Price elasticity of illegal versus legal cannabis: a behavioral economic substitutability analysis
Bibliographic record
Abstract
Abstract Background and Aims The evolving legal status of cannabis world‐wide necessitates evidence‐based regulatory policies to minimize risks associated with cannabis misuse. A prominent concern is the impact legalization may have on the illegal cannabis market, including whether illegal cannabis will serve as a substitute for legal cannabis. Empirical data on this issue are virtually non‐existent. This study used behavioral economics to investigate substitutability of legal and illegal cannabis in legalized catchment areas in the United States. Design A substitution‐based marijuana purchase task assessed estimated cannabis consumption from concurrently available legal (a dispensary) and illegal (a dealer) sources. Prices of the two options were reciprocally either held constant ($10/gram) or escalated ($0–$60/gram). Setting US states with legalized recreational cannabis. Participants Adult cannabis users who were at least 21 years old ( n = 724; mean age = 34.13; 52% female; 74% Caucasian) were recruited using online crowdsourcing. Measurements Mean consumption values were used in demand curve modeling to generate indices of price sensitivity and elasticity. Differences in demand indices were compared using extra sums‐of‐squares F ‐tests. Findings Both legal and illegal fixed‐price cannabis options had significant positive cross‐price elasticities ( P s < 0.001), indicating that higher prices motivate substitution irrespective of legality. However, the presence of a legal alternative had a substantially greater effect on consumption and elasticity of illegal cannabis (∆ elasticity = 0.0019; F (1,37) = 160, P < 0.0001) than the presence of an illegal alternative on demand for legal cannabis (∆ elasticity = 0.0002; F (1,37) = 48, P < 0.0001), indicating asymmetric substitution. Demand for legal cannabis was significantly greater than for illegal cannabis ( P < 0.0001). Conclusions Cannabis users treat legal cannabis as a superior commodity compared with illegal cannabis and exhibit asymmetric substitutability favoring legal product. Cannabis price policies that include somewhat higher consumer costs for legal cannabis relative to contraband (but not excessively higher costs) would not be expected to incentivize and expand the illegal market.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".