Widening the Price Gap: The Effect of The Netherlands’ 2020 Tax Increase on Tobacco Prices
Bibliographic record
Abstract
INTRODUCTION: The public health impact of a tobacco tax increase depends on the extent to which the industry passes the increase onto consumers, also known as tax-pass through. In 2020, the Netherlands announced tax increases aimed at increasing the retail price by €1 per 20 factory-made (FM) cigarettes and €2.50 per 50 g of roll-your-own (RYO) tobacco. This study examines the pass-through rate after the tax increase, and whether this differed by type of tobacco and brand segment. AIMS AND METHODS: Self-reported prices of 117 tobacco brand varieties (cigarettes = 72, RYO = 45) pre- and post-tax increases were extracted from the 2020 International Tobacco Control Netherlands Surveys (n = 2959 respondents). We calculated the tax pass-through rate per variant, examining differences between the type of tobacco and brand segments. RESULTS: On average, cigarette prices increased by €1.12 (SD = 0.49; 112% of €1) and RYO prices by €2.53 (SD = 0.60; 101% of €2.50). Evidence of differential shifting across segments was found, with evidence of overshifting in non-discount varieties. The average price of discount varieties increased by €0.20 less than non-discount varieties. Similarly, the net-of-tax price decreased in discount varieties (cigarettes = -€0.02; RYO = -€0.05), but increased in non-discount varieties (cigarettes = +€0.14; RYO = +€0.20). CONCLUSIONS: Despite the large tax increase, the industry increased prices in line with or above the required level. Through differential shifting, the price gap between discount and non-discount varieties has widened, which may reduce the public health impact of the tax increase. Measures aimed at reducing price variability should be strengthened in taxation policy, such as the European Tobacco Tax Directive (TTD). IMPLICATIONS: We found that the industry used differential shifting after a significant tobacco tax increase in the Netherlands. Prices increased more than required in higher-priced products, but not in lower-priced products. This pattern was found both for FM cigarettes and RYO tobacco. Through differential shifting, the industry undermines the potential public health impact of tobacco tax increases, by offering a relatively cheaper alternative, which discourages people to quit or reduce consumption. The revision of the European TTD provides an opportunity to address the widening price gap-both between and within product segments-across the European Union.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".