A spatial econometric approach to designing and rating scalable index insurance in the presence of missing data
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Woodard, J., Shee, A. and Mude, A. 2016. A spatial econometric approach to designing and rating scalable index insurance in the presence of missing data. Geneva Papers on Risk and Insurance – Issues and Practice, 41(2):259-279
Permanent link to cite or share this item: https://hdl.handle.net/10568/76923
Index-Based Livestock Insurance has emerged as a promising market-based solution for insuring livestock against drought-related mortality. The objective of this work is to develop an explicit spatial econometric framework to estimate insurable indexes that can be integrated within a general insurance pricing framework. We explore the problem of estimating spatial panel models when there are missing dependent variable observations and cross-sectional dependence, and implement an estimable procedure which employs an iterative method. We also develop an out-of-sample efficient cross-validation mixing method to optimise the degree of index aggregation in the context of spatial index models.
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