(Customs) unity as strenght: How the EU and its partners can respond to tariff threats
Bibliographic record
Abstract
This Policy Brief explores the potential impact of forming a customs union between the European Union (EU) and key global partners (e.g. Canada, the UK, Mexico and Japan) as a strategic response to U.S. President Donald Trump's threatened tariffs. Using the GSIM partial equilibrium model, the study simulates various customs union configurations under two baseline scenarios of high and low U.S. tariffs. The findings show modest overall economic effects, with the EU consistently benefiting from increased output, while countries like Canada, Mexico and Japan would also gain under certain scenarios. The U.S. would experience output losses, and China would incur consistent welfare losses. The study argues that, beyond the economic rationale, broader security and geopolitical concerns - especially in light of Trump's antagonism towards NATO and traditional U.S. allies - justify stronger EU-led economic cooperation. It advocates for a strategic expansion of the EU's customs union to include like-minded global partners, reinforcing trade resilience and global economic stability.
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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 | 0.002 | 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 | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".