Record Details

A Spatial Econometric Approach to Designing and Rating Scalable Index Insurance in the Presence of Missing Data

MELSpace

View Archive Info
 
 
Field Value
 
Title A Spatial Econometric Approach to Designing and Rating Scalable Index Insurance in the Presence of Missing Data
 
Creator Woodard, Joshua
 
Contributor Shee, Apurba
Mude, Andrew
 
Subject agropastoral
bio-economic modeling
 
Description 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.
 
Date 2016-01-20
2016-09-20T11:16:49Z
2016-09-20T11:16:49Z
 
Type Journal Article
 
Identifier https://mel.cgiar.org/reporting/download/hash/aRPIKiQB
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.
https://hdl.handle.net/20.500.11766/4953
Open access
 
Language en
 
Rights CC-BY-NC-4.0
 
Format PDF
 
Publisher Blackwell Publishing
 
Source Geneva Papers on Risk and Insurance: Issues and Practice;41,(2016) Pagination 1,21