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 However, many economies still do not publish GDP data at a quarterly basis, creating persistent information gaps.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.
Akbal et al. (Mon,) studied this question.