Eric is a globally recognized economist with a passion for analyzing the most effective ways to use data for development. He was an original member of the Inter-Agency and Expert Group on the Millennium Development Goals. As senior advisor and program manager of the World Bank’s Development Data Group, he was in charge of World Development Indicators and Global Monitoring, was managing editor of the World Development Indicators and Atlas of Global Development, and managed production of the Bank’s principal statistical databases. As a member of the senior management team, he was an expert representative on numerous high-level international committees and task forces.
World Economics has released a Data Quality Index (DQI), rating the quality of GDP estimates for 154 countries. The DQI is presented as a “new way to judge which countries (sic) GDP you can trust.” Therefore, it is striking, and perhaps ironic, that the DQI depends heavily on GDP.
Recently published estimates by Brookings Institution researchers Laurence Chandy and Christine Zhang of the funding needed to produce indicators for monitoring SDGs appears to demonstrate that other cost assessments are far too high. But the analysis leaves out elements and runs the risk of creating complacency over the need for serious, continuing investments in the statistical capacity of developing countries.
Two questions — “What is the data revolution?” and “How is it affecting people’s lives?” — lead to many more questions. The world is generating data at an ever increasing rate. What is it good for? Who benefits? Will poor countries be left out?