A Spatial Econometric Approach to Designing and Rating Scalable Index Insurance in the Presence of Missing Data
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Title |
A Spatial Econometric Approach to Designing and Rating Scalable Index Insurance in the Presence of Missing Data
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Creator |
Woodard, Joshua
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Contributor |
Shee, Apurba
Mude, Andrew |
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Subject |
agropastoral
bio-economic modeling |
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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. |
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Date |
2016-01-20
2016-09-20T11:16:49Z 2016-09-20T11:16:49Z |
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Type |
Journal Article
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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 |
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Language |
en
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Rights |
CC-BY-NC-4.0
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Format |
PDF
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Publisher |
Blackwell Publishing
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Source |
Geneva Papers on Risk and Insurance: Issues and Practice;41,(2016) Pagination 1,21
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