Askar Mukashov

Systematic risk profiling: Assessing compounding economic risks in developing countries

This paper presents a systematic risk profiling (SRP) framework to identify the most critical economic risks facing developing countries. Integrating computable general equilibrium (CGE) models with historical shock data and machine-learning tools, we examine how compound shocks affect development outcomes. We apply this method to Kenya, Rwanda, and Malawi, simulating thousands of plausible combinations of world price, capital flow, and productivity exogenous shocks and their impacts on countries’ GDP, household consumption, poverty, and undernourishment. The results reveal distinct risk profiles driven by structural differences: Kenya’s primary vulnerability is the volatility in global beverage crop prices, whereas Rwanda and Malawi face the highest risks from domestic root crop and cereal yields, respectively. These findings underscore that vulnerability is not just a function of shock magnitude, but of the specific structure of each economy. Specifically, the high economic volatility in Malawi and Rwanda is driven by the larger role of subsistence agriculture and more volatile domestic yields, whereas Kenya’s agricultural sector is more export-oriented. Unlike standard ad hoc scenario analysis, SRP quantifies both the likelihood of compound events and the relative importance of their drivers. This transparent, scalable framework provides policymakers a new tool to move beyond reactive measures and design targeted, country-specific resilience strategies for an increasingly volatile world.

Promoting regional income equity under structural transformation and climate change: An economywide analysis for Senegal

Ghana: Systematic analysis of world market and domestic production shocks

Achieving development goals is subject to economic uncertainties, yet policymaking rarely accounts for these risks. This Country Brief quantifies the risks facing Ghana’s economy and population, focusing on two primary sources: 1) External risks stemming from shocks in international commodity prices and foreign capital flows and 2) Domestic risks associated with production shocks in volatile sectors of the Ghanaian economy, such as primary agriculture and hydropower electricity generation, are often caused by extreme weather. The significance of these risks is assessed based on the range of the shocks’ impacts on four main economic and development indicators: total GDP, private consumption, poverty rate, and prevalence of undernourishment. The analysis uses data mining methods to simultaneously sample many shocks from historical data, con structing a comprehensive set of realistic shock scenarios for Ghana. A country-specific, economywide Computable General Equilibrium (CGE) model then simulates the impacts of these shocks on both total and sector-specific economic outcomes, deriving changes in poverty and undernourishment for each shock scenario. Finally, machine learning techniques are applied to obtain metrics for the relative im portance of different risk factors. The results suggest that Ghana’s trade-oriented economy is predominantly exposed to external risks, with fluctuations in world prices of key exports—particularly energy and metals—significantly influencing eco nomic activity and the country’s ability to finance imports. Poverty and undernourishment risks present a more complex picture, with a significant difference between urban and rural risk factors. Rural households, which are generally poorer than urban households and constitute the majority of the poor and undernourished population, are more exposed to domestic production volatility factors. Understanding these economic risks is a critical first step in facilitating discussions on potential risk management strategies, such as promoting domestic productivity growth and diversifying economic activity away from high-risk sectors.