• Communications for Statistical Applications and Methods
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• v.28 no.2
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• pp.171-188
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• 2021

Due to an increased demand for longevity risk analysis, various stochastic models have been suggested to evaluate uncertainly in estimated life expectancy and the associated value of future annuity payments. Recently updated data allow us to analyze mortality for a longer historical period and extended age ranges. This study followed up previous case studies using up-to-date empirical data on Korean mortality and the recently developed R package StMoMo for stochastic mortality models analysis. The suitability of stochastic mortality models, focusing on retirement ages, was investigated with goodness-of-fit, validity of models, and ability of generating reasonable sets of simulation paths of future mortality. Comparisons were made across various types of models. Based on the selected models, the variability of important estimated measures associated with pension, annuity, and reverse mortgage were quantified using simulations.

• The Korean Journal of Applied Statistics
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• v.34 no.3
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• pp.347-373
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• 2021

Over the past 50 years, explorative research on the nation's mortality decline patterns has showed a decrease in age-specific mortality rates in all age groups, but there were different improvement patterns in specific mortality rates depending on ages and periods. Greater distinct improvement was observed in mortality rates among women than men, and there was a noticeable improvement in mortality rates in certain groups especially in the more recent decades, revealing a structural change in the overall trends regarding death periods. In this paper, we compare various stochastic mortality models considering cohort effects for mortality projection using Korean female mortality data and further explore the uncertainty related to projection. It also created age-specific mortality rates and life expectancy for women until 2067 based on the results of the analysis, and compared them with future age-specific mortality rates and life expectancy provided by the national statistical office (KOISIS). The best optimal model could vary depending on data usage periods. however, considering the overall fit and predictability, the PLAT model would be regarded to have appropriate predictability in terms of the mortality rates of women in South Korea.

• Communications for Statistical Applications and Methods
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• v.29 no.6
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• pp.679-694
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• 2022

Mortality risk is a significant threat to individual life, and quantifying the risk is necessary for making a national population plan and is a traditionally fundamental task in the insurance and annuity businesses. Like other advanced countries, the sustainability of life pensions and the management of longevity risks are becoming important in Asian countries entering the era of aging society. In this study, mortality and pension value sustainability trends are compared and analyzed based on national population and mortality data, focusing on four Asian countries from 1990 to 2017. The result of analyzing the robustness and accuracy of generalized linear/nonlinear models reveals that the Cairns-Blake-Dowd model, the nonparametric Renshaw-Haberman model, and the Plat model show low stability. The Currie, CBD M5, M7, and M8 models have high stability against data periods. The M7 and M8 models demonstrate high accuracy. The longevity risk is found to be high in the order of Taiwan, Hong Kong, Korea, and Japan, which is in general inversely related to the population size.

• Journal of Veterinary Clinics
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• v.31 no.1
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• pp.40-45
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• 2014

Abalone herpes-like virus (AbHV) is a fatal disease of abalones that impose severe economic impacts on the industry of infected regions due to high mortality. The aim of this study was to quantify the risk of introducing AbHV into Korea through the importation of live abalones for human consumption by import risk analysis (IRA). Monte Carlo simulation models were developed to provide estimates of the probability that a ton of imported abalone contains at least one AbHV-infected individual, using historical trade data and relevant literatures. A sensitivity analysis with 5,000 iterations was also conducted to determine the extent to which input parameters affect the outcome of the model. Although many uncertainties were present in the data, the results indicated that, if 5,000 tons of abalone were imported from a hypothetical exporting country with low prevalence of AbHV (model 1), there would be at least one AbHV-infected abalones in 4,816 of those tons (96.3%), while there would be at least one AbHV-infected abalones in 100% of those tons imported from country with high prevalence (model 2). Sensitivity analysis indicated that for model 1, prevalence was the strongest influence factor on the predicted number of infections. For model 2, background mortality and washing to reduce the risk of surface contamination during processing were the major contributing factors. Risk management strategies need to be enforced to reduce the risk of AbHV introduction in that at least one infected abalone would remain in a consignment from country even with a low prevalence of AbHV infection. The methodology and the results presented here will contribute to improve the development of AbHV management program, and with more accurate data this IRA model will aid science-based decision-making on mitigation strategies to reduce the risk of AbHV introduction in Korea.