Cost–benefit analysis involving addictive goods: contingent valuation to estimate willingness‐to‐pay for smoking cessation
Why this work is in the frame
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Bibliographic record
Abstract
The valuation of changes in consumption of addictive goods resulting from policy interventions presents a challenge for cost-benefit analysts. Consumer surplus losses from reduced consumption of addictive goods that are measured relative to market demand schedules overestimate the social cost of cessation interventions. This article seeks to show that consumer surplus losses measured using a non-addicted demand schedule provide a better assessment of social cost. Specifically, (1) it develops an addiction model that permits an estimate of the smoker's compensating variation for the elimination of addiction; (2) it employs a contingent valuation survey of current smokers to estimate their willingness-to-pay (WTP) for a treatment that would eliminate addiction; (3) it uses the estimate of WTP from the survey to calculate the fraction of consumer surplus that should be viewed as consumer value; and (4) it provides an estimate of this fraction. The exercise suggests that, as a tentative first and rough rule-of-thumb, only about 75% of the loss of the conventionally measured consumer surplus should be counted as social cost for policies that reduce the consumption of cigarettes. Additional research to estimate this important rule-of-thumb is desirable to address the various caveats relevant to this study.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 it