IDEAS home Printed from https://ideas.repec.org/a/taf/uaajxx/v26y2022i1p102-122.html
   My bibliography  Save this article

Backcasting Mortality in England and Wales, 1600–1840

Author

Listed:
  • Di Wang
  • Wai-Sum Chan

Abstract

There have been significant developments in using extrapolative stochastic models for mortality forecasting (forward projection) in the literature. However, little attention has been devoted to mortality backcasting (backward projection). This article proposes a simple mortality backcasting framework that can be used in practice. Research and analysis of English demography in the 17th and 18th centuries have suffered from a lack of mortality data. We attempt to alleviate this problem by developing a technique that runs backward in time and produces estimates of mortality data before the time at which such data became available. After confirming the time reversibility of the mortality data, we compare the backcasting performance of some commonly used stochastic mortality models for the England and Wales data. The original Lee–Carter model is selected for backcasting purpose of this dataset. Finally, we examine the longevity of British artists between the 17th and the 20th centuries using the backcasted population mortality as benchmarks. The results show that artists living in Britain from 1600 to the mid 1800s had life expectancies similar to those of the general population, with a marked increase in longevity after the Industrial Revolution.

Suggested Citation

  • Di Wang & Wai-Sum Chan, 2022. "Backcasting Mortality in England and Wales, 1600–1840," North American Actuarial Journal, Taylor & Francis Journals, vol. 26(1), pages 102-122, January.
  • Handle: RePEc:taf:uaajxx:v:26:y:2022:i:1:p:102-122
    DOI: 10.1080/10920277.2020.1853574
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/10920277.2020.1853574
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/10920277.2020.1853574?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.

    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:26:y:2022:i:1:p:102-122. 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.