Empirical forecasting of slow-onset disasters for improved emergency response: An application to Kenya's arid north
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.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Luseno, Winnie K. & McPeak, John G. & Barrett, Christopher B. & Little, Peter D. & Gebru, Getachew, 2003. "Assessing the Value of Climate Forecast Information for Pastoralists: Evidence from Southern Ethiopia and Northern Kenya," World Development, Elsevier, vol. 31(9), pages 1477-1494, September.
- Meese, Richard A. & Rogoff, Kenneth, 1983. "Empirical exchange rate models of the seventies : Do they fit out of sample?," Journal of International Economics, Elsevier, vol. 14(1-2), pages 3-24, February.
- Lybbert, Travis J. & Barrett, Christopher B. & Desta, Solomon & Coppock, D. Layne, 2002.
"Stochastic Wealth Dynamics And Risk Management Among A Poor Population,"
14736, Cornell University, Department of Applied Economics and Management.
- Travis J. Lybbert & Christopher B. Barrett & Solomon Desta & D. Layne Coppock, 2004. "Stochastic wealth dynamics and risk management among a poor population," Economic Journal, Royal Economic Society, vol. 114(498), pages 750-777, October.
- Manuel Arellano & Stephen Bond, 1991.
"Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations,"
Review of Economic Studies,
Oxford University Press, vol. 58(2), pages 277-297.
- Tom Doan, "undated". "RATS program to replicate Arellano-Bond 1991 dynamic panel," Statistical Software Components RTZ00169, Boston College Department of Economics.
- Anderson, T. W. & Hsiao, Cheng, 1982. "Formulation and estimation of dynamic models using panel data," Journal of Econometrics, Elsevier, vol. 18(1), pages 47-82, January.
- Deaton, Angus, 1985. "Panel data from time series of cross-sections," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 109-126.
- McKenzie, D.J.David J., 2004. "Asymptotic theory for heterogeneous dynamic pseudo-panels," Journal of Econometrics, Elsevier, vol. 120(2), pages 235-262, June.
- Christopher Barrett, 1997. "Heteroscedastic price forecasting for food security management in developing countries," Oxford Development Studies, Taylor & Francis Journals, vol. 25(2), pages 225-236.
- John McPeak, 2004. "Contrasting income shocks with asset shocks: livestock sales in northern Kenya," Oxford Economic Papers, Oxford University Press, vol. 56(2), pages 263-284, April.
When requesting a correction, please mention this item's handle: RePEc:eee:jfpoli:v:34:y:2009:i:4:p:329-339. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.