Empirical forecasting of slow-onset disasters for improved emergency response: An application to Kenya's arid north
Andrew G. Mude,
Christopher Barrett (),
Robert Kaitho and
Food Policy, 2009, vol. 34, issue 4, 329-339
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 3Â months lead time. Such a forecasting model is a potentially valuable tool for enhancing early warning capacity.
Keywords: Food; security; Food; aid; Early; warning; Emergency; response; Forecasting; famine (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10) Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:jfpoli:v:34:y:2009:i:4:p:329-339
Access Statistics for this article
Food Policy is currently edited by J. Kydd
More articles in Food Policy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().