|Titre :||Estimating the production, consumption and export of cannabis: The Dutch case (2016)|
|Auteurs :||M. VAN DER GIESSEN ; M. M. J. VAN OOYEN-HOUBEN ; D. E. G. MOOLENAAR|
|Type de document :||Article : Périodique|
|Dans :||International Journal of Drug Policy (Vol.31, May 2016)|
|Article en page(s) :||104-112|
|Discipline :||MAR (Marché de la drogue / Drug market)|
Thésaurus TOXIBASECANNABIS ; PRODUCTION ; MARCHE DE LA DROGUE ; TRAFIC INTERNATIONAL ; CONSOMMATION ; MODELE STATISTIQUE
Background: Quantifying an illegal phenomenon like a drug market is inherently complex due to its hidden nature and the limited availability of reliable information. This article presents findings from a recent estimate of the production, consumption and export of Dutch cannabis and discusses the opportunities provided by, and limitations of, mathematical models for estimating the illegal cannabis market.
Methods: The data collection consisted of a comprehensive literature study, secondary analyses on data from available registrations (2012-2014) and previous studies, and expert opinion. The cannabis market was quantified with several mathematical models. The data analysis included a Monte Carlo simulation to come to a 95% interval estimate (IE) and a sensitivity analysis to identify the most influential indicators.
Results: The annual production of Dutch cannabis was estimated to be between 171 and 965 tons (95% IE of 271-613 tons). The consumption was estimated to be between 28 and 119 tons, depending on the inclusion or exclusion of non-residents (95% IE of 51-78 tons or 32-49 tons respectively). The export was estimated to be between 53 and 937 tons (95% IE of 206-549 tons or 231-573 tons, respectively).
Conclusion: Mathematical models are valuable tools for the systematic assessment of the size of illegal markets and determining the uncertainty inherent in the estimates. The estimates required the use of many assumptions and the availability of reliable indicators was limited. This uncertainty is reflected in the wide ranges of the estimates. The estimates are sensitive to 10 of the 45 indicators. These 10 account for 86-93% of the variation found. Further research should focus on improving the variables and the independence of the mathematical models.
|Domaine :||Drogues illicites / Illicit drugs|
|Affiliation :||Erasmus University Rotterdam, Rotterdam School of Management - Centre of Excellence in Public Safety Management, Rotterdam, The Netherlands|