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Record W3124132495 · doi:10.3386/w17376

Embodied Carbon Tariffs

2011· preprint· en· W3124132495 on OpenAlexaff
Christoph Böhringer, Jared C. Carbone, Thomas F. Rutherford

Bibliographic record

VenueNational Bureau of Economic Research · 2011
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicClimate Change Policy and Economics
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCarbon leakageGreenhouse gasEconomicsComputable general equilibriumEmbodied cognitionCarbon taxInternational economicsScope (computer science)Global warmingClimate policyClimate changeInternational tradeNatural resource economicsMacroeconomics

Abstract

fetched live from OpenAlex

In a world where the prospects of a global agreement to control greenhouse gas emissions are bleak, the idea of using trade policy as an implicit regulation of foreign emission sources has gained many supporters in countries contemplating unilateral climate policies.Embodied carbon tariffs tax the direct and indirect carbon emissions embodied in imported goods.The appeal seems obvious: as OECD countries are, on average, large net importers of embodied emissions from non-OECD countries, carbon tariffs could substantially extend the reach of OECD climate policies.We investigate this claim by simulating the effects of embodied carbon tariffs with a computable general equilibrium model of global trade and energy use.We find that embodied carbon tariffs do effectively reduce carbon leakage.However, the scope for improvements in the global cost-effectiveness of unilateral climate policy is limited.The main welfare effect of the tariffs is to shift the burden of OECD climate policy to the developing world.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.025
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0250.002

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 head0.667
GPT teacher head0.484
Teacher spread0.183 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations33
Published2011
Admission routes1
Has abstractyes

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