Trends in beverage prices following the introduction of a tax on sugar-sweetened beverages in Barbados
Bibliographic record
Abstract
A 10% excise tax on sugar sweetened beverages (SSBs) was implemented in Barbados in September 2015. A national evaluation has been established to assess the impact of the tax. We present a descriptive analysis of initial price changes following implementation of the SSB tax using price data provided by a major supermarket chain in Barbados over the period 2014-2016. We summarize trends in price changes for SSBs and non-SSBs before and after the tax using year-on-year mean price per liter. We find that prior to the tax, the year-on-year growth of SSB and non-SSB prices was very similar (approximately 1%). During the quarter in which the tax was implemented, the trends diverged, with SSB price growth increasing to 3% and that of non-SSBs decreasing slightly. The growth of SSB prices outpaced non-SSBs prices in each quarter thereafter, reaching 5.9% compared to <1% for non-SSBs. Future analyses will assess the trends in prices of SSBs and non-SSBs over a longer period and will integrate price data from additional sources to assess heterogeneity of post-tax price changes. A continued examination of the impact of the SSB tax in Barbados will expand the evidence base available to policymakers worldwide in considering SSB taxes as a lever for reducing the consumption of added sugar at the population level.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".