IDEAS home Printed from https://ideas.repec.org/a/taf/uaajxx/v25y2021is1ps421-s456.html
   My bibliography  Save this article

A Multi-population Approach to Forecasting All-Cause Mortality Using Cause-of-Death Mortality Data

Author

Listed:
  • Pintao Lyu
  • Anja De Waegenaere
  • Bertrand Melenberg

Abstract

All-cause mortality is driven by various types of cause-specific mortality. Projecting all-cause mortality based on cause-of-death mortality allows one to understand the drivers of the recent changes in all-cause mortality. However, the existing literature has argued that all-cause mortality projections based on cause-specific mortality experience have a number of serious drawbacks, including the inferior cause-of-death mortality data and the complex dependence structure between causes of death. In this article, we use the recent World Health Organization causes-of-death data to address this issue in a multipopulation context. We construct a new model in the spirit of N. Li and Lee (2005) but in terms of cause-specific mortality. A new two-step beta convergence test is used to capture the cause-specific mortality dynamics between different countries and between different causes. We show that the all-cause mortality estimations produced by the new model perform in the sample similarly to the estimations by the Lee-Carter and Li-Lee all-cause mortality models. However, in contrast to results from earlier studies, we find that the all-cause mortality projections of the new model have better out-of-sample performance in a long forecast horizon. Moreover, for the case of The Netherlands, an approximately 1-year higher remaining life expectancy projection for a 67-year-old Dutch male in a 30-year forecast horizon is obtained by this new model, compared to the all-cause Li-Lee mortality model.

Suggested Citation

  • Pintao Lyu & Anja De Waegenaere & Bertrand Melenberg, 2021. "A Multi-population Approach to Forecasting All-Cause Mortality Using Cause-of-Death Mortality Data," North American Actuarial Journal, Taylor & Francis Journals, vol. 25(S1), pages 421-456, February.
  • Handle: RePEc:taf:uaajxx:v:25:y:2021:i:s1:p:s421-s456
    DOI: 10.1080/10920277.2019.1662316
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/10920277.2019.1662316
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/10920277.2019.1662316?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. Blake, David & Cairns, Andrew J.G., 2021. "Longevity risk and capital markets: The 2019-20 update," Insurance: Mathematics and Economics, Elsevier, vol. 99(C), pages 395-439.
    2. Miguel Santolino, 2023. "Should Selection of the Optimum Stochastic Mortality Model Be Based on the Original or the Logarithmic Scale of the Mortality Rate?," Risks, MDPI, vol. 11(10), pages 1-21, September.
    3. Nhan Huynh & Mike Ludkovski, 2021. "Joint Models for Cause-of-Death Mortality in Multiple Populations," Papers 2111.06631, arXiv.org.
    4. Basellini, Ugofilippo & Camarda, Carlo Giovanni & Booth, Heather, 2023. "Thirty years on: A review of the Lee–Carter method for forecasting mortality," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1033-1049.
    5. Basellini, Ugofilippo & Camarda, Carlo Giovanni & Booth, Heather, 2022. "Thirty years on: A review of the Lee-Carter method for forecasting mortality," SocArXiv 8u34d, Center for Open Science.

    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:uaajxx:v:25:y:2021:i:s1:p:s421-s456. 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/uaaj .

    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.