Sectoral composition, export trade partners and value added: An input-output analysis for Brazil and Mexico Patieene Alves-Passoni
Bibliographic record
Abstract
This study examine the impact of changes in the sectoral composition of exports and in trade partners on the value added of Brazil and Mexico between 2000 and 2019, within the framework of Latin American structuralism. Employing quantitative input-output structural decomposition analysis, we identify shifts in value added coefficients, production techniques, domestic demand and exports (level, product mix and trade partners). The research brings out a significant correlation between changes in trade partners and the structure of the export basket. Both Brazil and Mexico display export concentration, geographically and sectorally. While alterations in the export basket and trade partners had a negative impact on Mexico’s value added growth, Brazil experienced a positive effect. This finding for Brazil is attributed in part to its specialized agricultural and mineral exports to China. Conversely, Mexico’s specialization in transport equipment exports to the United States and Canada contributed to its unfavourable outcome.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".