This assignment aims to compare the impacts of conflict across the Fragile, Conflict, and Violence (FCV) regions of the Middle East and North Africa (MENA), Afghanistan, and Pakistan through alternative data sources.
- Python 3.8 or higher
- Jupyter Lab for running notebooks
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Clone the repository:
git clone https://github.com/worldbank/MENA-FCV-economic-monitor.git cd MENA-FCV-economic-monitor -
Launch Jupyter Lab:
jupyter lab
For detailed documentation and analysis notebooks, visit the project documentation.
The following datasets are used in this assignment. The raw data accessible to project team members is available on SharePoint
- LinkedIn Hiring Rate - Data from LinkedIn's Economic Graph, which provides insights into hiring trends across MENA region, Afghanistan, and Pakistan.
- Speedtest Intelligence - Data from Ookla's Speedtest Intelligence, which provides insights into internet speed and quality across MENA region, Afghanistan, and Pakistan.
- Down Detector - Data from Ookla's Down Detector, which provides insights into internet outages and disruptions across MENA region, Afghanistan, and Pakistan.
- International Migration Flows - Data from Meta's Data for Good program, which provides insights into global migration flows using Facebook's privacy-protected records of their three billion users. This dataset estimates migration flows for 181 countries on a monthly basis from January 2019 to December 2022.
- ACLED - Data from Armed Conflict Location Event Database that decsribes the locations of all conflicts and fatalities.
- Population - Population data is used from WorldPop
Additional details about each dataset—such as licensing, update frequency, and access instructions—are provided within the respective data products.
Restrictions may apply to the data that support the findings of this study. Data received from the private sector through the Development Data Partnership are subject to the terms and conditions of the data license agreement and the “Official Use Only” data classification. These data are available upon request through the Development Data Partnership. Licensing and access information for all other datasets are included in the documentation.
For questions, feedback, or contributions, please contact:
- Development Data Partnership: datapartnership@worldbank.org
- GitHub Issues: github@worldbank.org
You can also open an issue in the GitHub repository.
This project is licensed under the MIT License together with the World Bank IGO Rider. The Rider is purely procedural: it reserves all privileges and immunities enjoyed by the World Bank, without adding restrictions to the MIT permissions. Please review both files before using, distributing or contributing.
See LICENSE for full details.
This project maintains a Code of Conduct to ensure an inclusive and respectful environment for everyone. Please adhere to it in all interactions within our community.