Risk sharing in the Middle East and North Africa
Bibliographic record
Abstract
Abstract This study investigates welfare gains and channels of risk sharing among 14 Middle Eastern and North African (MENA) countries, including the oil‐rich Gulf region and the resource‐scarce economies such as Egypt, Morocco and Tunisia. The results show that for the 1992–2009 period, the overall welfare gains across MENA countries were higher than those documented for the Organization for Economic Cooperation and Development (OECD) nations. In the Gulf region, the amount of factor income smoothing does not differ considerably when output shocks are longer lasting rather than transitory, whereas the amount smoothed by savings increases remarkably when shocks are longer lasting. In contrast, both factor income flows and international transfers respond more to permanent shocks than to transitory shocks in the non‐oil MENA countries. The results also show that a significant portion of shocks is smoothed via remittance transfers in the economically less‐developed MENA countries, but not in the oil‐rich Gulf and OECD countries. Finally, for the overall MENA region, a large part of the shock remains unsmoothed, suggesting that more market integration is needed to remedy the weak link of incomplete risk sharing.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.003 | 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".