Effects of Regional Trade Agreements on Trade in Agrifood Products: Evidence from Gravity Modeling Using Disaggregated Data
Bibliographic record
Abstract
The recent proliferation of regional trade agreements (RTAs) has intensified the debate on their merits. A growing literature has addressed this policy debate, focusing on the welfare and trade effects of RTAs and their likely impacts on the multilateral trading system. Some view them as stepping-stones toward multilateral trade liberalization while others see them as stumbling blocks against free trade. The existing literature has neglected some important aspects of RTAs dealing with trade in agrifood products. This study analyzes trade creation and diversion effects of the North American Free Trade Agreement (NAFTA) on trade of six selected agrifood products from 1985 to 2000. The investigation estimates an extended gravity model using pooled cross-sectional time-series regression and generalized least squares methods. The result shows that the share of intraregional trade is growing within NAFTA and that NAFTA has displaced trade with the rest of the world. NAFTA has served to boost trade significantly among its members rather than with the rest of the world. Countries participating in NAFTA have moved toward a lower degree of relative openness in agrifood trade with the rest of the world.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".