Rwanda: Systematic analysis of domestic production and world market shocks
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International Food Policy Research Institute
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This study explores Rwanda’s vulnerability to economic shocks and identifies those contributing most to economic uncertainty. The Rwandan Computable General Equilibrium (CGE) model was employed to simulate a range of potential economic outcomes under various sampled shock scenarios developed using historical data to capture domestic agricultural yield volatilities and world market prices uncertainty for traded goods. Data mining and machine learning methods were applied to quantify the contribution of each shock to the uncertainty of economic outcomes (gross domestic product [GDP], private consumption, poverty, and undernourishment). Key findings suggest that domestic root and cereal yield volatility risks are the most important for GDP, poverty, and undernourishment outcomes, while external factors like world energy prices pose the most significant risks to high-income households’ consumption. Understanding how possible shocks would impact various segments of the Rwandan economy and population is a critical first step in facilitating discussions on relevant risk mitigation strategies, such as increasing average crop yields, adopting technologies and practices that narrow yield uncertainties, or diversifying production away from risky crops and sectors.
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risk assessment, climate, shock, economic shock, market prices, computable general equilibrium models, machine learning, agriculture, crop yield