Effect of the Duty-Free Quota-Free Market access Schemes in favour of Least developed countries' Products on the Volatility of the Utilization Rate of these Schemes
Bibliographic record
Abstract
Members of the World Trade Organization (WTO) accord a special attention to the integration of the least developed countries (LDCs) into the global trading system. A major Decision in favour of LDCs adopted by WTO Trade Ministers was the one concerning the Duty-Free-Quota-Free (DFQF) market access for products originating in LDCs. The Decision requests that developed-country Members, and developing-country Members in a position to do so, to provide DFQF market access for at least 97% of products originating from LDCs. The present paper investigates whether the DFQF market access schemes offered by the Quadrilateral (i.e., Canada, the European Union, Japan and the United States) to LDCs have helped reduce the volatility of the utilization rates of these generous preferences. The theoretical hypothesis tested is that the minimum target of '97%' and the unlimited duration of the schemes (as long as beneficiaries do not lose the LDC status) have increased the market access predictability as well as the potential benefits of the schemes for LDCs' trading firms, and could hence result in a lower volatility of LDCs' utilization of these schemes. To perform the analysis, we compare LDCs' performance in terms of the volatility of the utilization rate of the DFQF market access schemes with the performance of other designated LICs by the International Monetary Fund, that did not the benefits of the DFQF schemes, and whose products enjoyed less generous preferential treatment. The comparison of the performance of these two groups was made over the period from 2014 to 2019 versus the period from 2004 to 2013. Results have lent credence to the theoretical hypothesis by revealing that the DFQF market access initiative has genuinely been instrumental in reducing the volatility of the utilization rate of these generous preferences schemes in LDCs. The policy implications of the analysis are discussed.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".