Cannabis Countdown: Estimating the Size of Illegal Markets and Lost Tax Revenue Post-Legalization
Bibliographic record
Abstract
With Canada ending the legal prohibition of recreational marijuana as of October 17, 2018, governments across the country have been mobilizing to tackle the many policy challenges. But there has been a lack of policy discussion on whether supply from existing authorized producers will be sufficient to meet expected demand. This Commentary contributes to the literature by estimating the size of the marijuana black market during the first year of legalization, October 2018 – September 2019. These estimates take into account legal-illegal price differences as well as the gap between market demand and available legal supply. Our results show that both pricing and supply shortages will contribute to maintaining the black market, resulting in lost tax revenues and a continued need to spend significant resources on law enforcement activities related to the market. Our projections indicate the size of the black market, including legal supply shortages, will be about 380 tonnes, or at least $2.5 billion during the first year of legalization. This further suggests that forgone government revenues based on the coordinated excise tax framework and GST/HST/QST could be about $800 million. This loss can be attributed to a shifting mix of black market activity and legal market supply shortages, depending on the legal price and availability of supply. Using midpoint estimates for demand, our supply projections indicate that at $9 per gram, 87 percent of the resulting tax loss would be attributed to the black market and the remaining 13 percent to supply shortage in the legal market. There are various options that Canadian governments could employ to reduce this potential loss. Provinces should ensure regulations facilitate a competitive and convenient legal retail market. The federal government should focus on ensuring that it does not impede production more than is necessary to protect public health so there will be enough legal marijuana to supply these retail outlets. In addition, the federal government and Health Canada should develop regulations for edible and concentrated marijuana products. These products are already available on the black market, providing it a significant competitive advantage since they will not be part of the legal regime, at least at first. While our results predict initial shortages in legal supply, the market should be able to adjust as time goes on; Consumers' Interests and Protection;Provincial Taxation and Budgets; Health Policy; Provincial Comparisons
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".