When Cigarette Sales Suddenly Become Illegal: Evidence From an Online Survey of South African Smokers During COVID-19 Lockdown
Bibliographic record
Abstract
INTRODUCTION: Despite high levels of illicit trade in the tobacco market, the South African government banned the sale of tobacco products in March 2020 as part of its COVID-19 response. The ban lasted five months. We assess how the ban affected the cigarette market for a sample of smokers by comparing the price, consumption, and competitive landscapes before (March), during (May and June), and after (September) the ban. METHODS: We conducted three online surveys of cigarette smokers, asking about smoking behavior before, during, and after the ban. We use descriptive statistics and OLS regressions to estimate the impact of the ban on the South African cigarette market, focusing on the price of cigarettes. RESULTS: Most smokers continued smoking despite the sales ban. During the ban, prices increased by over 240%. Purchases shifted away from the normally dominant brands of the multinational tobacco companies to local/regional producers. The covariates of price changed substantially during the sales ban, the most pronounced being inter-provincial effects. After the ban, the market shifted back to its preban state, with an overall increase in price of 3.6%. CONCLUSIONS: Cigarette sales continued despite the sales ban, further entrenching an already large illicit market. Had the government substantially increased the excise tax, rather than banned the sale of tobacco products, it would have achieved a similar public health outcome, received more revenue, and presumably not further entrenched the illicit market. IMPLICATIONS: South Africa temporarily banned the sale of tobacco as part of its COVID-19 response. Despite the ban, the sale of cigarettes did not cease; rather, it caused major disruption to the cigarette market. The ban inadvertently benefited manufacturers who were previously disproportionately involved in illicit activities; these manufacturers increased their market share even after the ban was lifted. The ban may have further entrenched South Africa's already large illicit market. Our results show that there are unintended consequences associated with a temporary ban on the sale of cigarettes.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".