Smokeless tobacco product prices and taxation in Bangladesh: Findings from the International Tobacco Control Survey
Bibliographic record
Abstract
INTRODUCTION: Smokeless tobacco use occupies a significant portion of overall tobacco consumption in Bangladesh. Yet very little is known about the effectiveness of tax and price policy in controlling the use of smokeless tobacco use in the country. METHODS: The paper examines the price distribution of various smoked (cigarette, bidi) and smokeless tobacco products (zarda, gul) using the univariate Epanechnikov kernel density function. It estimates the own and cross price elasticity of demand for the most widely used smokeless tobacco product zarda using two-step regression analysis. The analysis is based on data from the ITC Bangladesh Wave 3 Survey which is a nationally representative cohort survey of tobacco users and nonusers conducted in in Bangladesh during 2011-12. RESULTS: The price elasticity of lower price brands of zarda is estimated at -0.64 and of higher priced brands at -0.39, and the cross price elasticity of zarda with respect to cigarette price at 0.35. The tax increase on smokeless tobacco needs to be greater than the tax increase on smoked tobacco to bridge the wide price differential between the two types of products that currently encourages downward substitution from smoked to smokeless tobacco and discourages quitting behavior. CONCLUSIONS: This paper argues that increasing tax on smokeless tobacco simultaneously with the tax increase on smoked tobacco can have significant negative impact on the prevalence of smokeless tobacco use in Bangladesh. Finally, a specific excise system replacing the existing ad valorem excise tax can substantially contribute to the revenue collection performance from smokeless tobacco products.
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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 | 0.001 | 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".