This paper estimates the macroeconomic benefits of improved hydrometeorological forecast services in Cambodia using the World Bank's MFMod macro-fiscal model. Three impact channels—disaster risk reduction (DRR) for flood damages, agricultural productivity increase, and electricity cost reduction—are considered under optimistic and pessimistic climate change projections until the year 2050. Benefits under current forecast skill and continued investment into forecast improvements are compared to a control scenario without any forecast benefits. When all channels operate jointly, GDP is estimated to be 2.50–4.30% above the no-forecast control by 2050. Continued improvement of forecast services yields a 1.3–1.4% increase in GDP, compared to the status quo scenario with constant forecast skill. Agricultural productivity is the dominant channel for economic benefits, while DRR contributions grow with climate severity and become increasingly important under the pessimistic scenario. Electricity cost reduction (through improved hydropower production) contributes positively across all scenarios, though at a lower order of magnitude. Aggregate benefits are larger under the pessimistic climate scenario, because DRR channel returns amplify with increasing flood exposure. Back-of-the-envelope estimates suggest large benefit-cost ratios, making an economic case for improved hydrometeorological forecasts and services. The results provide quantitative support for sustained investment in hydrometeorological infrastructure.
| Repository name | URI |
|---|---|
| Reproducible Research Repository (World Bank) | https://reproducibility.worldbank.org |
Paper exhibits were reproduced on a computer with the following specifications:
• OS: Windows 11 Enterprise
• Processor: INTEL(R) XEON(R) PLATINUM 8562Y+ 2.80 GHz (2 processors)
• Memory available: 32.0 GB
Runtime: 30 minutes
To reproduce the findings in this paper, a user should:
requirements.txt (for Python in Command Prompt) or environment.yml (if using Conda).prepare_impact_channel_data.py.KHM_shocks_EWS.prg.process_model_results.py.All tables and figures will be generated upon completion.
All data sources are publicly available and included in the reproducibility package.
| Author | Affiliation | |
|---|---|---|
| Robin Middelanis | World Bank | rmiddelanis@worldbank.org |
| Unnada Chewpreecha | World Bank | uchewpreecha@worldbank.org |
| Bramka Arga Jafino | World Bank | bjafino@worldbank.org |
| Rachel Koh | CNRS@CREATE | kohzq.rachel@gmail.com |
| Stefano Galelli | Cornell University | galelli@cornell.edu |
| Moussa Sidibe | World Bank | msidibe3@worldbank.org |
| Paolo Avner | World Bank | pavner@worldbank.org |
2026-04-30
| Location | Code |
|---|---|
| Cambodia | KHM |
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 | |
|---|---|---|
| Robin Middelanis | World Bank | rmiddelanis@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 |
2026-04-30
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