Energy Subsidy Reform and Poverty in Arab Countries: A Comparative CGE‐Microsimulation Analysis of Egypt and Jordan
Bibliographic record
Abstract
This study simulates the macroeconomic and distributive impacts of real proposed (by local policy makers) energy subsidy reforms in Egypt and Jordan. To do that, we develop a dynamic CGE‐microsimulation model that is able to reconcile the general equilibrium effects of the reform and the individual‐ and household‐specific distributive effects. While the nature of the proposed reforms differs in the two countries, the study underscores the need, in both countries, for reform to generate fiscal savings to boost private investment and increase economic growth. It also shows that the reform alone would further exacerbate poverty through increased consumer prices. However, a modest reinvestment of fiscal savings into cash transfers creates a win‐win scenario of reduced poverty without significantly sacrificing the fiscal and growth benefits from the reform. Impacts (prices, growth, fiscal savings, poverty) are greater in Egypt due to the extent of proposed reforms and the fact that a larger share of the energy products concerned are consumed directly by households, while in Jordan the major effects come from the increase in intermediate input costs which generate a fall in the aggregate demand and, so, in labor demand.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".