The Potential Global and Developing Country Impacts of Alternative Emission Cuts and Accompanying Mechanisms for the Post Copenhagen Process
Bibliographic record
Abstract
We report numerical simulation results using a multiyear global multi country modeling framework which we use to assess the impacts of alternative emissions cuts which will likely come under consideration for the process to follow the December 2009 UNFCCC negotiation in Copenhagen.The Copenhagen Accord sets out prior country unilateral commitments, and provides a framework for further negotiation of mutually agreed cuts.We also consider possible financial transfers under the Adaptation Fund and possible trade linked border measures against non participants.Countries are linked not only through shared impacts of global temperature change but also through trade among country subscripted goods.We can thus evaluate the potential impacts of either explicit or implicit accompanying mechanisms including funds/transfers, border adjustments, and tariffs.We calibrate the model to alternative BAU damage scenarios largely as set out in the Stern report.The welfare impacts of both emission reductions and accompanying measures are computed in Hicksian money metric equivalent form over alternative potential commitment periods: 2012-2020, 2012-2030, and 2012-2050.We consider different depth, forms, and timeframes for reductions by China, India, Russia, Brazil, US, EU, Japan and a residual Row.Given the damage estimates we use all countries lose from joint reductions since their foregone consumption is more costly than saved damage from reduced climate change.With the use of larger damage estimates this reverses the depth of cut and allocation of cuts by country cause large differences in impacts by country, while differences in form of cut (intensity, embedment) matter less.Accompanying mechanisms also can make a large difference to participation decisions and especially for large population, low wage, rapidly growing non OECD countries, but are costly for the OECD countries.This all suggests that the bargaining set for the post Copenhagen process is very large, making an eventual jointly agreed outcome difficult to achieve.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".