Empirical forecasting of slow-onset disasters for improved emergency response: An application to Kenya's arid north

Andrew G. Mude, Christopher B. Barrett, John G. McPeak, Robert Kaitho, Patti Kristjanson

Research output: Contribution to journalArticle

17 Scopus citations

Abstract

Mitigating the negative welfare consequences of crises such as droughts, floods, and disease outbreaks, is a major challenge in many areas of the world, especially in highly vulnerable areas insufficiently equipped to prevent food and livelihood security crisis in the face of adverse shocks. Given the finite resources allocated for emergency response, and the expected increase in incidences of humanitarian catastrophe due to changing climate patterns, there is a need for rigorous and efficient methods of early warning and emergency needs assessment. In this paper we develop an empirical model, based on a relatively parsimonious set of regularly measured variables from communities in Kenya's arid north, that generates remarkably accurate forecasts of the likelihood of famine with at least 3 months lead time. Such a forecasting model is a potentially valuable tool for enhancing early warning capacity.

Original languageEnglish (US)
Pages (from-to)329-339
Number of pages11
JournalFood Policy
Volume34
Issue number4
DOIs
StatePublished - Aug 2009

Keywords

  • Early warning
  • Emergency response
  • Food aid
  • Food security
  • Forecasting famine

ASJC Scopus subject areas

  • Food Science
  • Development
  • Sociology and Political Science
  • Economics and Econometrics
  • Management, Monitoring, Policy and Law

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