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Record W7128642270 · doi:10.26180/5084668.v1

Short-run effects of a carbon tax

2017· article· W7128642270 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueMonash University · 2017
Typearticle
Language
FieldDecision Sciences
Topicdemographic modeling and climate adaptation
Canadian institutionsnot available
Fundersnot available
KeywordsCarbon taxWageRevenueTax revenueConsumption (sociology)Greenhouse gasCarbon fibersTax rate

Abstract

fetched live from OpenAlex

This paper presents estimates of short-run sectoral and economy-wide effects of the introduction of a carbon tax in Australia. The results are derived using an enhanced version of the ORANI multi-sectoral model of the Australian economy. We simulate the introduction of a carbon tax at a rate of 1991-92 $25 per tonne, designed to achieve the Toronto target of a 20 per cent reduction in carbon dioxide emissions below the 1988 level by 2005. We find that the macroeconomic impact would depend critically on the extent to which price rises flowed through into wage rates. Assuming fixed money wages, real GDP would be decreased by an estimated 0.9 per cent, and employment by 1.2 per cent. To maintain a given employment level in the face of the carbon tax would require a reduction in the foreign-currency-equivalent wage rate estimated at 2.8 per cent. This would also entail a decrease in the real wage rate (defined with respect to the consumption price deflator) of 2.8 per cent. Government could promote lower wage outcomes by returning the carbon tax revenue to the community through reductions in other taxes. Enhancements to ORANI used in this simulation include disaggregation of the fossil fuel sector and provision for carbon taxation.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.526
Threshold uncertainty score0.947

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0020.001
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 head0.055
GPT teacher head0.298
Teacher spread0.243 · 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