English  |  正體中文  |  简体中文  |  Post-Print筆數 : 11 |  Items with full text/Total items : 89686/119522 (75%)
Visitors : 23949723      Online Users : 336
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    政大機構典藏 > 商學院 > 統計學系 > 期刊論文 >  Item 140.119/115639
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/115639


    Title: Mortality models and longevity risk for small populations
    Authors: 余清祥
    Wang, Hsin-Chung
    Yue, Ching-Syang Jack
    Chong, Chen-Tai
    Contributors: 統計學系
    Keywords: Longevity risk;Small area estimation;Lee–Carter model;Standard mortality ratio;Graduation
    Date: 2017
    Issue Date: 2018-01-29 12:29:36 (UTC+8)
    Abstract: Prolonging life expectancy and improving mortality rates is a common trend of the 21st 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.
    Relation: INSURANCE MATHEMATICS & ECONOMICS, 78, 351-359
    Data Type: article
    DOI 連結: https://doi.org/10.1016/j.insmatheco.2017.09.020
    DOI: 10.1016/j.insmatheco.2017.09.020
    Appears in Collections:[統計學系] 期刊論文

    Files in This Item:

    File Description SizeFormat
    j.insmatheco.2017.09.020.pdf676KbAdobe PDF213View/Open


    All items in 政大典藏 are protected by copyright, with all rights reserved.


    社群 sharing

    著作權政策宣告
    1.本網站之數位內容為國立政治大學所收錄之機構典藏,無償提供學術研究與公眾教育等公益性使用,惟仍請適度,合理使用本網站之內容,以尊重著作權人之權益。商業上之利用,則請先取得著作權人之授權。
    2.本網站之製作,已盡力防止侵害著作權人之權益,如仍發現本網站之數位內容有侵害著作權人權益情事者,請權利人通知本網站維護人員(nccur@nccu.edu.tw),維護人員將立即採取移除該數位著作等補救措施。
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback