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Predicting Food Crises

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  • Andree,Bo Pieter Johannes
  • Chamorro Elizondo,Andres Fernando
  • Kraay,Aart C.
  • Spencer,Phoebe Girouard
  • Wang,Dieter

Abstract

Globally, more than 130 million people are estimated to be in food crisis. Thesehumanitarian disasters are associated with severe impacts on livelihoods that can reverse years of development gains. Theexisting outlooks of crisis-affected populations rely on expert assessment of evidence and are limited in theirtemporal frequency and ability to look beyond several months. This paper presents a statistical forecastingapproach to predict the outbreak of food crises with sufficient lead time for preventive action. Different usecases are explored related to possible alternative targeting policies and the levels at which finance is typicallyunlocked. The results indicate that, particularly at longer forecasting horizons, the statistical predictions comparefavorably to expert-based outlooks. The paper concludes that statistical models demonstrate good ability to detect futureoutbreaks of food crises and that using statistical forecasting approaches may help increase lead time for action.

Suggested Citation

  • Andree,Bo Pieter Johannes & Chamorro Elizondo,Andres Fernando & Kraay,Aart C. & Spencer,Phoebe Girouard & Wang,Dieter, 2020. "Predicting Food Crises," Policy Research Working Paper Series 9412, The World Bank.
    • Handle: RePEc:wbk:wbrwps:9412
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    1. Vu, Khoa & Vuong, Nguyen Dinh Tuan & Vu-Thanh, Tu-Anh & Nguyen, Anh Ngoc, 2022. "Income shock and food insecurity prediction Vietnam under the pandemic," World Development, Elsevier, vol. 153(C).

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