This 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. ii