Nowcasting Low-Income Countries Through Global Linkages

Timely assessment of economic activity is crucial for effective policymaking at the national, regional, and global levels. However, many economies still do not publish GDP data at a quarterly basis, creating persistent information gaps. In 2025, 34% of economies publish only annual GDP statistics. This lack of higher-frequency and timely data is particularly restrictive for emerging market and developing economies, where economic volatility and spillover risks are often highest. The problem is more severe for historical data: only 42% of economies have quarterly GDP estimates for a period longer than 20 years. To address these gaps, this paper develops a model that estimates missing quarterly GDP series by leveraging global and regional economic interconnections. The method transforms sparse annual data into quarterly estimates by exploiting higher-frequency information from the rest of the world, enabling real-time policymaking in both data-scarce economies and in global-level discussions. Moreover, this method ensures internally consistent estimates of regional and global economic activity, allowing both top-down and bottom-up scenario analyses.