Predicting high-magnitude, low-frequency crop losses using machine learning: An application to cereal crops in Ethiopia

Timely and accurate agricultural impact assessments for droughts are critical for designing appropriate interventions and policy. These assessments are often ad hoc, late, or spatially imprecise, with reporting at the zonal or regional level. This is problematic as we find substantial variability in...

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