Climate-Change-Driven Inflation, Modern Money Theory, and Degrowth
Bibliographic record
Abstract
Despite its growing price impacts, climate change has been a relatively overlooked contributor to recent inflationary trends. While global inflationary pressures have been easing since 2023, the global economy remains increasingly more vulnerable to climate-change-driven inflation. This concern has been recently voiced by the European Central Bank, the Bank of England, the Central Bank of Ireland, and the Bank of Canada, among others. Given the supply-side nature of climate-change-driven inflation, the traditional tools of monetary policy, such as higher interest rates, will prove ineffective at controlling it. Fiscal policy measures, such as public-sector-driven productive capacity expansion, as proposed in the Modern Money Theory (MMT) literature, may prove unfeasible from an ecological economics perspective. In the age of rapidly accelerating climate change, a transition to a global degrowth-based economic system may prove the only viable approach to mitigating climate change and the risks of climate-change-driven inflation. While MMT has been commonly associated with growth-oriented public policies and public sector-supported productive capacity expansion, MMT could be effectively utilized as a policy toolkit for a degrowth transition instead, as has been suggested in the degrowth literature
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".