Bibliographic record
Abstract
In the past half-century, the MENA region has witnessed several political uproars, varying between internal instability and conflict to external assaults and disputes. Studies conducted on developing countries have shown that political risk factors have, one way or another, rushed the governments’ decision to default on their debt. The purpose of this study is to examine the significance of the determinants of sovereign debt default. The aim here is to find the correct set of independent variables, whose effect is significant and are agreed upon generally in the literature. The empirical study is a panel data that samples 35 years 1984-2018 for all MENA countries. From the political perspective, I find that corruption and cohesion are the factors that stand behind sovereign debt default. From the economic standpoint, inflation and debt to GDP ratio are significant and positively related indicators to sovereign debt defaults. Whereas, trade openness is significant and negatively related. Moreover, the results reveal that GDP growth is insignificant, this finding contradicts the literature of the determinants of sovereign debt.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".