Academic Journal
Mortality models and longevity risk for small populations.
| Τίτλος: | Mortality models and longevity risk for small populations. |
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| Συγγραφείς: | Wang, Hsin-Chung1, Yue, Ching-Syang Jack2,3 csyue@nccu.edu.tw, Chong, Chen-Tai2 |
| Πηγή: | Insurance: Mathematics & Economics. Jan2018, Vol. 78, p351-359. 9p. |
| Θεματικοί όροι: | *Mortality -- Mathematical models, *Longevity -- Economic aspects, Life expectancy, Small area statistics, Maximum likelihood statistics, Whittaker functions |
| Περίληψη: | Prolonging life expectancy and improving mortality rates is a common trend of the 21 st century. Stochastic models, such as Lee–Carter model (Lee and Carter, 1992), are a popular choice to deal with longevity risk. However, these mortality models often have unsatisfactory results for the case of small populations. Thus, quite a few modifications (such as approximation and maximal likelihood estimation) to the Lee–Carter can be used for the case of small populations or missing observations. In this study, we propose an alternative approach (graduation methods) to improve the performance of stochastic models. The proposed approach is a combination of data aggregation and mortality graduation. In specific, we first combine the historical data of target population, treating it as the reference population, and use the data graduation methods (Whittaker and partial standard mortality ratio) to stabilize the mortality estimates of the target population. We first evaluate whether the proposed method have smaller errors in mortality estimation than the Lee–Carter model in the case of small populations, and explore if it is possible to reduce the bias of parameter estimates in the Lee–Carter model. We found that the proposed approach can improve the model fit of the Lee–Carter model when the population size is 200,000 or less. [ABSTRACT FROM AUTHOR] |
| Copyright of Insurance: Mathematics & Economics is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Βάση Δεδομένων: | Business Source Index |
| FullText | Links: – Type: other Text: Availability: 0 CustomLinks: – Url: https://www.doi.org/10.1016/j.insmatheco.2017.09.020? Name: ScienceDirect (all content) (s7799221) Category: fullText Text: View record from ScienceDirect MouseOverText: View record from ScienceDirect |
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| Items | – Name: Title Label: Title Group: Ti Data: Mortality models and longevity risk for small populations. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Wang%2C+Hsin-Chung%22">Wang, Hsin-Chung</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Yue%2C+Ching-Syang+Jack%22">Yue, Ching-Syang Jack</searchLink><relatesTo>2,3</relatesTo><i> csyue@nccu.edu.tw</i><br /><searchLink fieldCode="AR" term="%22Chong%2C+Chen-Tai%22">Chong, Chen-Tai</searchLink><relatesTo>2</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Insurance%3A+Mathematics+%26+Economics%22">Insurance: Mathematics & Economics</searchLink>. Jan2018, Vol. 78, p351-359. 9p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Mortality+--+Mathematical+models%22">Mortality -- Mathematical models</searchLink><br />*<searchLink fieldCode="DE" term="%22Longevity+--+Economic+aspects%22">Longevity -- Economic aspects</searchLink><br /><searchLink fieldCode="DE" term="%22Life+expectancy%22">Life expectancy</searchLink><br /><searchLink fieldCode="DE" term="%22Small+area+statistics%22">Small area statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Maximum+likelihood+statistics%22">Maximum likelihood statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Whittaker+functions%22">Whittaker functions</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Prolonging life expectancy and improving mortality rates is a common trend of the 21 st century. Stochastic models, such as Lee–Carter model (Lee and Carter, 1992), are a popular choice to deal with longevity risk. However, these mortality models often have unsatisfactory results for the case of small populations. Thus, quite a few modifications (such as approximation and maximal likelihood estimation) to the Lee–Carter can be used for the case of small populations or missing observations. In this study, we propose an alternative approach (graduation methods) to improve the performance of stochastic models. The proposed approach is a combination of data aggregation and mortality graduation. In specific, we first combine the historical data of target population, treating it as the reference population, and use the data graduation methods (Whittaker and partial standard mortality ratio) to stabilize the mortality estimates of the target population. We first evaluate whether the proposed method have smaller errors in mortality estimation than the Lee–Carter model in the case of small populations, and explore if it is possible to reduce the bias of parameter estimates in the Lee–Carter model. We found that the proposed approach can improve the model fit of the Lee–Carter model when the population size is 200,000 or less. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Insurance: Mathematics & Economics is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1016/j.insmatheco.2017.09.020 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 9 StartPage: 351 Subjects: – SubjectFull: Mortality -- Mathematical models Type: general – SubjectFull: Longevity -- Economic aspects Type: general – SubjectFull: Life expectancy Type: general – SubjectFull: Small area statistics Type: general – SubjectFull: Maximum likelihood statistics Type: general – SubjectFull: Whittaker functions Type: general Titles: – TitleFull: Mortality models and longevity risk for small populations. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Wang, Hsin-Chung – PersonEntity: Name: NameFull: Yue, Ching-Syang Jack – PersonEntity: Name: NameFull: Chong, Chen-Tai IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Text: Jan2018 Type: published Y: 2018 Identifiers: – Type: issn-print Value: 01676687 Numbering: – Type: volume Value: 78 Titles: – TitleFull: Insurance: Mathematics & Economics Type: main |
| ResultId | 1 |