Bibliographic record
Abstract
We explore the tax revenue consequences of legalizing recreational cannabis in Canada. We build, calibrate, and simulate a two-level nested demand model in which legal and illegal cannabis are differentiated products and that incorporates econometric estimates of critical parameters. First, we find that sales tax and excise tax revenues accruing from legalization may be fully offset by declines in revenues from alcohol and tobacco. Second, and in contrast to excise and sales tax revenue, new revenue will accrue from personal income and corporate profits taxes. Using some available information on the wage structure of cannabis-producing corporations and imposing a Pareto distribution on incomes within the industry, we obtain an estimate of personal income tax revenues. To compute corporate profits tax revenue, we use priors on labour and capital shares and simulate the results of assumptions of debt leverage. We also estimate the private dollar value of legalization to individuals using a utility function approach. Per user, our results suggest a value roughly equal to $500 per annum. The results of this study may carry over to high-sin-tax economies contemplating legalization.
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.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".