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Ermolieva, T. & Ermoliev, Y.
(2013).
Modeling catastrophe risk for designing insurance systems.
In:
Integrated Catastrophe Risk Modeling: Supporting Policy Processes.
Eds. Amendola, A, Ermolieva, T, Linnerooth-Bayer, J, & Mechler, R 
ORCID: https://orcid.org/0000-0003-2239-1578,
Dordrecht: Springer.
10.1007/978-94-007-2226-2_3.
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).
| Item Type: | Book Section |
|---|---|
| Uncontrolled Keywords: | Flood and seismic risk; Catastrophe modeling; Catastrophe insurance; Contingent credit; Stochastic optimization; Safety constraints; Risk measures |
| Research Programs: | Advanced Systems Analysis (ASA) Ecosystems Services and Management (ESM) |
| Bibliographic Reference: | In: A Amendola, T Ermolieva, J Linnerooth-Bayer, R Mechler (Eds); Integrated Catastrophe Risk Modeling: Supporting Policy Processes; Springer, Dordrecht, Netherlands pp.29-52 |
| Related URLs: | |
| Depositing User: | IIASA Import |
| Date Deposited: | 15 Jan 2016 08:49 |
| Last Modified: | 27 Aug 2021 17:23 |
| URI: | https://pure.iiasa.ac.at/10601 |
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