The New Tomato Suspension Agreement: What Are the Implications for Trade Flows?
Bibliographic record
Abstract
This paper examines the implications of the new tomato suspension agreement (signed on March 4, 2013, by the U.S. government and Mexican tomato producers) for trade in fresh tomatoes and processed tomato products. The empirical analysis is performed through a gravity model that accounts for vertical linkages between primary and processed goods. The estimated gravity parameters are used to implement suspension agreement scenarios. The results show that the new suspension agreement leads to considerable decreases in Mexico's exports of fresh tomatoes to the United States. These decreases are accompanied with various trade diversion and deflection effects. There are increases in Mexico's exports of processed tomato products to the United States and other countries, and in Mexico's exports of fresh tomatoes to non‐U.S. destinations. These increases do not amount, however, to considerable compensations of the decreases in Mexico's fresh tomato exports to the United States. The results also suggest that the initial 1996‐based suspension agreement has significantly smaller impacts on trade flows over the period that preceded the implementation of the new suspension agreement.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".