World Data Lab specializes in creating economic and demographic models that help organizations make data-driven decisions. Our global team of data scientists, economists, demographers, and developers are passionate about combining new data sources with groundbreaking methods to push the frontiers of what is knowable.
In 2017, we developed the world's first standardized and comparable model of global poverty and published the methodology in the peer-reviewed scientific journal Palgrave Macmillion as a public good. The method—which uses publicly available data—produces real-time estimates and forecasts of the number of people living on less than $1.90 in every country of the world. Working in partnership with GIZ, the International Fund for Agricultural Development, and IIASA, we are developing methodologies to expand our global poverty dataset to include age, gender and rural/urban proximity.
This model estimates and forecasts extreme poverty for every country in the world by combining survey microdata and mid-term macroeconomic forecasts from the IMF and IIASA.
In the modeling methodology, we separate the shape and location parameters of income and consumption distributions. Once separated, we can forecast location, keep the shape constant and forecast similar consumption distributions by age and gender which can then be fit into the constraints of the national forecasts. Countries without survey information are imputed. Imputations are based on GDP, age pyramids, sectoral employment, and education makeup.
The World Poverty Clock is a webtool which presents estimates and forecasts of the number of people living in extreme poverty for every country of the world, in real-time. Initial development of the World Poverty Clock was sponsored by GIZ in 2017.
To End Poverty
The World Poverty Clock project is ongoing and is shaped by the needs of the development community. We are interested in partnering with like-minded organizations to deepen and broaden the functionality and user experience of the World Poverty Clock.