Impact of the USMCA on corn (Zea mays L.) trade dynamics and food security in Mexico
Bibliographic record
Abstract
Objective: To determine the impact of corn imports on food security in Mexico by describing the trade dynamics generated by the United States-Mexico-Canada Agreement (USMCA) to highlight the positive effects of foreign trade and free trade policies. Design/Methodology/Approach: The research is based on a quantitative analysis of statistical data on corn involving 27 periods, coinciding with the entry into force of the North American Free Trade Agreement (NAFTA). We used a gravity model with two simultaneously estimated equations —very effective in describing the economies’ trade dynamics. Results: The estimate of the simultaneous equation model identified the United States as the country of greatest significance regarding corn trade with Mexico —an important consideration being that corn trade has a major influence on food security. Study limitations/implications: The most relevant limitation was the lack of a unique source for data documentation. Findings/Conclusions: Mexico’s government policy aims to guarantee food supply. Yet, in 2020, imports supplied 36% of the national corn consumption. Corn imported from the United States is of the yellow variety; the tariff liberalization of this product as per USMCA and the geographical proximity to Mexico contribute to the imported volumes of yellow corn. As per the measurements provided by the Food and Agriculture Organization of the United Nations (FAO), the physical availability of food —in this case, corn— and the economic and physical access to food are met in Mexico. Nevertheless, food security has not been achieved, since 70% of the supply for consumption should come from national production.
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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 | 0.001 |
| 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".