WTO membership, the membership duration and the utilization of non-reciprocal trade preferences offered by the QUAD Countries
Bibliographic record
Abstract
This article explores the effect of WTO membership and the duration of this membership on the utilization of non-reciprocal trade preferences (NRTPs) offered by the QUAD countries (Canada, European Union, Japan and the United States). It uses an unbalanced dataset of 136 beneficiaries of NRTPs over the period of 2002-2019. Results based on the two-step system generalized method of moments approach have revealed that over the full sample, both the WTO membership and its duration exerts a strong positive effect on the utilization rate of GSP programs and other trade preferences. WTO members have made a better utilization of GSP programs than of other trade preferences. Meanwhile, as the duration of their WTO membership increases, beneficiaries make more use of other trade preferences than of GSP programs. Additionally, WTO membership and its duration exert different effects on the usage of NRTPs across sub-samples, including in least developed countries versus non-least developed countries on the one hand, and in WTO Article XII members versus non-Article XII members, on the other hand. Finally, there exists a non-linear positive effect of the duration of WTO membership on the utilization of both GSP programs and other trade preferences, whereby the positive effect takes place immediately after entry of a country into the WTO, and its magnitude amplifies for every additional year of WTO membership.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".