This repository contains the analysis presented in the paper “Will Every Child Be Able to Read by 2030? Why Eliminating Learning Poverty Will Be Harder Than You Think, and What to Do About It.” [1].
As a significant contributor to human capital deficits, the learning crisis undermines sustainable growth and poverty reduction. The paper introduces the new concept of learning poverty and provides a synthetic indicator with global coverage to spotlight this crisis. Learning poverty means being unable to read and understand a short, age-appropriate text by age 10. This indicator brings together schooling and learning by adjusting the proportion of kids in school below a proficiency threshold by the out-of-school population.
The new data show that more than half of all children in World Bank client countries suffer from learning poverty – the majority of them low- and middle-income countries. And progress in reducing learning poverty is far too slow to meet the SDG aspirations: even if countries reduce their learning poverty at the fastest rates we have seen so far in this century, the goal of ending it will not be attained by 2030.
[1] Azevedo, J.P., and others. 2019. “Will Every Child Be Able to Read by 2030? Why Eliminating Learning Poverty Will Be Harder Than You Think, and What to Do About It.” World Bank Policy Research Working Paper series. Washington, DC: World Bank.
Most of the data used to calculate learning poverty comes from the Global Learning Assessment Database (GLAD), a collection of harmonized datasets at the individual and country level. This harmonization has been made possible thanks to the leadership of the UNESCO Institute for Statistics (UIS), the custodian agency for SDG 4, in coordinating a Global Alliance for the Monitoring of Learning (GAML), and in establishing Minimum Proficiency Levels (MPLs) that enable countries to benchmark learning. Working with the UIS, we have built a consolidated global database representing 80% of the population of primary-age children globally.
See the Technical Note for more contextual information on the learning poverty measure, how it was calculated and which sources were used.
See the Repository Structure Note to understand the sequencing of the tasks, visualizing the data flowcharts in this project and for an overview of the variables in each dataset.
See the Contribution and Replication Note for information on how to navigate this repository, how to contribute to the code and how to replicate the numbers.
This Repository is maintained by the EduAnalytics team at the World Bank Education Global Practice.
The EduAnalytics team aims to provide internal and external clients timely access to high quality data, tools, and analytics that can be used to measure, monitor, and understand the education sector across regions.
The team can be reached at eduanalytics@worldbank.org.