Spatial Panel Model Analysis and Risk Measure Indexes Assessments In Typhoon and flood losses
Date Issued
2009
Date
2009
Author(s)
Hu, Ling
Abstract
Natural disasters occur with low frequency but often cause tremendous damage and social loss. Located in the typhoon belt, Taiwan is one of the most hazard prone areas in the world. Its mountainous topography and high rainfall increase its risk of flooding. Hence, managing the risk of typhoons and floods is an important issue for Taiwan’s government and insurance companies. Using the wrong loss models or risk measure indexes to price insurance products could lead to inaccurate pricing and insolvency. his dissertation has two parts. First, a spatial panel model was used to analyze the annual loss of twenty-three cities in Taiwan. The empirical results showed that spatial effect existed. By adding spatial effect into panel model, the model can explain more than the fixed effect panel model and random effect panel model. Second, a loss distribution of typhoons and floods was built by using a Bayesian Monte Carlo Markov Chain method. Although most researchers use Log-Normal distributions to model a catastrophic loss, this is not appropriate because the loss distribution has positive skewness and is heavy-tailed. Recently, McNeil and Frey (2000), Rootzen and Tajvidi (2000), Thuring, Gustafsson and Pritchard (2008), also stated that using Log-Normal distribution to model a characteristic loss is not appropriate. Our results showed that the Pareto distribution is more adaptive for modeling a typhoon and flood’s loss. Finally, we evaluated different risk measure indexes through simulating and numerical analysis. The simulation results demonstrated that “Tail Standard Deviation” and “Dual Power Distortion” are more suitable while considering the tail loss risk. This dissertation aims to provide guidance to insurance companies and governments in assessing and managing typhoon and flood risks.
Subjects
Spatial Panel Model
Typhoon and flood losses
Monte Carlo Markov Chain
Risk Measure Index
SDGs
Type
thesis
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