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Integrated Catastrophe Risk Modeling pp 29–52Cite as

Modeling Catastrophe Risk for Designing Insurance Systems

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Part of the book series: Advances in Natural and Technological Hazards Research ((NTHR,volume 32))

Abstract

In catastrophe management, risk spreading is one of the important measures for increasing societal resilience to disasters. In this paper we discuss an integrated catastrophe management model which explores alternative risk spreading options. As a case study we consider the seismic prone Tuscany region of Italy. Special attention is given to the evaluation of a public loss-spreading program involving partial compensation to victims by the central government and the spreading of risks through a pool of insurers on the basis of location-specific exposures. GIS-based catastrophe models and stochastic optimization methods are used to guide policy analysis with respect to location-specific risk exposures. The use of economically sound risk indicators lead to convex stochastic optimization problems strongly connected with nonconvex insolvency constraint and Conditional Value-at-Risk (CVaR).

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Author information

Authors and Affiliations

  1. Ecosystems, Services and Management (ESM) Program, International Institute for Applied Systems Analysis (IIASA), Schlossplatz 1, A-2361, Laxenburg, Austria

    Tatiana Ermolieva

  2. International Institute for Systems Analysis (IIASA), Schlossplatz 1, A-2361, Laxenburg, Austria

    Yuri Ermoliev

Authors
  1. Tatiana Ermolieva
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  2. Yuri Ermoliev
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Correspondence to Tatiana Ermolieva .

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Editors and Affiliations

  1. Risk, Policy and Vulnerability (RPV) Program, International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria

    Aniello Amendola , Joanne Linnerooth-Bayer  & Reinhard Mechler ,  & 

  2. Ecosystems, Services and Management (ESM) Program, International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria

    Tatiana Ermolieva

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Ermolieva, T., Ermoliev, Y. (2013). Modeling Catastrophe Risk for Designing Insurance Systems. In: Amendola, A., Ermolieva, T., Linnerooth-Bayer, J., Mechler, R. (eds) Integrated Catastrophe Risk Modeling. Advances in Natural and Technological Hazards Research, vol 32. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-2226-2_3

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