Cross-Country Comparison of the Incentives of the EU Emission Trading Scheme for Replacing Existing Power Plants in 2008–12
Bibliographic record
Abstract
In this paper, we conduct a cross-country quantitative analysis of the replacement incentives generated by the EU Emission Trading Scheme (EU ETS) for the power sector in 2008–12. In order to do so, the allocation rules of the Member States are applied to concrete reference power plants for three different fuel types (lignite, hard coal and gas). Based on these calculations, we compare installation-specific replacement incentives across the Member States. Our analysis shows that replacement incentives vary significantly across Member States and typically deviate from the incentives provided in the reference case of full auctioning. Furthermore, the EU ETS allocation rules lead to perverse incentives in approximately 30% of the possible replacement options. Only 5 MS do not provide any perverse incentives. Finally, we explore the link between replacement incentives and allocation types. Based on our findings, we derive policy recommendations for the design of emission trading schemes emerging around the world.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".