Integrated Catastrophe Risk Modeling: Supporting Policy by Aniello Amendola, Tatiana Ermolieva, Joanne

By Aniello Amendola, Tatiana Ermolieva, Joanne Linnerooth-Bayer, Reinhard Mechler

Efficient and equitable regulations for dealing with catastrophe dangers and adapting to worldwide environmental swap are significantly depending on improvement of strong strategies supported by means of built-in modeling.

The publication is predicated on learn and state-of-the artwork types constructed at IIASA (International Institute for utilized platforms research) and inside of its cooperation community. It addresses the methodological complexities of assessing catastrophe dangers, which demand stochastic simulation, optimization equipment and monetary modeling. in addition, it describes coverage frameworks for built-in catastrophe probability administration, together with stakeholder participation facilitated by way of user-interactive decision-support instruments.

Applications and effects are awarded for a couple of case experiences at diversified challenge scales and in numerous socio-economic contexts, and their implications for loss sharing regulations and financial improvement are mentioned. between others, the ebook provides stories for policies for earthquakes within the Tuscany sector in Italy and flood possibility within the Tisza river basin in Hungary. additional, it investigates the industrial influence of common mess ups on improvement and attainable monetary coping thoughts; and functions are proven for chosen South Asian international locations.

The booklet is addressed either to researchers and to businesses concerned with disaster chance administration and danger mitigation policies.

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Griffith University, Brisbane, pp 17–35 Chapter 3 Modeling Catastrophe Risk for Designing Insurance Systems Tatiana Ermolieva and Yuri Ermoliev 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.

1999; Jobst and Zenios 2001; Rockafellar and Uryasev 2000). 5) is a simple example of the so-called stochastic maximin problems. It is easy to see from the optimality conditions for this problem (see Ermoliev and Wets 1988, pp. 165, 416, and further references) that for continuous distributions the optimal value V satisfies condition PbWit Vc ¼ 1=g. For the normal distribution and g ¼ 2, it coincides with the traditional mean value EWit . , the maximization of À Á2 E Wit À V , the optimal V ¼ EWit .

The economic loss of destroyed cubic meters 44 T. Ermolieva and Y. Ermoliev Fig. 2 Earthquake generator of a building is defined as the cost for their reconstruction. Then it is possible to be independent of contingent pricing by considering the cost of reconstruction per cubic meters to be the monetary unit. In this way the simulation of time histories for possible earthquakes in the region produces the sets of economical losses, and enables the design of an insurance programme. It also enables one to determine in which way preventive retrofitting could decrease the losses: this is easily done by a consequent decrease of the vulnerability indices in the loss model.

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