The Effects of Power Outages on the Performance of Manufacturing Firms in the MENA Region
Bibliographic record
Abstract
Abstract Power supply in developing countries is often characterized by unreliability and inefficiency, resulting in disruption costs for operating firms. The extents of power outages in the Middle East and North Africa (MENA) region are more significant compared to other geo-economic regions. This paper examines the effects of power outages on the performance of manufacturing firms in the MENA region using a firm-level dataset derived from the World Bank’s Enterprise Surveys (WBES) database. Firm performance is represented by sales, employment, and productivity growth rates. The extents of power outages are depicted by objective measures characterizing durations and frequencies of power outages, and by perception-based measures reflecting firms’ perceived severity of power outages. The results emphasize the adverse consequences of power outages for the performance of manufacturing firms in the MENA region. They also suggest that different patterns of power outages have varying implications for firm performance, and that the effects of power outages exhibit variations with firm size.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".