A spatial econometric approach to designing and rating scalable index insurance in the presence of missing data
Woodard, Joshua D., Shee, Apurba ORCID: 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:https://doi.org/10.1057/gpp.2015.31)
|
PDF (Author Accepted Manuscript)
17673 SHEE_A_Spatial_Econometric_Approach_to_Designing_and_Rating_Scalable_Index_Insurance_2015.pdf - Accepted Version Download (608kB) | Preview |
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 |
Actions (login required)
View Item |
Downloads
Downloads per month over past year