Using Alternative Data to Understand Economic Impacts of the 2023 Turkey–Syria Earthquake
On February 6, 2023, a powerful 7.8 magnitude earthquake and a series of strong tremors and aftershocks wrought substantial damages across southeastern Türkiye and northwest Syria. As of time of writing, the death toll has passed 40,000 and the earthquake’s aftermath is substantially impacting the people, infrastructure, and economies of the two countries. The World Bank announced $1.78 Billion for Türkiye’s recovery and reconstruction efforts. Effective World Bank and donor interventions will require a deep, data-driven understanding of these impacts.
The Türkiye Country Economist team has requested advisory on data and analytical resources that may support measurement and monitoring of socio-economic impacts, including population displacement and business impacts.
The Türkiye Country Economist team requested the WB Data Lab to explore use of alternative data to better understand immediate socio-economic impacts of the earthquake and resiliency of the affected economies. To this end, the team prepared a Strategic Brief, which presents available datasets and analytics to support answers to these questions.
From this Brief, the team requested the Lab to focus on trends in observed nighttime lights, internet connectivity, population movement, and retail activity.
The team, comprised of colleagues from the Global Operations Support Team (GOST), the Development Impact Monitoring and Evaluation team (DIME), the Development Data Partnership, and the WB Data Lab, worked with the country team to explore use of alternative open and proprietary data sources to generate new data products that can be sustainably updated.
Datasets and methods used to generate insights for this project have been prepared as Data Goods. Data Goods are comprised of data, reproducible methods (code), documentation, and sample insights. Unlike a traditional data analysis, which results in a single-use report or visualization, Data Goods are designed to be re-used for future updates and projects, thereby building the capacity of the World Bank and partner organizations to quickly and effectively deliver complex data science solutions to pressing global challenges.
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.
This projects is licensed under the Mozilla Public License - see the LICENSE file for details.