Do Changes In Cigarette Taxes Impact Youth Smoking? Evidence from Canadian Provinces
Bibliographic record
Abstract
Recent U.S. studies report much smaller youth smoking participation elasticities compared to research based on 1980s and 1990s data. We exploit the considerable time-series variation available within and across Canadian provinces. In particular, we study the dramatic (50%) reduction in cigarette excise taxes that occurred in February 1994 in most eastern provinces in Canada as well as significant increases within most provinces between 1994 and 2006. OLS and logit estimates from a variety of surveys suggest participation elasticities from 0.1 to 0.3 for teens aged 15 to 19 years, which are lower than traditional estimates. However, children aged 10 to 14 are significantly more tax elastic than older peers, with participation elasticities between -1.5 and -2. Finally, employing different sub-samples, we find that sharp hikes and reductions generate similar cigarette tax elasticities.
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".