Please use this identifier to cite or link to this item: https://ah.lib.nccu.edu.tw/handle/140.119/82970
DC FieldValueLanguage
dc.contributor統計系
dc.creatorWang, Hsin Chung;Yue, Jack C.;Tsai, Yi-Hsuan
dc.creator王信忠;余清祥;蔡乙瑄zh_TW
dc.date2016
dc.date.accessioned2016-03-25T09:37:14Z-
dc.date.available2016-03-25T09:37:14Z-
dc.date.issued2016-03-25T09:37:14Z-
dc.identifier.urihttp://nccur.lib.nccu.edu.tw/handle/140.119/82970-
dc.description.abstractGender and age are the top two risk factors considered in pricing life insurance products. Although it is believed that mortality rates are also related to other factors e.g. smoking, overweight, and especially marriage), data availability andmarketing often limit the possibility of including them. Many studies have shown that married people (particularly men) benefit from the marriage, and generally have lower mortality rates than unmarried people.However, most of these studies used data from a population sample; their results might not apply to the whole population. In this study, we explore if mortality rates differ by marital status using mortality data (1975–2011) from the Taiwan Ministry of the Interior. In order to deal with the problem of small sample sizes in some marital status groups, we use graduationmethods to reduce fluctuations in mortality rates. We also use a relational approach to model mortality rates by marital status, and then compare the proposed model with some popular stochastic mortality models. Based on computer simulation, we find that the proposed smoothing methods can reduce fluctuations in mortality estimates between ages, and the relational mortality model has smaller errors in predicting mortality rates by marital status. Analyses of the mortality data from Taiwan show that mortality rates differ significantly by marital status. In some age groups, the differences in mortality rates are larger between marital status groups than between smokers and non-smokers. For the issue of practical consideration, we suggest modifications to include marital status in pricing of life insurance products.
dc.format.extent301347 bytes-
dc.format.mimetypeapplication/pdf-
dc.relationASTIN Bulletin, page 1 of 19.
dc.subjectMarital status; risk factor; small area estimation; longevity risk; relational mortality model
dc.titleMarital Status as a Risk Factor in Life Insurance: An Empirical Study in Taiwan,
dc.typearticle
dc.identifier.doi10.1017/asb.2016.3
dc.doi.urihttp://dx.doi.org/10.1017/asb.2016.3
item.openairetypearticle-
item.cerifentitytypePublications-
item.fulltextWith Fulltext-
item.grantfulltextrestricted-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
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