Managed trade: The US–Mexico sugar suspension agreements
Bibliographic record
Abstract
Abstract Under the 1994 North American Free Trade Agreement, Mexican sugar producers were ultimately granted free access to the US sugar market, while all other suppliers, including US refiners, were subject to supply quotas. Following a surge in imports of Mexican sugar, the American Sugar Coalition initiated anti‐dumping and countervailing duty (ADCVD) proceedings against Mexico in early 2014. In December 2014, the ADCVD cases were halted as a result of two suspension agreements negotiated between the US and Mexico. This paper contributes to a small number of empirical studies that have estimated the impact of suspension agreements. We measure the impacts of the ADCVD filings and the suspension agreements on US domestic raw and refined prices, the raw‐to‐refined margin and the quantity and composition of sugar imports from Mexico. Results suggest US raw sugar prices increased by 3¢ per lb. (14%) under ADCVD proceedings, equivalent to an ad valorem tariff between 40% and 50%, while the suspension agreements increased US raw sugar prices by 5¢ (70% tariff equivalent). US refined sugar prices increased by similar amounts under the ADCVD proceedings and the suspension agreements (4.5¢ per lb.). Ultimately, both the ADCVD proceedings and the suspension agreements significantly reduced sugar imports from Mexico. US sugar refiner economic welfare hinges critically on the quantity and composition of raw sugar imports. As such, refiner revenue, following the ADCVD filings and suspension agreements, is estimated to have declined by 16%, relative to a free trade environment.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".