IDEAS home Printed from https://ideas.repec.org/a/bla/jorssa/v164y2001i2p275-291.html
   My bibliography  Save this article

Bayesian analysis of mortality data

Author

Listed:
  • Petros Dellaportas
  • Adrian F. M. Smith
  • Photis Stavropoulos

Abstract

Congdon argued that the use of parametric modelling of mortality data is necessary in many practical demographical problems. In this paper, we focus on a form of model introduced by Heligman and Pollard in 1980, and we adopt a Bayesian analysis, using Markov chain Monte Carlo simulation, to produce the posterior summaries required. This opens the way to richer, more flexible inference summaries and avoids the numerical problems that are encountered with classical methods. Particular methodologies to cope with incomplete life‐tables and a derivation of joint lifetimes, median times to death and related quantities of interest are also presented.

Suggested Citation

  • Petros Dellaportas & Adrian F. M. Smith & Photis Stavropoulos, 2001. "Bayesian analysis of mortality data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 164(2), pages 275-291.
    • Handle: RePEc:bla:jorssa:v:164:y:2001:i:2:p:275-291
    DOI: 10.1111/1467-985X.00202
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/1467-985X.00202
    Download Restriction: no
    File URL: https://libkey.io/10.1111/1467-985X.00202?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
    ---><---

    Citations

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


    Cited by:

    1. Emanuele Aliverti & Stefano Mazzuco & Bruno Scarpa, 2022. "Dynamic modelling of mortality via mixtures of skewed distribution functions," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(3), pages 1030-1048, July.
    2. Adrien Remund & Carlo G. Camarda & Tim Riffe, 2018. "A Cause-of-Death Decomposition of Young Adult Excess Mortality," Demography, Springer;Population Association of America (PAA), vol. 55(3), pages 957-978, June.
    3. Mattia Mezzelani & Gloria Polinesi & Francesca Mariani & Maria Cristina Recchioni, 2021. "Longevity-risk-adjusted global age as a measure of well-being," RIEDS - Rivista Italiana di Economia, Demografia e Statistica - The Italian Journal of Economic, Demographic and Statistical Studies, SIEDS Societa' Italiana di Economia Demografia e Statistica, vol. 75(4), pages 28-30, October-D.
    4. Czado, Claudia & Delwarde, Antoine & Denuit, Michel, 2005. "Bayesian Poisson log-bilinear mortality projections," Insurance: Mathematics and Economics, Elsevier, vol. 36(3), pages 260-284, June.
    5. Njenga, Carolyn Ndigwako & Sherris, Michael, 2020. "Modeling mortality with a Bayesian vector autoregression," Insurance: Mathematics and Economics, Elsevier, vol. 94(C), pages 40-57.
    6. David Sharrow & Samuel J. Clark & Mark Collinson & Kathleen Kahn & Stephen Tollman, 2013. "The age pattern of increases in mortality affected by HIV," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 29(39), pages 1039-1096.
    7. Benchimol, Andrés Gustavo & Albarrán Lozano, Irene & Marín Díazaraque, Juan Miguel & Alonso, Pablo J., 2015. "Hierarchical Lee-Carter model estimation through data cloning applied to demographically linked countries," DES - Working Papers. Statistics and Econometrics. WS ws1510, Universidad Carlos III de Madrid. Departamento de Estadística.
    8. Katrien Antonio & Anastasios Bardoutsos & Wilbert Ouburg, 2015. "Bayesian Poisson log-bilinear models for mortality projections with multiple populations," BAFFI CAREFIN Working Papers 1505, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    9. Carolyn Njenga & Michael Sherris, 2011. "Modeling Mortality with a Bayesian Vector Autoregression," Working Papers 201105, ARC Centre of Excellence in Population Ageing Research (CEPAR), Australian School of Business, University of New South Wales.
    10. Miklos Arato, N. & Dryden, Ian L. & Taylor, Charles C., 2006. "Hierarchical Bayesian modelling of spatial age-dependent mortality," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 1347-1363, November.
    11. Wang, Pengjie & Pantelous, Athanasios A. & Vahid, Farshid, 2023. "Multi-population mortality projection: The augmented common factor model with structural breaks," International Journal of Forecasting, Elsevier, vol. 39(1), pages 450-469.
    12. Erengul Dodd & Jonathan J. Forster & Jakub Bijak & Peter W. F. Smith, 2018. "Smoothing mortality data: the English Life Tables, 2010–2012," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 181(3), pages 717-735, June.
    13. Carlo G. Camarda & Ugofilippo Basellini, 2021. "Smoothing, Decomposing and Forecasting Mortality Rates," European Journal of Population, Springer;European Association for Population Studies, vol. 37(3), pages 569-602, July.
    14. Kaishev, Vladimir K. & Dimitrova, Dimitrina S. & Haberman, Steven, 2007. "Modelling the joint distribution of competing risks survival times using copula functions," Insurance: Mathematics and Economics, Elsevier, vol. 41(3), pages 339-361, November.

    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:bla:jorssa:v:164:y:2001:i:2:p:275-291. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/rssssea.html .

    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.