Structural change in Thailand’s tobacco leaf exports: Implications of tobacco control in ASEAN countries
Bibliographic record
Abstract
The purpose of this research is to investigate the implications of tobacco control policies and measure how these have brought about structural changes in Thailand’s tobacco leaf exports. The methodology involved employing secondary data to estimate the econometrics model and then utilizing the Chow test. The findings showed that the estimates from the econometrics model reflect the income elasticity of the real export value of 6.621. In the Chow test, a statistically significant (at 0.05) structural change in Thailand’s tobacco leaf export was apparent when comparing the results before and after the first quarter of 2010. Furthermore, since 2010 the exports have shifted from the old market to other ASEAN countries, namely Indonesia, the Philippines, Malaysia, and Lao PDR. Concerning the practical implications, from a public health perspective, the results provide evidence for the efficiency of tobacco control policies and measures in European countries, the US, and Australia. On the other hand, they also pinpoint an area of improvement for tobacco control policies in ASEAN countries, and further investigation is required. From an economic perspective, Thai tobacco farmers need to be supported by the government during the transition period.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".