An Analysis of the IMF’s International Carbon Price Floor
Bibliographic record
Abstract
Abstract The International Monetary Fund (IMF) has proposed an International Carbon Price Floor (ICPF) arrangement among six major emitting economies (the US, EU, UK, Canada, China, and India) to scale up global climate mitigation action. Our quantitative analysis of the IMF’s ICPFs indicates that, compared to the committed policies of National Determined Contributions (NDCs), differentiated price floors are non-binding for developed countries – and therefore have a limited impact on their climate actions. However, for developing countries (e.g. China and India), the ICPFs effectively translate into substantial increases in carbon prices. Essentially, the ICPFs place additional responsibilities of emission reductions and economic costs fully on China and India. Given this gap between the participation incentives of developed and developing economies, we believe that the ICPF arrangement, in its current form, is unlikely to be adopted by major economies. To address this, we recommend that the IMF devote efforts to: (1) estimating the price equivalents of non-price policy instruments, as well as re-calibrating the desirable floors for broadly defined carbon prices; and (2) considering options to redistribute the economic benefits between developed and developing countries by increasing the availability of climate mitigation funds and low-carbon technologies to developing countries.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".