Woodard, Joshua D., Shee, Apurba ORCID: https://orcid.org/0000-0002-1836-9637 and Mude, Andrew (2016) A spatial econometric approach to designing and rating scalable index insurance in the presence of missing data. The Geneva Papers on Risk and Insurance - Issues and Practice, 41 (2). pp. 259-279. ISSN 1018-5895 (Print), 1468-0440 (Online) (doi:10.1057/gpp.2015.31)

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Abstract

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.

Item Type:	Article
Uncontrolled Keywords:	Index insurance; Spatial econometric models with missing data; NDVI; Kenya pastoralist livestock production; Cross-validation; Model mixing
Subjects:	S Agriculture > S Agriculture (General)
Faculty / School / Research Centre / Research Group:	Faculty of Engineering & Science Faculty of Engineering & Science > Natural Resources Institute Faculty of Engineering & Science > Natural Resources Institute > Development Studies Research Group Faculty of Engineering & Science > Natural Resources Institute > Food & Markets Department
Last Modified:	26 Apr 2020 16:40
URI:	http://gala.gre.ac.uk/id/eprint/17673

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