Highlights
- Availability of indicators to estimate the illegal cannabis market is limited.
- Uncertainty is inherent in estimates of the size of illegal cannabis markets.
- Models are valuable to assess the size and uncertainty of illegal market estimates.
- Between 171 and 965 tons (95% IE of 271 to 613 tons) of Dutch cannabis is produced.
- Between 53 and 937 tons (95% IE of 206 to 573 tons) of Dutch cannabis is exported.
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 to 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 to 78 tons or 32 to 49 tons respectively). The export was estimated to
be between 53 and 937 tons (95% IE of 206 to 549 tons or 231 to 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% to 93% of the variation found. Further research should focus on
improving the variables and the independence of the mathematical models.
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