A new IFPRI study published in the Economic Modelling journal presents a groundbreaking approach to understanding how developing economies are affected by multiple, simultaneous shocks — from swings in global commodity prices to volatile crop yields and capital flow disruptions. The study introduces a Systematic Risk Profiling (SRP) framework that integrates computable general equilibrium (CGE) modeling, historical shock data, and machine‑learning tools to identify the most consequential risks facing vulnerable economies.
The SRP framework simulates 10,000 correlated shock scenarios per country, covering 28 external and domestic shocks, enabling analysts to uncover which specific drivers have the greatest influence on GDP, household consumption, poverty, and undernourishment.
Applied to Kenya, Rwanda, and Malawi, the SRP framework reveals sharp differences in vulnerability tied to each country’s economic structure:
- Kenya is primarily exposed to global market volatility, especially fluctuations in world beverage crop prices (coffee and tea), its major export earners. External shocks account for more than 60% of variation in national poverty, with rural households particularly affected.
- Rwanda faces its greatest risks from domestic agricultural shocks, especially root crop yield volatility. Urban households also show significant vulnerability to global energy price fluctuations, given the country’s import dependence.
- Malawi exhibits the highest overall economic volatility among the three countries, driven overwhelmingly by domestic factors. Cereal yield volatility alone accounts for nearly half of the variation in GDP and consumption shocks.
Compounding shocks pose increasing challenges
The authors highlight that shocks rarely occur in isolation. For example, spikes in global energy and fertilizer prices often coincide, and weather-related disruptions frequently affect multiple crops at once. Yet most policy tools and analytical models are not equipped to assess these compounding, correlated shocks.
The SRP framework fills this gap by simulating a wide array of statistically grounded combinations of shocks and using machine learning to decompose the resulting economic outcomes. The findings show that vulnerability is driven not only by shock magnitude but also by underlying structural features, such as:
- The role of subsistence vs. commercial agriculture
- Exposure to international trade
- Variability in domestic crop yields
- Dependence on key export commodities
Implications for policymakers and development partners
“Our study allows policymakers to move from reacting to crises toward proactively identifying and addressing the most dangerous fault lines in their economies,” said lead author Askar Mukashov, Research Fellow at IFPRI.
“SRP turns complex data into practical insights that policymakers can use to target investments and reduce vulnerability where it matters most,” added James Thurlow, Director, Foresight and Policy Modeling, IFPRI.
The study highlights multiple applications for the SRP framework:
- Climate adaptation — integrating climate projections to assess future volatility.
- Agricultural investment prioritization — identifying staple crops driving national risk.
- Trade and macroeconomic planning — understanding exposure to global market fluctuations.
- Social protection targeting — anticipating which households face the highest vulnerability under compound shocks.
“Global challenges demand collective solutions,” said co-author Channing Arndt, Director, Global Trade Analysis Project (GTAP), Purdue University; former Senior Director of Transformation Strategies at IFPRI. “SRP offers a common analytical platform that supports collaboration across governments, regional bodies, and development partners.”
A scalable tool for developing economies
The SRP approach is transparent, scalable, and designed for use in countries where data limitations often restrict conventional risk analysis. The full methodology, country models, and replication package are publicly available as part of IFPRI’s commitment to transparency and open science.
Citation: Mukashov, Askar; Robinson, Sherman; Arndt, Channing; Thurlow, James; and Thomas, Timothy S. 2026. Systematic risk profiling: Assessing compounding economic risks in developing countries. Economic Modelling 157 (April 2026): 07511.
https://doi.org/10.1016/j.econmod.2026.107511
Acknowledgements: The research was supported by the CGIAR Foresight Initiative and the Gates Foundation.
About IFPRI: The International Food Policy Research Institute (IFPRI) provides research-based policy solutions to sustainably reduce poverty and end hunger and malnutrition. IFPRI’s strategic research aims to identify and analyze alternative international and country-led strategies and policies for meeting food and nutrition needs in low- and middle-income countries, with particular emphasis on poor and vulnerable groups in those countries, inclusive development, and sustainability. It is a research center of CGIAR, a worldwide partnership engaged in agricultural research for development. www.ifpri.org
Media inquiries: Evgeniya Anisimova, e.anisimova@cgiar.org