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Record W2031876440 · doi:10.1142/s0219198912500168

STRATEGIC EFFECTS OF A BORDER TAX ADJUSTMENT

2012· article· en· W2031876440 on OpenAlex
Terry Eyland, Georges Zaccour

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

VenueInternational Game Theory Review · 2012
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicClimate Change Policy and Economics
Canadian institutionsGroup for Research in Decision AnalysisBishop's UniversityHEC Montréal
Fundersnot available
KeywordsCarbon taxWelfareEconomicsEnvironmental taxInternational economicsCarbon leakagePublic economicsBusinessInternational tradeClimate policyGreenhouse gasTax reformMarket economy

Abstract

fetched live from OpenAlex

Carbon leakage and competitiveness concerns are some of the main reasons why an international environmental agreement is lacking to fight climate change. Many studies discussed the adoption of a border tax adjustment (BTA) to allow countries that would like to implement a carbon tax to level the playing field with imports. The big drawback from these studies is that the other country is not allowed to react by adopting itself a carbon tax to avoid being punished with the BTA. The model proposed in this paper looks at the optimization of two different governments and their respective firms. Parametric values inside the set [0, 1) are used to represent the possible extents of the BTA depending on both countries environmental policy allowing countries to have different carbon policies. The result that a BTA parameter of 0.5 yields the highest total welfare could increase its acceptance within the World Trade Organization (WTO).

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.768
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0030.001

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 head0.084
GPT teacher head0.316
Teacher spread0.231 · 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