RTAs' Proliferation and Trade‐diversion Effects: Evidence of the ‘Spaghetti Bowl’ Phenomenon
Bibliographic record
Abstract
Abstract This paper investigates the trade‐diversion effects of regional trade agreements (RTAs), so‐called spaghetti bowl phenomenon (SBP), in multilateral trade. The SBP is due to the proliferation of RTAs. Thus, I investigate the relationship between the number of RTAs concluded by a country and the additional trade value attributed to a RTA. Using bilateral trade data in a sample of 119 countries, from 1995 to 2012, my main finding reveals a negative trade effect between them, confirming the existence of SBP in multilateral trade. However, results could not conclude the evidence of a negative effect of overlapping RTAs, involving the existence of SBP, within North–North, North–South or South–South trade. But, the additional trade value attributed to a RTA concluded with EU countries or US seems to confirm significantly a trade‐diversion effect because of the number of RTAs signed by these countries.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".