Kenya: 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 Kenya’s vulnerability to economic shocks and identifies those contributing most to economic uncertainty. The Kenyan Computable General Equilibrium (CGE) model was employed to simulate a range of po-tential economic outcomes under various sampled shock scenarios developed using historical data to capture do-mestic 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 yield volatility is the key risk factor for GDP, urban consumption and poverty, while external risks, partic-ularly world beverage crop prices, are more significant for rural consumption and poverty. As the majority of those below the poverty line are rural farmers, world beverage price volatility is the top risk for national poverty levels. Finally, for undernourishment outcomes, domestic cereal yield volatility is the dominant risk factor for all household types. Understanding how possible shocks would impact various segments of the Kenyan 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.
Palabras clave
climate, shock, market prices, computable general equilibrium models, agriculture, crop yield, poverty, nutrition, machine learning, risk assessment