Price and Income Elasticities of Cigarette Smoking Demand in Bangladesh: Evidence from Urban Adolescents and Young Adults
Bibliographic record
Abstract
INTRODUCTION: Understanding the elasticities of cigarette smoking demand among the youth could help improve the effectiveness of tobacco control interventions. The objective of this study is to measure the price and income elasticities of cigarette smoking demand among urban Bangladeshi male adolescents and young adults aged 10-24 years. METHOD: Using data from a cross-sectional survey conducted in seven urban districts of Bangladesh, we applied probit and ordinary least square (OLS) models to examine the effect of price and income on smoking participation (decision to smoke) and intensity (number of cigarettes smoked). RESULTS: Our results showed that price was not significantly associated with the decision to smoke, while income was a significant determinant of smoking participation. Both price and income determined the smoking intensity. The positive income elasticity (0.39) indicated that participants with greater access to money were more likely to participate in cigarette smoking and smoked more cigarettes. Negative price elasticity (-0.62) implied that increasing prices could lead to a reduction in smoking intensity among adolescents and young adults in urban Bangladesh. CONCLUSION: The inelastic price demand for cigarette smoking suggests that there is scope for increasing tax on cigarettes without compromising the tax revenue. IMPLICATIONS: This is the first study to investigate price and income elasticities among urban adolescents and young adults in Bangladesh. The study found no evidence that increasing the price of cigarettes discourages smoking participation but did show that increasing the price reduces the intensity of smoking among existing smokers. The results also suggest that economic measures such as taxation that increase the price of cigarettes could be a useful policy tool to limit smoking intensity without compromising government tax revenue.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".