Designing index based livestock insurance for managing asset risk in northern Kenya
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Title |
Designing index based livestock insurance for managing asset risk in northern Kenya
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Creator |
Chantarat, S.
Mude, Andrew G. Barrett, Christopher B. Carter, M.R. |
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Subject |
LIVESTOCK
LIVESTOCK INSURANCE PASTORALISM MORTALITY DROUGHT |
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Description |
This paper describes a novel effort at developing index-based insurance for locationaveraged livestock mortality as a means to fill an important void in the risk management instruments available to protect the main asset of pastoralists in the arid and semi-arid lands of Kenya, where insurance markets are effectively absent and uninsured risk exposure is a main cause of the existence of poverty traps. We describe the detailed methodology in designing such insurance contract with the underlying index uniquely constructed off explicit statistical predictions established using longitudinal observations of household-level herd mortality, fit to high quality, objectively verifiable remotely sensed vegetation data not manipulable by either party to the contract and available at low cost and in near-real time. The resulting index performs very well out of sample, both when tested against other complementing household-level herd mortality data from the same region and period and when compared qualitatively with community level drought experiences over the past 27 years. We describe contract pricing and potential risk exposures of the underwriter using a rich time series of satellite-based vegetation data available from 1982-present. And finally, implementation opportunities and challenges are discussed to spur the product’s pilot potential. |
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Date |
2010-03-13T08:08:44Z
2010-03-13T08:08:44Z 2009-07 |
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Type |
Manual
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Identifier |
Chantarat, S.; Mude, A.G.; Barrett, C.B.; Carter, M.R. 2009. Designing index based livestock insurance for managing asset risk in northern Kenya. Ithaca, NY (USA): Cornell University
https://hdl.handle.net/10568/780 |
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Language |
en
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Format |
application/pdf
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Publisher |
Cornell University
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