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Record W2128013496 · doi:10.1016/s2214-109x(15)70095-1

The consequences of tobacco tax on household health and finances in rich and poor smokers in China: an extended cost-effectiveness analysis

2015· article· en· W2128013496 on OpenAlex
Stéphane Verguet, Cindy L. Gauvreau, Sujata Mishra, Mary MacLennan, Shane Murphy, Elizabeth Brouwer, Rachel Nugent, Kun Zhao, Prabhat Jha, Dean T. Jamison

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Lancet Global Health · 2015
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsUniversity of TorontoCentre for Global Health ResearchSt. Michael's Hospital
FundersUniversity of WashingtonBill and Melinda Gates Foundation
KeywordsExciseTax revenuePrice elasticity of demandPopulationChinaRevenueEconomicsPublic economicsEnvironmental healthMedicineGeographyFinance

Abstract

fetched live from OpenAlex

BACKGROUND: In China, there are more than 300 million male smokers. Tobacco taxation reduces smoking-related premature deaths and increases government revenues, but has been criticised for disproportionately affecting poorer people. We assess the distributional consequences (across different wealth quintiles) of a specific excise tax on cigarettes in China in terms of both financial and health outcomes. METHODS: We use extended cost-effectiveness analysis methods to estimate, across income quintiles, the health benefits (years of life gained), the additional tax revenues raised, the net financial consequences for households, and the financial risk protection provided to households, that would be caused by a 50% increase in tobacco price through excise tax fully passed onto tobacco consumers. For our modelling analysis, we used plausible values for key parameters, including an average price elasticity of demand for tobacco of -0·38, which is assumed to vary from -0·64 in the poorest quintile to -0·12 in the richest, and we considered only the male population, which constitutes the overwhelming majority of smokers in China. FINDINGS: Our modelling analysis showed that a 50% increase in tobacco price through excise tax would lead to 231 million years of life gained (95% uncertainty range 194-268 million) over 50 years (a third of which would be gained in the lowest income quintile), a gain of US$703 billion ($616-781 billion) of additional tax revenues from the excise tax (14% of which would come from the lowest income quintile, compared with 24% from the highest income quintile). The excise tax would increase overall household expenditures on tobacco by $376 billion ($232-505 billion), but decrease these expenditures by $21 billion (-$83 to $5 billion) in the lowest income quintile, and would reduce expenditures on tobacco-related disease by $24·0 billion ($17·3-26·3 billion, 28% of which would benefit the lowest income quintile). Finally, it would provide financial risk protection worth $1·8 billion ($1·2-2·3 billion), mainly concentrated (74%) in the lowest income quintile. INTERPRETATION: Increased tobacco taxation can be a pro-poor policy instrument that brings substantial health and financial benefits to households in China. FUNDING: Bill & Melinda Gates Foundation and Dalla Lana School of Public Health.

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.

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)0.002
metaresearch head score (Gemma)0.000
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 score0.025
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.099
GPT teacher head0.408
Teacher spread0.309 · 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