A comparison of alternative methods for measuring cigarette prices
Bibliographic record
Abstract
BACKGROUND: Government agencies, public health organisations and tobacco control researchers rely on accurate estimates of cigarette prices for a variety of purposes. Since the 1950s, the Tax Burden on Tobacco (TBOT) has served as the most widely used source of this price data despite its limitations. PURPOSE: This paper compares the prices and collection methods of the TBOT retail-based data and the 2003 and 2006/2007 waves of the population-based Tobacco Use Supplement to the Current Population Survey (TUS-CPS). METHODS: From the TUS-CPS, we constructed multiple state-level measures of cigarette prices, including weighted average prices per pack (based on average prices for single-pack purchases and average prices for carton purchases) and compared these with the weighted average price data reported in the TBOT. We also constructed several measures of tax avoidance from the TUS-CPS self-reported data. RESULTS: For the 2003 wave, the average TUS-CPS price was 71 cents per pack less than the average TBOT price; for the 2006/2007 wave, the difference was 47 cents. TUS-CPS and TBOT prices were also significantly different at the state level. However, these differences varied widely by state due to tax avoidance opportunities, such as cross-border purchasing. CONCLUSIONS: The TUS-CPS can be used to construct valid measures of cigarette prices. Unlike the TBOT, the TUS-CPS captures the effect of price-reducing marketing strategies, as well as tax avoidance practices and non-traditional types of purchasing. Thus, self-reported data like TUS-CPS appear to have advantages over TBOT in estimating the 'real' price that smokers face.
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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 | 0.000 |
| 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) | 0.000 | 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".