Does the designation of least developed country status promote exports?
Bibliographic record
Abstract
In this paper we examine to what extent developing countries export more as a result of having the official Least Developed Country (LDC) status. We estimate a gravity model of trade over the period 1973–2013, in which identification is achieved by exploiting the particularities and asymmetries of ‘inclusion’ and ‘graduation’ criteria of LDC status. As mechanisms through which LDCs might benefit, we evaluate the effectiveness of individual trade preference schemes for LDCs of the European Union, United States, Canada, Japan, Australia, New Zealand, Norway, and Turkey and the impact of LDC status on exports. We find that first, individual trade preference regimes are not always beneficial in terms of increased export values. Export promoting effects are found for the individual schemes of some developed countries and some sectors. Second, a country’s official designation as a LDC is associated with higher aggregated exports. This is particularly the case for LDCs that export agricultural goods and light manufacturing products, including textiles and leather after 1990. Third, the positive effect of LDC status is significant and sizable even when controlling for specific trade preference schemes suggesting that there are other benefits of LDC status that play a role in promoting exports.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".