IDEAS home Printed from https://ideas.repec.org/a/eee/insuma/v126y2026ics0167668725001283.html

Mortality modeling via vitality: Model constructions and actuarial applications

Author

Listed:
  • Zhu, Xiaobai
  • Zhou, Kenneth Q.
  • Wang, Zijia

Abstract

Mortality modeling plays a central role in actuarial science, with applications ranging from life insurance valuation to optimal lifetime financial planning. Traditional approaches, such as mortality laws and factor-based models, often fall short in capturing the complexity and heterogeneity of mortality dynamics. This paper introduces a novel modeling framework based on the concept of vitality and its stochastic evolution over the life course. The framework consists of four components that account for initial health conditions, natural aging trends, stochastic fluctuations, and sudden accidental events. We explore how modeling mortality through vitality can replicate a wide class of existing mortality models and capture diverse features such as mortality plateaus and longevity trends. Through multiple applications, including optimal consumption planning and disability modeling, we show that the vitality-based framework is capable of providing tractable solutions and intuitive insights to a broad range of mortality-related problems. A numerical illustration using real-world mortality data further demonstrates the framework’s estimation procedure and modeling outcomes.

Suggested Citation

  • Zhu, Xiaobai & Zhou, Kenneth Q. & Wang, Zijia, 2026. "Mortality modeling via vitality: Model constructions and actuarial applications," Insurance: Mathematics and Economics, Elsevier, vol. 126(C).
  • Handle: RePEc:eee:insuma:v:126:y:2026:i:c:s0167668725001283
    DOI: 10.1016/j.insmatheco.2025.103181
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167668725001283
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.insmatheco.2025.103181?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

    for a different version of it.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:eee:insuma:v:126:y:2026:i:c:s0167668725001283. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/505554 .

    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.