An Analysis of Alternative Emission Trading Strategies of Parties to the Kyoto Protocol
Bibliographic record
Abstract
This article analyzes the cost of Canada, Japan, and Western Europe of complying with the Kyoto Protocol and the possible revenues of Eastern Europe, Russia, and Ukraine in a set of scenarios, each of which reflecting one particular pattern of permit trading. One main focus was to investigate how a working Clean Development Mechanism (CDM) scheme may influence the market power of a possible cartel of “hot air” sellers. The results show that the compliance costs are significantly reduced with the availability of CDM and that these cost depend only weakly on the restrictions of the “hot air” supply. The greenhouse gas emission reductions of the trading scenarios are about 40% less than in a domestic measures only scenario. The analysis uses a modified version of the well-known MERGE model (Manne and Richels, 2004). Zusammenfassung Dieser Artikel analysiert die Kosten, die Japan, Kanada und Westeuropa infolge der Erfüllung ihrer Verpflichtungen gemäß dem Kyoto-Protokoll entstehen, sowie den möglichen Ertrag, den Osteuropa, Russland und die Ukraine aus dem Verkauf eines Teils ihrer Emissionszertifikate erlösen können. Für die Analyse werden verschiedene Szenarien angenommen, von denen jedes ein bestimmtes Muster des Emissionshandels widerspiegelt. Im Besonderen wurde der Einfluss eines funktionierenden CDM-Systems (Reduktionsgutschriften im Rahmen des “Clean Development Mechanism“) auf die Marktdominanz eines möglichen solchen Kartells untersucht. Die Resultate zeigen, dass die Kosten der Erfüllung der Kyoto-Verpflichtungen stark abnehmen, wenn Reduktionsgutschriften im Rahmen des CDM verfügbar sind, und dass diese Kosten nur schwach von (Selbst-) Beschränkungen der Anbieter abhängen. Die Treibhausgasemissionsreduktionen für die Emissionshandelsszenarien sind etwa 40 % geringer als in einem Szenario ohne Emissionshandel. In der Analyse wird das weithin bekannte MERGE-Modell verwendet (Manne und Richels 2004).
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 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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".