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Record W342110783 · doi:10.15173/esr.v16i2.516

Ancillary Benefits of Carbon Mitigation: How Does it Affect Cost Effectiveness of the Annex-1 Emissions Trading?

2009· article· en· W342110783 on OpenAlexvenueno aff
Tsung-Chen Lee

Bibliographic record

VenueEnergy Studies Review · 2009
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicClimate Change Policy and Economics
Canadian institutionsnot available
Fundersnot available
KeywordsEmissions tradingBusinessMarginal costCost–benefit analysisNatural resource economicsEnvironmental economicsClean Development MechanismIntervention (counseling)Compliance (psychology)Marginal abatement costGreenhouse gasEconomicsMicroeconomics

Abstract

fetched live from OpenAlex

This paper explores how ancillary benefits of carbon mitigation may affect the cost effectiveness of Annex-1 emissions trading. We find that emissions trading could lead to cost-savings for both the Annex-1 countries as a whole and for the individual countries, as compared with the case of no-trading. The sum of the compliance costs is minimized under the cost-effective condition where marginal costs of domestic abatement are equalized across the Annex-1 countries. However, such a condition of cost effectiveness in emissions trading does not imply cost effectiveness in terms of the compliance of individual countries. The buyers of emission allowances, consisting of the European Union, the United States and Japan, could have even lower costs of compliance in the trading case where the ancillary benefits are taken into consideration. This result supports the intervention that takes account of the ancillary benefit in designing national carbon mitigation policies. To achieve the cost effectiveness in national carbon abatement, there should be regulatory interventions so that the price of carbon emission allowances can reflect the ancillary benefits.

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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.710
Threshold uncertainty score0.507

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.105
GPT teacher head0.298
Teacher spread0.193 · 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 teacher head, not a consensus.

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

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

Citations1
Published2009
Admission routes1
Has abstractyes

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