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Record W3125645315

Cannabis Countdown: Estimating the Size of Illegal Markets and Lost Tax Revenue Post-Legalization

2018· article· en· W3125645315 on OpenAlex
Anindya Sen, Rosalie Wyonch

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueC.D. Howe Institute Commentary · 2018
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsnot available
Fundersnot available
KeywordsBlack marketExciseTax revenueLegalizationSupply and demandRevenueBusinessEnforcementEconomicsPublic economicsEconomic policyMarket economyFinanceLawMicroeconomics
DOInot available

Abstract

fetched live from OpenAlex

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

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.191
Threshold uncertainty score0.535

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.012
GPT teacher head0.288
Teacher spread0.275 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it