Forecasting the Present in Developing Economies
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- Authors: Jeff Kearns
- Published: November 17, 2025
Nowcasting: concept and evolution
- Nowcasting uses real-time data to predict the present, very recent past, and very near future of economic activity; term adapted from meteorology to economics in work beginning in 2002 and formalized in a 2008 paper by Giannone, Reichlin, and Small.
- Nowcasting put informal judgment-based reads on real-time releases into a formal statistical framework and has been expanded to weekly estimates (example: weekly estimates of quarterly US economic growth).
- Recent advances in large language models and artificial intelligence expand possibilities for using text as data and integrating data with metadata.
Data gaps and urgency in developing economies
- About a third of countries publish only annual GDP; many developing economies publish official indicators infrequently or with a delay.
- First estimates of GDP in many advanced economies come out about a month after the end of the quarter; two months in some major emerging market economies; in developing economies it can take more than three months.
- The COVID-19 pandemic exposed “statistical darkness,” motivating central banks and agencies to mobilize alternative high-frequency data sources and enhance nowcasting (Irving Fisher Committee/Bank for International Settlements, 2023).
- Transactional and commercial high-frequency data can provide earlier signals than official releases (examples: Kenya, South Africa).
Practical applications and country examples
- Rwanda
- During COVID-19, a weekly economic activity index combined central bank measures with tax authority electronic billing machine consumer spending, exports, and imports to detect rapid deterioration and inform policy; nowcasting is included in staff briefings before quarterly Monetary Policy Committee meetings.
- National Bank of Rwanda expanded its staff of economists, statisticians, and data scientists; chief economist Thierry Kalisa joined the central bank as chief economist in 2021.
- Kenya
- National Bureau of Statistics releases GDP about three months after a quarter ends.
- The central bank can start gauging the quarter after only a week using private consumer spending data; remittance data available after two weeks; trade, money supply, tourism, and electricity data available in about 40 days to refine the picture.
- IMF-supported nowcasting work shows it is possible to approximate Kenya’s economic growth ahead of official releases and to apply nowcasting where quarterly GDP estimates are unavailable.
- South Africa
- Commercial agricultural data provided early reads on meat and other crops to gauge food inflation; commercial indicators lead CPI by one to three months across components.
- Statistics South Africa released CPI for September three weeks after month-end; corresponding commercial data were available two weeks earlier.
- Samoa
- Population about 220,000; central bank has fewer than 90 staff members.
- Two years into a formal nowcasting system (supported by IMF technical assistance); economics department expected to expand from 8 people to 10.
- Democratic Republic of the Congo
- Official GDP figures are published only annually and with long delays.
- Nowcasting combines copper and cobalt production and prices, money supply, satellite night-light intensity, and Google search trends to feed a quarterly projection model linking short-term assessments with medium-term forecasts and policy scenarios.
- Mining sector contributes about a third of GDP.
- Guinea-Bissau
- In May 2024, deployed blockchain technology to manage public wage bill, in collaboration with IMF, EY, and donors.
- Wage bill fell to half of tax revenue in 2024 from about four-fifths of tax revenues previously.
- Platform to be expanded to cover all 26,600 public officials and 8,100 pensioners nationwide.
- Madagascar
- In October (year not restated in source), customs introduced agentic AI to detect inconsistencies in customs declarations by cross-analyzing declarations, invoices, manifests, and databases, automating many manual inspection tasks and enabling experts to focus on complex cases.
Methodological considerations and limitations
- Practitioners caution that nowcasting and new data sources do not replace the need to expand and improve official statistics; rigorous data collection remains essential.
- Reichlin: “First start with the data, then you get to the technique.” Simple models often perform best; nowcasting exploits different data releases and combines series at different frequencies.
- New data sources can be noisy or nonrepresentative; models that perform well can fail when the world changes.
- Broader concerns include privacy, transparency, legitimacy, and governance when using novel data and AI (Joshua Blumenstock).
- Capacity constraints in many developing economies: limited budgets, scarce skilled staff, and need for computing tools.
Policy implications and operational recommendations
- Use nowcasting to provide timelier, higher-frequency indicators to complement official releases and inform policy decisions in real time.
- Prioritize identification and use of high-quality domestic data or reliable proxies before deploying complex techniques.
- Invest in capacity development: expand rosters of economists, statisticians, and data scientists and equip them with necessary computing resources.
- Combine traditional high-frequency indicators (trade, money supply, production, electricity use) with nontraditional inputs (transaction data, satellite night-lights, Google search trends, commercial market data) to detect turning points and calibrate policy responses.
- Apply nowcasting regionally and through global linkages: interpolate for low-information countries using neighbors, trade partners, and global GDP comovement.
- Leverage AI and LLMs cautiously to expand data access and text-as-data applications while addressing privacy, transparency, and governance issues.
Forecasting the Present in Developing Economies — Jeff Kearns, F&D Magazine, December 2025.
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- Forecasting the Present in Developing Economies