Dependence Structure among Carbon Markets around the World: New Evidence from GARCH-Copula Analysis
Bibliographic record
Abstract
In this paper, we investigate the dependence structure among carbon markets globally through different copulas. The analysis examines the relationship between carbon prices being traded across different emission trading systems (ETS) worldwide. The novelty of our approach lies in assessing carbon allowances for both futures and spot prices across all the key carbon markets as well as the three Chinese carbon markets for the period from 2011 to 2019 for future prices and the period from 2015 to 2020 for spot prices. The results demonstrate an asymmetric relationship between most carbon markets. A low tail dependence was observed between the European Union ETS and Regional Greenhouse Gas Initiative ETS, California and Quebec carbon markets, while higher tail dependence was found in the Asian carbon markets. Furthermore, carbon markets that have linkage agreements, ongoing cooperation or are geographically close tend to have positive and higher tail dependence. Our findings suggest the formation of regional carbon clubs based on the dependence structure.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".