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dc.contributor.authorChanna, Hiraen_US
dc.date.accessioned2014-02-25T18:36:35Z
dc.date.available2014-02-25T18:36:35Z
dc.date.issued2014-01-27en_US
dc.identifier.otherbibid: 8442251
dc.identifier.urihttps://hdl.handle.net/1813/36013
dc.description.abstractThis thesis presents a scalable approach for an index based livestock insurance product in Kenya. The index is formulated using remote sensing data from the Modis satellite data to capture the systemic risk associated with livestock mortality. A spatial econometric approach is taken to model the response functions associated with the insurance. A key research question that it addresses is the level of aggregation at which to estimate the response function. Through the examination of marginal impacts of parameter estimates and using out of sample log likelihood techniques, it is determined that the optimal level of aggregation for the vegetation effects is at the district level, with division level intercepts/fixed effects. The thesis also examines the impact of using Tropical Livestock Units versus animal specific contracts. It determines that the use of Tropical Livestock Units might lead to mispricing of the contract due to the differences in adaptation capacity of the various animals. iien_US
dc.language.isoen_USen_US
dc.titleScalability Of Remotely Sensed Livestock Insurance In East Africaen_US
dc.typedissertation or thesisen_US
thesis.degree.disciplineAgricultural Economics
thesis.degree.grantorCornell Universityen_US
thesis.degree.levelMaster of Science
thesis.degree.nameM.S., Agricultural Economics
dc.contributor.chairWoodard, Joshua D.en_US
dc.contributor.committeeMemberTurvey, Calum G.en_US


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