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Analysis of cause-of-death mortality and actuarial implications

Authors
Kwon, Hyuk-SungVu Hai Nguyen
Issue Date
Nov-2019
Publisher
KOREAN STATISTICAL SOC
Keywords
actuarial model; annuity; cause-of-death mortality; life insurance; longevity risk; mortality risk; multinomial logistic regression model
Citation
COMMUNICATIONS FOR STATISTICAL APPLICATIONS AND METHODS, v.26, no.6, pp.557 - 573
Journal Title
COMMUNICATIONS FOR STATISTICAL APPLICATIONS AND METHODS
Volume
26
Number
6
Start Page
557
End Page
573
URI
http://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/35464
DOI
10.29220/CSAM.2019.26.6.557
ISSN
2287-7843
Abstract
Mortality study is an essential component of actuarial risk management for life insurance policies, annuities, and pension plans. Life expectancy has drastically increased over the last several decades; consequently, longevity risk associated with annuity products and pension systems has emerged as a crucial issue. Among the various aspects of mortality study, a consideration of the cause-of-death mortality can provide a more comprehensive understanding of the nature of mortality/longevity risk. In this case study, the cause-of-mortality data in Korea and the US were analyzed along with a multinomial logistic regression model that was constructed to quantify the impact of mortality reduction in a specific cause on actuarial values. The results of analyses imply that mortality improvement due to a specific cause should be carefully monitored and reflected in mortality/longevity risk management. It was also confirmed that multinomial logistic regression model is a useful tool for analyzing cause-of-death mortality for actuarial applications.
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College of Natural Sciences (Department of Statistics and Actuarial Science)
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