A Spatial Econometric Approach to Designing and Rating Scalable Index Insurance in the Presence of Missing Data
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Joshua Woodard, Apurba Shee, Andrew Mude. (20/1/2016). 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), pp. 1-21.
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 outof-sample efficient cross-validation mixing method to optimise the degree of index aggregation in the context of spatial index models.