Estimating Price Elasticity for Tobacco in Canada’s Aboriginal Communities; Job Market Paper, 2010. Available online: http://works.bepress.com/cgi/viewcontent.cgi?article= 1003&context =matheson (accessed on 31
Bibliographic record
Abstract
Exploiting a repeated cross-section created from the 1991 and 2001 waves of the Aboriginal Peoples Survey, I provide the first estimates of tobacco price elasticity for adults in Canada’s Aboriginal communities. These communities are small and secluded, presenting a unique opportunity to look at the potential influence of community smoking norms on individual behavior. Specifically, I allow aggregate smoking behavior within the community to influence individual smoking behavior. I distinguish between two price effects: the direct effect, reflecting individual reaction to a price change; and the indirect effect, whereby price influences the individual by changing community smoking behavior. I find the indirect effect doubles the price elasticity over the direct effect alone. I also find the discouraging effect of taxes on smoking to be significantly less than previously hypothesized. A 10 percent increase in prices leads to a 0.73 percentage point decrease in daily smoking, a 1.39 percentage point decrease in occasional smoking, and does not significantly affect smoking intensity among daily smokers. I conclude that taxation is an effective tool for revenue creation but a largely ineffective tool for adult health policy.
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 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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".