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Department seminar by Joshua Woodard, CornellExport this event to calendar

Thursday, November 29, 2012 — 4:00 PM EST

 "A spatial-time model for index based livestock insurance expansion in Kenya"

Index Based Livestock Insurance (IBLI) is a contract written to safeguard livestock against drought which uses an index based on remotely sensed Normalize Difference Vegetation Index observations as the basis for indemnification. Pastoral livestock production is the main livelihood of over three million people in northern Kenya’s arid and semi-arid lands (ASALs). IBLI provides a promising and innovative risk management tool that protects pastoralists and agro-pastoralists from drought related asset losses. IBLI was commercially launched in the Marsabit district (consisting of 5 divisions) in Kenya in January 2010 and in the Borana Zone in southern Ethiopia in July 2012 under the direction of the International Livestock Research Institute (ILRI). The apparent commercial viability of the product has sparked considerable interest in IBLI in Kenya and surrounding regions.

The author is currently working with ILRI on product development in order to scale up IBLI to seven additional districts (92 additional divisions) in Northern Kenya. The broader objective is also to improve the product design in order to reduce basis risk. Given the sparse data available on household mortality over space and time, the challenge is to obtain area-specific optimal response function parameters that adequately predict livestock mortality in the new areas. To this end, we employ spatial econometric methods in order to credibly estimate alternative district/division-specific mortality index response functions and investigate alternative contract design options. Spatial rating methods are developed to allow for maximal information extraction in these missing data cases as information from mortality data in neighboring locations can be formally utilized for predicting mortality where there are missing observations. This framework is also desirable as it allows the structure to capture the influence of other unobservables as well as multidirectional feedback processes. For example, since herds migrate during droughts, the dynamic feedback effects potentially provide another dimension to the response function which can be modeled using the methods proposed. The proposed method employs an out-of-sample efficient spatial modeling framework which optimizes the degree of contract aggregation. Specifically, the final estimated indexes are those resulting from a model which consists of an optimal mixture of a robust division level models and a spatial lag model, where the model weights are estimated via optimization of a cross-validation criterion. The purpose of this seminar will be to outline the contract design and rating and to provide an evaluation of the resulting household-level basis risk.

Location 
M3 - Mathematics 3
3127
200 University Avenue West

Waterloo, ON N2L 3G1
Canada

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