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Quantifying spatial basis risk for weather index insurance

Quantifying spatial basis risk for weather index insurance Purpose – The purpose of this paper to develop an empirical methodology for managing spatial basis risk in weather index insurance by studying the fundamental causes for differences in weather risk between distributed locations. Design/methodology/approach – The paper systematically compares insurance payouts at nearby locations based on differences in geographical characteristics. The geographic characteristics include distance between stations and differences in altitude, latitude, and longitude. Findings – Geographic differences are poor predictors of payouts. The strongest predictor of payout at a given location is payout at nearby location. However, altitude has a persistent effect on heat risk and distance between stations increases payout discrepancies for precipitation risk. Practical implications – Given that payouts in a given area are highly correlated, it may be possible to insure multiple weather stations in a single contract as a “risk portfolio” for any one location. Originality/value – Spatial basis risk is a fundamental problem of index insurance and yet is still largely unexplored in the literature. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The Journal of Risk Finance Emerald Publishing

Quantifying spatial basis risk for weather index insurance

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References (126)

Publisher
Emerald Publishing
Copyright
Copyright © 2013 Emerald Group Publishing Limited. All rights reserved.
ISSN
1526-5943
DOI
10.1108/15265941311288086
Publisher site
See Article on Publisher Site

Abstract

Purpose – The purpose of this paper to develop an empirical methodology for managing spatial basis risk in weather index insurance by studying the fundamental causes for differences in weather risk between distributed locations. Design/methodology/approach – The paper systematically compares insurance payouts at nearby locations based on differences in geographical characteristics. The geographic characteristics include distance between stations and differences in altitude, latitude, and longitude. Findings – Geographic differences are poor predictors of payouts. The strongest predictor of payout at a given location is payout at nearby location. However, altitude has a persistent effect on heat risk and distance between stations increases payout discrepancies for precipitation risk. Practical implications – Given that payouts in a given area are highly correlated, it may be possible to insure multiple weather stations in a single contract as a “risk portfolio” for any one location. Originality/value – Spatial basis risk is a fundamental problem of index insurance and yet is still largely unexplored in the literature.

Journal

The Journal of Risk FinanceEmerald Publishing

Published: Dec 28, 2012

Keywords: Insurance; Precipitation; Rainfall; Index insurance; Weather derivatives; Spatial basis risk; Basis risk

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