IDEAS home Printed from https://ideas.repec.org/a/dem/demres/v6y2002i1.html
   My bibliography  Save this article

The Survivor Ratio Method for Estimating Numbers at High Ages

Author

Listed:
  • A. Roger Thatcher

    (Office for National Statistics)

  • Väinö Kannisto

    (Max-Planck-Institut für Demografische Forschung)

  • Kirill F. Andreev

    (United Nations)

Abstract

Only a few countries have official population statistics which are sufficiently accurate to produce reliable estimates of death rates at high ages. For other countries, there are several methods which can be used to produce improved estimates. The choice is important for research on old age mortality. In 1999 the Max Planck Institute for Demographic Research undertook a research project to compare the performance of the three leading methods, using data for nine countries over 35 years. This paper describes the research and the results, which were unexpectedly simple. It also gives an authoritative account of the most successful method.

Suggested Citation

  • A. Roger Thatcher & Väinö Kannisto & Kirill F. Andreev, 2002. "The Survivor Ratio Method for Estimating Numbers at High Ages," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 6(1), pages 1-18.
  • Handle: RePEc:dem:demres:v:6:y:2002:i:1
    DOI: 10.4054/DemRes.2002.6.1
    as

    Download full text from publisher

    File URL: https://www.demographic-research.org/volumes/vol6/1/6-1.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.4054/DemRes.2002.6.1?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. Andrew J. G. Cairns & David Blake & Kevin Dowd & Amy R. Kessler, 2016. "Phantoms never die: living with unreliable population data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 179(4), pages 975-1005, October.
    2. Kirill F. Andreev, 2004. "A Method for Estimating Size of Population Aged 90 and over with Application to the U.S. Census 2000 Data," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 11(9), pages 235-262.
    3. T. Gudaitis & A. Fiori Maccioni, 2014. "Optimal Individual Choice of Contribution to Second Pillar Pension System in Lithuania," Working Paper CRENoS 201402, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    4. Tom Wilson & Jeromey Temple, 2020. "The rapid growth of Australia’s advanced age population," Journal of Population Research, Springer, vol. 37(4), pages 377-389, December.
    5. A. Fiori Maccioni & A. Bitinas, 2013. "Lithuanian pension system's reforms following demographic and social transitions," Working Paper CRENoS 201315, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    6. Roland Rau & Eugeny Soroko & Domantas Jasilionis & James W. Vaupel, 2008. "Continued Reductions in Mortality at Advanced Ages," Population and Development Review, The Population Council, Inc., vol. 34(4), pages 747-768, December.
    7. Alessandro Fiori Maccioni, 2011. "A Stochastic Model for the Analysis of Demographic Risk in Pay-As-You-Go Pension Funds," Papers 1106.5081, arXiv.org.
    8. Dmitri A. Jdanov & Rembrandt D. Scholz & Vladimir Shkolnikov, 2005. "Official population statistics and the Human Mortality Database estimates of populations aged 80+ in Germany and nine other European countries," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 13(14), pages 335-362.
    9. Wang, Hsin-Chung & Yue, Ching-Syang Jack & Chong, Chen-Tai, 2018. "Mortality models and longevity risk for small populations," Insurance: Mathematics and Economics, Elsevier, vol. 78(C), pages 351-359.
    10. Dana Glei & Magali Barbieri & Carolina Santamaría-Ulloa, 2019. "Costa Rican mortality 1950‒2013: An evaluation of data quality and trends compared with other countries," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 40(29), pages 835-864.
    11. Dmitri A. Jdanov & Domantas Jasilionis & Eugeny L. Soroko & Roland Rau & James W. Vaupel, 2008. "Beyond the Kannisto-Thatcher Database on Old Age Mortality: an assessment of data quality at advanced ages," MPIDR Working Papers WP-2008-013, Max Planck Institute for Demographic Research, Rostock, Germany.
    12. Rembrandt D. Scholz & Heiner Maier, 2003. "German unification and the plasticity of mortality at older ages," MPIDR Working Papers WP-2003-031, Max Planck Institute for Demographic Research, Rostock, Germany.
    13. Tom Wilson & Martin Bell, 2004. "Australia's uncertain demographic future," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 11(8), pages 195-234.
    14. Dmitri A. Jdanov & Rembrandt D. Scholz & Vladimir M. Shkolnikov, 2005. "Official population statistics and the Human Mortality Database estimates of populations aged 80+ in Germany and nine other European countries," MPIDR Working Papers WP-2005-010, Max Planck Institute for Demographic Research, Rostock, Germany.
    15. Marilia Miranda Fortes Gomes & Cássio M. Turra, 2009. "The number of centenarians in Brazil: Indirect estimates based on death certificates," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 20(20), pages 495-502.
    16. Sergey Timonin & Inna Danilova & Evgeny Andreev & Vladimir M. Shkolnikov, 2017. "Recent Mortality Trend Reversal in Russia: Are Regions Following the Same Tempo?," European Journal of Population, Springer;European Association for Population Studies, vol. 33(5), pages 733-763, December.

    More about this item

    Keywords

    estimation techniques; survivor ratio; population estimates; high ages;
    All these keywords.

    JEL classification:

    • J1 - Labor and Demographic Economics - - Demographic Economics
    • Z0 - Other Special Topics - - General

    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:dem:demres:v:6:y:2002:i:1. 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: Editorial Office (email available below). General contact details of provider: https://www.demogr.mpg.de/ .

    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.