Drug Trafficking Under Partial Prohibition: Evidence from Recreational Marijuana
Bibliographic record
Abstract
The use of marijuana is banned federally yet the substance will soon be available to 21% of the United States population under state laws. This regime of partial prohibition creates the potential for externalities created by states with legal markets. Indeed, a chief concern among local and national policy makers is the trafficking of marijuana produced legally in one state to other states. We measure, for the first time, this extent of this trafficking. We use a natural experiment: Oregon began allowing recreational marijuana sales on October 1, 2015, after Washington, its neighbor, began allowing sales on July 8, 2014. Using comprehensive administrative data on the universe of Washington sales, we find that Washington retailers along the Oregon border experienced a 41% decline in sales immediately following Oregon's market opening. Retailers along Washington's borders with Idaho and Canada experienced no such decline. The decline occurred equally across weekdays and weekends, and was largest among the largest transaction sizes, suggesting that drug trafficking, not drug tourism, was to blame. Our estimates suggest that 11.9% of the marijuana sold in Washington was trafficked out of the state before Oregon legalized and 7.5% remains trafficked today.
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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 | 0.004 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 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".