Estimation of insurance premiums for coverage against natural disaster risk: an application of Bayesian Inference

This study applies Bayesian Inference to estimate flood risk for 53 dyke ring areas in the Netherlands, and focuses particularly on the data scarcity and extreme behaviour of catastrophe risk. The probability density curves of flood damage are estimated through Monte Carlo simulations. Based on thes...

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Main Authors: Y. Paudel, W. J. W. Botzen, J. C. J. H. Aerts
Format: Article
Language:English
Published: Copernicus Publications 2013-03-01
Series:Natural Hazards and Earth System Sciences
Online Access:http://www.nat-hazards-earth-syst-sci.net/13/737/2013/nhess-13-737-2013.pdf
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author Y. Paudel
W. J. W. Botzen
J. C. J. H. Aerts
author_facet Y. Paudel
W. J. W. Botzen
J. C. J. H. Aerts
author_sort Y. Paudel
collection DOAJ
description This study applies Bayesian Inference to estimate flood risk for 53 dyke ring areas in the Netherlands, and focuses particularly on the data scarcity and extreme behaviour of catastrophe risk. The probability density curves of flood damage are estimated through Monte Carlo simulations. Based on these results, flood insurance premiums are estimated using two different practical methods that each account in different ways for an insurer's risk aversion and the dispersion rate of loss data. This study is of practical relevance because insurers have been considering the introduction of flood insurance in the Netherlands, which is currently not generally available.
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spelling doaj.art-6799f4dfdacb4d55b6ae3fc4b1f42cdd2022-12-21T18:19:26ZengCopernicus PublicationsNatural Hazards and Earth System Sciences1561-86331684-99812013-03-0113373775410.5194/nhess-13-737-2013Estimation of insurance premiums for coverage against natural disaster risk: an application of Bayesian InferenceY. PaudelW. J. W. BotzenJ. C. J. H. AertsThis study applies Bayesian Inference to estimate flood risk for 53 dyke ring areas in the Netherlands, and focuses particularly on the data scarcity and extreme behaviour of catastrophe risk. The probability density curves of flood damage are estimated through Monte Carlo simulations. Based on these results, flood insurance premiums are estimated using two different practical methods that each account in different ways for an insurer's risk aversion and the dispersion rate of loss data. This study is of practical relevance because insurers have been considering the introduction of flood insurance in the Netherlands, which is currently not generally available.http://www.nat-hazards-earth-syst-sci.net/13/737/2013/nhess-13-737-2013.pdf
spellingShingle Y. Paudel
W. J. W. Botzen
J. C. J. H. Aerts
Estimation of insurance premiums for coverage against natural disaster risk: an application of Bayesian Inference
Natural Hazards and Earth System Sciences
title Estimation of insurance premiums for coverage against natural disaster risk: an application of Bayesian Inference
title_full Estimation of insurance premiums for coverage against natural disaster risk: an application of Bayesian Inference
title_fullStr Estimation of insurance premiums for coverage against natural disaster risk: an application of Bayesian Inference
title_full_unstemmed Estimation of insurance premiums for coverage against natural disaster risk: an application of Bayesian Inference
title_short Estimation of insurance premiums for coverage against natural disaster risk: an application of Bayesian Inference
title_sort estimation of insurance premiums for coverage against natural disaster risk an application of bayesian inference
url http://www.nat-hazards-earth-syst-sci.net/13/737/2013/nhess-13-737-2013.pdf
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AT wjwbotzen estimationofinsurancepremiumsforcoverageagainstnaturaldisasterriskanapplicationofbayesianinference
AT jcjhaerts estimationofinsurancepremiumsforcoverageagainstnaturaldisasterriskanapplicationofbayesianinference