In today's rapidly changing world, timely development data is crucial for effective policymaking. The World Bank and its partners are working to invest in frontier approaches to monitor poverty and welfare in real time. By combining traditional data sources with cutting-edge technologies and methodologies, the aim is to develop advanced tools to inform decision-making and strengthen the adaptive capacity of policies.
Traditional poverty measures often reflect conditions from months or years past. In a world of increasing uncertainty—from pandemics to climate shocks—policymakers need timely information to design effective interventions. This work is particularly vital in data-deprived contexts, where household surveys may be infrequent or challenging to conduct.
The World Bank is developing and investing in new approaches to bridge gaps in welfare and poverty data. Many of these approaches leverage new machine learning methods and diverse data sources—from traditional household surveys to satellite imagery and mobile phone data—to create more frequent estimates of poverty. These efforts complement and build on traditional data collection efforts, enhancing the value of existing surveys and supporting the modernization of statistical systems.
For more information on the World Bank's work in real-time welfare monitoring, please contact Paul Clare at pclare@worldbank.org.
Last Updated: Sep 05, 2024