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Record W2769822109 · doi:10.1111/dar.12638

Alcohol taxes’ contribution to prices in high and middle‐income countries: Data from the International Alcohol Control Study

2017· article· en· W2769822109 on OpenAlexfundno aff
Martin Wall, Sally Casswell, Sarah Callinan, Surasak Chaiyasong, Phạm Việt Cường, Gaile Gray‐Phillip, Charles Parry

Bibliographic record

VenueDrug and Alcohol Review · 2017
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsnot available
FundersCenter for Alcohol StudiesMedical Research CouncilSouth African Medical Research CouncilMassey UniversityInternational Development Research CentreHealth Promotion AgencyThai Health Promotion FoundationAustralian National Preventive Health Agency
KeywordsPurchasing power parityEconomicsConsumption (sociology)Optimal taxAd valorem taxPublic economicsExciseInternational economicsTax reformMonetary economicsMicroeconomicsMacroeconomics

Abstract

fetched live from OpenAlex

INTRODUCTION: Taxation is increasingly being used as an effective means of influencing behaviour in relation to harmful products. In this paper we use data from six participating countries of the International Alcohol Control Study to examine and evaluate their comparative prices and tax regimes. METHODS: We calculate taxes and prices for three high-income and three middle-income countries. The data are drawn from the International Alcohol Control survey and from the Alcohol Environment Protocol. Tax systems are described and then the rates of tax on key products presented. Comparisons are made using the Purchasing Power Parity rates. The price and purchase data from each country's International Alcohol Control survey is then used to calculate the mean percentage of retail price paid in tax weighted by actual consumption. RESULTS: Both ad valorem and specific per unit of alcohol taxation systems are represented among the six countries. The prices differ widely between countries even though presented in terms of Purchasing Power Parity. The percentage of tax in the final price also varies widely but is much lower than the 75% set by the World Health Organization as a goal for tobacco tax. CONCLUSION: There is considerable variation in tax systems and prices across countries. There is scope to increase taxation and this analysis provides comparable data, including the percentage of tax in final price, from some middle and high-income countries for consideration in policy discussion.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.636

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.068
GPT teacher head0.359
Teacher spread0.290 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations19
Published2017
Admission routes1
Has abstractyes

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