Analysis of cause-of-death mortality and actuarial implications
- Authors
- Kwon, Hyuk-Sung; Vu 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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