Estimation of Economic Welfare Gains from Trade Facilitation in the Andean Community
Bibliographic record
Abstract
Border procedures around the globe can act as barriers hindering international trade. Another impact of these procedures relates to their economic resource costs. In this study, using a microeconomic framework of international trade, the potential economic gains are estimated for reductions in trade administration costs related to sea border trade in the Andean Community (CAN) as well as for the increase in import and export trades that are stimulated as a consequence of the reduction in trade administration costs. The potential cost reductions are estimated separately for import and export trade. The estimates are made with respect to the existing levels of trade flows. We measure the excess economic cost of the current trade administration procedures in CAN with respect to two benchmark levels of trade administration costs, namely those for Chile and Singapore. Our results suggest that improving the trade administration cost levels to match those of the reference countries will enable CAN countries to enjoy economic resource savings of between USD 1.25 billion and 1.5 billion annually, corresponding to 0.19% to 0.23% of their gross domestic product. Given the current trade environment of CAN nations, relevant policy and reform options are suggested. The key policy recommendation is to improve the electronic single window system for trade administration and in particular, the interconnectivity of information flows between the member countries of CAN. Maintaining the port infrastructure is also critical for the delivery of efficient services for the movement of goods.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".