Top expenditure distribution in Arab countries and the inequality puzzle
Bibliographic record
Abstract
This study was motivated by reports of a mismatch between inequality experienced on the streets across the Arab region, and that estimated in household expenditure surveys. The study uses eleven surveys from Egypt, Jordan, Palestine, Sudan and Tunisia to investigate whether the dispersion of top expenditures and measurement errors in them bias the measurement of inequality. The expenditure distributions are corrected by replacing potentially mismeasured values with those drawn from parametric distributions. Across all surveys, expenditure inequality is found to be at or below that found in emerging countries worldwide. The Gini is consistently 0.30–0.32 in Egypt, 0.35–0.37 in Jordan, and 0.38–0.43 in Palestine, Sudan and Tunisia. Several surveys include outliers raising inequality estimates. The Egyptian, Palestinian, and Tunisian surveys exhibit smoother top tails of expenditures, approximable by parametric distributions. Across years leading up to the Arab Spring, the estimates in these countries show falling inequality, suggesting that data problems are not behind the Arab inequality puzzle.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".