Journal of Risk Model Validation

Sensitivity analysis of risk measurement for catastrophe losses caused by natural disasters

Myung Suk Kim


In this paper, we examine the sensitivity of risk measurement for losses caused by natural catastrophes. Annual losses from natural disasters for sixteen cities and provinces in South Korea during the period 1979-2011 are used for the case study. Various distributions are suggested for modeling loss distribution, and they are evaluated using the Kolmogorov-Smirnov test. Test results indicate that normal mixture and lognormal distributions are suitable for modeling the losses in several districts. Using these distributions and annual value-at-risk, losses for one-in-ten-year, one-in-twenty-year and one-in-a-hundred-year events are estimated for each district. The corresponding event-to-budget ratios are reported, to examine their impacts on government budgets. Our empirical results show that risk measurements for potential catastrophe losses are very sensitive, according to the assumed loss distributions. This study may help improve governments' risk-based decision-making strategies in the event of natural disasters.


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