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Record W2750146189 · doi:10.1111/ecin.12490

PRICES, INFLATION, AND SMOKING ONSET: THE CASE OF ARGENTINA

2017· article· en· W2750146189 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEconomic Inquiry · 2017
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsMcMaster UniversityImpact
FundersOntario Ministry of Health and Long-Term CareInternational Development Research Centre
KeywordsEconomicsInflation (cosmology)HazardHyperinflationMonetary economicsHazard ratioEconometricsMonetary policyMedicine

Abstract

fetched live from OpenAlex

This article examines the effect of tobacco prices on the decision to start smoking in Argentina. Argentina is an interesting case to explore given its high smoking rates, its recent experience with periods of very high and hyperinflation, and the mixed evidence of the effect of prices on smoking onset, particularly in low‐ and middle‐income countries. We used data from four cycles of two large national surveys conducted between 2005 and 2011 and discrete‐time hazard models. We found that tobacco prices had a statistically significant and fairly large impact on the hazard of smoking onset, and these findings were robust to alternative specifications. We also found that prices had little effect on the hazards of smoking onset during periods of hyper‐ and very high inflation, which provide some support for the notion that prices lose their informational role in such periods. Governments need to be cognizant that their most important policy tool to reduce tobacco use—taxes that increase real tobacco prices—is likely no longer effective during these times. ( JEL C41, H20, I12, I18)

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)0.000
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 score0.007
Threshold uncertainty score0.174

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.057
GPT teacher head0.336
Teacher spread0.278 · 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