid-sized American city
47. How patterns of injecting drug use evolve in a cohort of people who inject drugs
48. Crime and Justice
49. How much illegally manufactured fentanyl could the U.S. be consuming?
50. Are users’ most recent drug purchases representative?
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