IDEAS home Printed from https://ideas.repec.org/a/taf/sactxx/v2019y2019i2p97-112.html
   My bibliography  Save this article

A logistic two-population mortality projection model for modelling mortality at advanced ages for both sexes

Author

Listed:
  • Jackie Li
  • Jia Liu

Abstract

In the current literature, numerous mortality projection models have been proposed and tested, but in general they have been designed for and applied to mainly ages below 90. As medical advances are being shifted to older ages over time and there is a rapid growth in the number of centenarians, there is a need to expand the modelling to older ages. We propose a logistic two-population mortality projection model for the death rates at ages 80 to 100+ for both sexes. We apply this model and its extensions to high quality old-age mortality data of Belgium, Sweden, Switzerland, and the UK and produce decent model performance in both mortality fitting and forecasting. The model structure also provides a reasonable way to close off the life table, which is supported by both theoretical arguments and empirical evidence.

Suggested Citation

  • Jackie Li & Jia Liu, 2019. "A logistic two-population mortality projection model for modelling mortality at advanced ages for both sexes," Scandinavian Actuarial Journal, Taylor & Francis Journals, vol. 2019(2), pages 97-112, February.
  • Handle: RePEc:taf:sactxx:v:2019:y:2019:i:2:p:97-112
    DOI: 10.1080/03461238.2018.1511464
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/03461238.2018.1511464
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/03461238.2018.1511464?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jackie Li & Jia Liu & Adam Butt, 2024. "A systematic vector autoregressive framework for modeling and forecasting mortality," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 2279-2297, September.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:sactxx:v:2019:y:2019:i:2:p:97-112. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/sact .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.