Empirical Forecasting of Slow-Onset Disasters for Improved Emergency Response: An Application to Kenya's Arid North

36 Pages Posted: 27 Jun 2008 Last revised: 24 May 2011

See all articles by Andrew G. Mude

Andrew G. Mude

affiliation not provided to SSRN

Christopher B. Barrett

Cornell University - Charles H. Dyson School of Applied Economics & Management

John G. McPeak

Syracuse University - Department of Economics

Robert Kaitho

Texas A&M University - Center for Natural Resource Information Technology (NRIT); Kenya Agricultural Research Institute (KARI); International Livestock Research Institute (ILRI)

Patti Kristjanson

affiliation not provided to SSRN

Date Written: June 25, 2008

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.

Keywords: Food security, Food aid, Early warning, Emergency response, Forecasting famine

Suggested Citation

Mude, Andrew G. and Barrett, Christopher B. and McPeak, John G. and Kaitho, Robert and Kristjanson, Patti, Empirical Forecasting of Slow-Onset Disasters for Improved Emergency Response: An Application to Kenya's Arid North (June 25, 2008). Food Policy, Vol. 34, No. 4, 2009, Available at SSRN: https://ssrn.com/abstract=1151355

Andrew G. Mude

affiliation not provided to SSRN

Christopher B. Barrett (Contact Author)

Cornell University - Charles H. Dyson School of Applied Economics & Management ( email )

315 Warren Hall
Ithaca, NY 14853-7801
United States
607-255-4489 (Phone)
607-255-9984 (Fax)

HOME PAGE: http://aem.cornell.edu/faculty_sites/cbb2/

John G. McPeak

Syracuse University - Department of Economics ( email )

Syracuse, NY 13244-1020
United States

Robert Kaitho

Texas A&M University - Center for Natural Resource Information Technology (NRIT) ( email )

College Station, TX 77843-2129
United States
(979) 458-3229 (Phone)

Kenya Agricultural Research Institute (KARI)

Makindu
Kenya

International Livestock Research Institute (ILRI)

P.O. Box 30709
Nairobi 00100
Kenya

Patti Kristjanson

affiliation not provided to SSRN

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