Do Public Smoking Bans have an Impact on Active Smoking? Evidence from the UK
Bibliographic record
Abstract
The literature on the effects of public smoking bans on smoking behaviour presents conflicting results and there is limited evidence on their impact on active smoking. This paper evaluates the impact of smoking bans on active smoking using data from the British Household Panel Survey and exploiting the policy experiment provided by the differential timing of the introduction of the bans in Scotland and England. We assess the short-term impact of the smoking bans by employing a series of flexible difference-in-differences fixed effects panel data models. We find that the introduction of the public smoking bans in England and Scotland had limited short-run effects on both smoking prevalence and the total level of smoking. Although we identify significant differences in trends in smoking consumption across the survey period by population sub-groups, we find insufficient evidence to conclude that these were affected by the introduction of the smoking bans. These results challenge those found in the public health literature but are in line with the most recent strand of economic literature indicating that there is no firm evidence on the effects of smoking bans on smoking.
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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 | 0.005 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 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) | 0.010 | 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".