The Influence of Trade Facilitation on the Depth and Breadth of China's Agricultural Exports: Empirical Evidence Based on RCEP Countries
Bibliographic record
Abstract
This article analyzes how trade facilitation influence China’s agricultural exports to RCEP partners. Based on the data of the World Economic Forum Global Competitiveness Report and principal component analysis, we constructs a 14 index system to measure trade facilitation. Based on the export data from 2011 to 2019, the extended gravity model is used to estimate the relationship between trade facilitation and the depth and breadth of China's agricultural exports. The study shows that improving the trade facilitation of RCEP partners can significantly enhance the depth of China's agricultural exports. Specifically, the trade openness, e-commerce and financial environment of importing countries have a significant positive impact on the depth and breadth of exports. Another important finding is that China's trade facilitation has played a more active role in the depth and breadth of exports. Its infrastructure quality, e-commerce and financial environment can greatly promote China's agricultural exports.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".