PRICES, INFLATION, AND SMOKING ONSET: THE CASE OF ARGENTINA
Bibliographic record
Abstract
This article examines the effect of tobacco prices on the decision to start smoking in Argentina. Argentina is an interesting case to explore given its high smoking rates, its recent experience with periods of very high and hyperinflation, and the mixed evidence of the effect of prices on smoking onset, particularly in low‐ and middle‐income countries. We used data from four cycles of two large national surveys conducted between 2005 and 2011 and discrete‐time hazard models. We found that tobacco prices had a statistically significant and fairly large impact on the hazard of smoking onset, and these findings were robust to alternative specifications. We also found that prices had little effect on the hazards of smoking onset during periods of hyper‐ and very high inflation, which provide some support for the notion that prices lose their informational role in such periods. Governments need to be cognizant that their most important policy tool to reduce tobacco use—taxes that increase real tobacco prices—is likely no longer effective during these times. (JELC41, H20, I12, I18)
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".