Would Plain Packaging and Health Warning Labels Reduce Smoking in the Presence of Informal Markets? A Choice Experiment in Colombia
Bibliographic record
Abstract
Despite progress made by many countries on the adoption of plain tobacco packaging laws over the last years, low- and middle-income countries, with a large supply of loose cigarettes via informal vendors, remain far behind. To study the potential effectiveness of plain tobacco packaging and dissuasive cigarette sticks, via willingness-to-pay estimates, when illicit cigarette options are available. We conducted a discrete choice experiment (DCE) in which respondents chose licit and illicit products with three attributes: packaging (standard vs. plain packaging), stick design (branded stick vs. stick with warning), and price level. The sample, collected on 12/2021, consisted of 1,761 respondents from an internet panel involving smokers and nonsmokers. Conditional logit and latent class models were used to estimate the willingness-to-pay (WTP) to avoid restrictive packaging elements. Nonsmokers are willing to pay USD $5.63 for a pack of cigarettes to avoid plain packaging, which is higher than the actual commercial price of illicit cigarettes (USD $2.40). The WTP increases to USD $12.14 in the presence of illicit alternatives. Smokers are also willing to pay to avoid illicit options, which they also deem riskier, and the presence of such options increases the WTP to avoid plain packaging. However, nonsmokers do not perceive the illicit option as riskier. The dissuasive stick (stick with warning) does not affect perceptions of risk and plays a small role in terms of choice for both smokers and nonsmokers. Even in the presence of illicit tobacco alternatives, plain packaging seems to be as effective in reducing the attractiveness of tobacco products in Colombia as in other countries that have already adopted it. Given conflicting results on the case for dissuasive sticks, there is a need for more research.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".