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Author Azevedo Filho, Adriano J. B. V
Title State-contingent insurance and risk management
book jacket
Descript 431 p
Note Source: Dissertation Abstracts International, Volume: 67-09, Section: B, page: 5377
Adviser: Ross D. Shachter
Thesis (Ph.D.)--Stanford University, 2006
This dissertation contributes to the design and evaluation of policies to manage risks from natural catastrophes, considering alternatives such as: state-contingent insurance (SCI), loss-contingent insurance (LCI) and risk mitigation. Particular focus is given to the optimal design of SCI, a risk sharing approach presented as a practical implementation of claims contingent on the state-of-nature, as originated in the Arrow-Debreu theory of markets for risk-bearing. Advances in measurement technology, new concepts, and the increasing openness of capital markets to innovative risk-transfer instruments, favor the success of properly designed SCIs
Indeed, SCI instances have facilitated the transfer of catastrophic risks to capital markets, which would have been difficult to address by conventional insurance (LCI). Transaction costs, contractual difficulties, coverage limitations and risk diversification issues impose insurability obstacles for LCI applied to catastrophic risks, avoided by SCI. In some cases, however, LCI and SCI are not substitutes but have complementary roles and participate together in the optimal risk management policy
Decision theory and decision analysis provide the framework for the risk management approach used in the dissertation. This framework includes decision/influence diagrams and probabilistic networks with continuous variables, implemented in software. A general model is customized to two specific situations. First, to seismic risk management, in a case study developed in the context of Stanford University. Second, to bioenergy risk management, in a case study developed in the context of the ethanol/renewable energy industry in Brazil
The dissertation offers an innovative approach to risk management directed to individuals or organizations interested in self-managing their risks pro-actively, by optimally transferring and/or mitigating them. By providing distinctions and tools to help optimal pricing under uncertainty, the dissertation contributes to the development of market oriented solutions for risk sharing in situations where a traditional resource would be to rely, ex-post disaster, on government aid or charity
School code: 0212
DDC
Host Item Dissertation Abstracts International 67-09B
Subject Business Administration, Management
Economics, Finance
Operations Research
0454
0508
0796
Alt Author Stanford University
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