IDEAS home Printed from https://ideas.repec.org/a/bla/jorssa/v181y2018i3p717-735.html
   My bibliography  Save this article

Smoothing mortality data: the English Life Tables, 2010–2012

Author

Listed:
  • Erengul Dodd
  • Jonathan J. Forster
  • Jakub Bijak
  • Peter W. F. Smith

Abstract

We describe the most recent statistical methodology used to produce the 17th English Life Table, covering the period 2010–2012. Crude mortality rates are smoothed, or graduated, by using a combination of a generalized additive model and low dimensional parametric models. The approach to graduation acknowledges uncertainty, particularly in the highest age groups, by model averaging, using a simplified version of a full Bayesian analysis.

Suggested Citation

  • 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.
    • Handle: RePEc:bla:jorssa:v:181:y:2018:i:3:p:717-735
    DOI: 10.1111/rssa.12309
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/rssa.12309
    Download Restriction: no
    File URL: https://libkey.io/10.1111/rssa.12309?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
    ---><---

    References listed on IDEAS

    as
    1. Martin Feldkircher, 2012. "Forecast Combination and Bayesian Model Averaging: A Prior Sensitivity Analysis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 31(4), pages 361-376, July.
    2. A. R. Thatcher, 1999. "The long‐term pattern of adult mortality and the highest attained age," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 162(1), pages 5-43.
    3. Jana Eklund & Sune Karlsson, 2007. "Forecast Combination and Model Averaging Using Predictive Measures," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 329-363.
    4. Ghosh, Pulak & Basu, Sanjib & Tiwari, Ram C., 2009. "Bayesian Analysis of Cancer Rates From SEER Program Using Parametric and Semiparametric Joinpoint Regression Models," Journal of the American Statistical Association, American Statistical Association, vol. 104(486), pages 439-452.
    5. 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.
    6. Bradley P. Carlin & Alan E. Gelfand & Adrian F. M. Smith, 1992. "Hierarchical Bayesian Analysis of Changepoint Problems," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 41(2), pages 389-405, June.
    7. S. Olshansky & Bruce Carnes, 1997. "Ever since gompertz," Demography, Springer;Population Association of America (PAA), vol. 34(1), pages 1-15, February.
    8. James Vaupel & Kenneth Manton & Eric Stallard, 1979. "The impact of heterogeneity in individual frailty on the dynamics of mortality," Demography, Springer;Population Association of America (PAA), vol. 16(3), pages 439-454, August.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Jose Valderrama & Javier Olivera, 2023. "The effects of social pensions on mortality among the extreme poor elderly," LISER Working Paper Series 2023-05, Luxembourg Institute of Socio-Economic Research (LISER).
    2. Jose A. Valderrama & Javier Olivera, 2023. "The effects of social pensions on mortality among the extreme poor elderly," Documentos de Trabajo / Working Papers 2023-525, Departamento de Economía - Pontificia Universidad Católica del Perú.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Pitacco, Ermanno, 2004. "Survival models in a dynamic context: a survey," Insurance: Mathematics and Economics, Elsevier, vol. 35(2), pages 279-298, October.
    2. Huang, Fei & Maller, Ross & Ning, Xu, 2020. "Modelling life tables with advanced ages: An extreme value theory approach," Insurance: Mathematics and Economics, Elsevier, vol. 93(C), pages 95-115.
    3. Booth, Heather, 2006. "Demographic forecasting: 1980 to 2005 in review," International Journal of Forecasting, Elsevier, vol. 22(3), pages 547-581.
    4. Annamaria Olivieri & Ermanno Pitacco, 2016. "Frailty and Risk Classification for Life Annuity Portfolios," Risks, MDPI, vol. 4(4), pages 1-23, October.
    5. M S Finkelstein, 2008. "Reliability modelling for biological ageing," Journal of Risk and Reliability, , vol. 222(1), pages 1-6, March.
    6. Ting Li & James Anderson, 2013. "Shaping human mortality patterns through intrinsic and extrinsic vitality processes," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 28(12), pages 341-372.
    7. Anders Ledberg, 2020. "Exponential increase in mortality with age is a generic property of a simple model system of damage accumulation and death," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-17, June.
    8. Martin Feldkircher & Florian Huber & Josef Schreiner & Marcel Tirpák & Peter Tóth & Julia Wörz, 2015. "Bridging the information gap: small-scale nowcasting models of GDP growth for selected CESEE countries," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue 2, pages 56-75.
    9. Maxim S. Finkelstein, 2009. "Understanding the shape of the mixture failure rate (with engineering and demographic applications)," MPIDR Working Papers WP-2009-031, Max Planck Institute for Demographic Research, Rostock, Germany.
    10. Maxim S. Finkelstein, 2011. "On ordered subpopulations and population mortality at advanced ages," MPIDR Working Papers WP-2011-022, Max Planck Institute for Demographic Research, Rostock, Germany.
    11. Maxim S. Finkelstein & Veronica Esaulova, 2005. "On mixture failure rate ordering," MPIDR Working Papers WP-2005-019, Max Planck Institute for Demographic Research, Rostock, Germany.
    12. Ghosh, Pulak & Huang, Lan & Yu, Binbing & Tiwari, Ram C., 2009. "Semiparametric Bayesian approaches to joinpoint regression for population-based cancer survival data," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 4073-4082, October.
    13. A. Roger Thatcher & Siu Lan Karen Cheung & Shiro Horiuchi & Jean-Marie Robine, 2010. "The compression of deaths above the mode," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 22(17), pages 505-538.
    14. Zeugner, Stefan & Feldkircher, Martin, 2015. "Bayesian Model Averaging Employing Fixed and Flexible Priors: The BMS Package for R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 68(i04).
    15. Camarda, Carlo Giovanni, 2022. "The curse of the plateau. Measuring confidence in human mortality estimates at extreme ages," Theoretical Population Biology, Elsevier, vol. 144(C), pages 24-36.
    16. Martin Feldkircher & Florian Huber & Josef Schreiner & Julia Woerz & Marcel Tirpak & Peter Toth, 2015. "Small-scale nowcasting models of GDP for selected CESEE countries," Working and Discussion Papers WP 4/2015, Research Department, National Bank of Slovakia.
    17. W.J. Willemse & R. Kaas, 2007. "Rational reconstruction of frailty-based mortality models by a generalisation of Gompertz' law of mortality," DNB Working Papers 135, Netherlands Central Bank, Research Department.
    18. Hans Oluf Hansen, 2015. "Modeling and projecting mortality. A new model of heterogeneity and selection in survivorship," Discussion Papers 15-16, University of Copenhagen. Department of Economics.
    19. Maxim S. Finkelstein, 2006. "On engineering reliability concepts and biological aging," MPIDR Working Papers WP-2006-021, Max Planck Institute for Demographic Research, Rostock, Germany.
    20. Kenneth Manton & Igor Akushevich & Alexander Kulminski, 2008. "Human Mortality at Extreme Ages: Data from the NLTCS and Linked Medicare Records," Mathematical Population Studies, Taylor & Francis Journals, vol. 15(3), pages 137-159.

    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:181:y:2018:i:3:p:717-735. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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.