Energy access in conflict-affected states carries a cost premium — yet there is little evidence of its magnitude and whether it can, at least partially, be mitigated. Analyzing 923 World Bank-financed solar PV installations across Yemen between 2019 and 2025, this analysis finds that project-level learning systematically reduces conflict-linked costs, including in the most volatile regions. The aggregate price decomposition attributes 16.8 percentage points of cost reduction to project-level factors. More generally, a Shapley Machine Learning decomposition of project-level cost variation confirms that project-level learning is the most powerful predictor, explaining 45.2% of cost variation. Critically, the conflict-cost relationship evolves over successive procurement cycles: early packages exhibit a significant positive conflict premium, which is gradually mitigated. Cost trajectories converge regardless of whether governorates experienced escalating or de-escalating violence, confirming that learning operates independently of security trends.
| Repository name | URI |
|---|---|
| Reproducible Research Repository (World Bank) | https://reproducibility.worldbank.org |
Paper exhibits were reproduced on a computer with the following specifications:
• OS: MacOS
• Processor: Apple M4 Pro
• Memory available: 24 GB
Runtime: 5 minutes
To reproduce the findings in this paper, a replicator must:
Data section for details.conda env create -f environment.ymlconda activate rr_yem_2026python 01_data_preparation.pypython 02_conflict_intensity.pypython 03_cost_decomposition.pypython 04_regression_analysis.pypython 05_contractor_heterogeneity.pypython 06_shap_analysis.pypython 07_battery_rationalization.pypython generate_all_figures.pyoutputs for users to compare with the published manuscript. Some data is not yet publicly available but is expected to be made available through the World Bank Microdata Library in the future.
| Author | Affiliation | |
|---|---|---|
| Ali Ahmad | World Bank | aahmad10@worldbank.org |
2026-04-06
| Location | Code |
|---|---|
| Yemen | YEM |
The materials in the reproducibility packages are distributed as they were prepared by the staff of the International Bank for Reconstruction and Development/The World Bank. The findings, interpretations, and conclusions expressed in this event do not necessarily reflect the views of the World Bank, the Executive Directors of the World Bank, or the governments they represent. The World Bank does not guarantee the accuracy of the materials included in the reproducibility package.
| Name | URI |
|---|---|
| Modified BSD3 | https://opensource.org/license/bsd-3-clause/ |
| Name | Affiliation | |
|---|---|---|
| Ali Ahmad | World Bank | aahmad10@worldbank.org |
| Reproducibility WBG | World Bank | reproducibility@worldbank.org |
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Reproducibility WBG | DECDI | World Bank - Development Impact Department | Verification and preparation of metadata |
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