Implications of the <scp>EU</scp>'s Carbon Border Adjustment Mechanism for Fertiliser and Food Markets
Bibliographic record
Abstract
Summary Coherence in policy approaches across countries is crucial for achieving common GHG emission reduction goals at lower costs. Agro‐economic models like Aglink‐Cosimo, including global fertiliser markets, are useful for analyzing the anticipated effects of GHG reduction policies on food commodity markets. These policies can significantly affect domestic industry competitiveness, either positively or negatively. Such assessment tools can enhance evidence‐based policy discussions and formation. We include in the baseline a EU ETS carbon price on fertiliser production in the EU as of 2026, without free allowances at 100 USD/tonne of CO2‐eq emitted. Carbon pricing is assumed to be applied by the EU, Canada and the USA to fertiliser production from 2026 onwards. The results of the analysis presented in this article indicate that a Carbon Border Adjustment Mechanism (CBAM) significantly impacts fertiliser trade. A unilateral CBAM tariff affects EU fertiliser trade more than a common CBAM tariff adopted by a coalition of countries. These effects depend heavily on the volume of bilateral trade within club countries. Fertiliser markets influence commodity production and prices modestly due to the price inelasticity of fertiliser demand by farmers and the buffering role of trade in response to price shocks. In terms of GHG emissions, a climate club scenario results in lower total world emissions compared to a unilateral CBAM scenario.
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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".