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Beyond the Kannisto-Thatcher Database on Old Age Mortality: an assessment of data quality at advanced ages

Author

Listed:
  • Dmitri A. Jdanov

    (Max Planck Institute for Demographic Research, Rostock, Germany)

  • Domantas Jasilionis

    (Max Planck Institute for Demographic Research, Rostock, Germany)

  • Eugeny L. Soroko

    (Max Planck Institute for Demographic Research, Rostock, Germany)

  • Roland Rau

    (Max Planck Institute for Demographic Research, Rostock, Germany)

  • James W. Vaupel

    (Max Planck Institute for Demographic Research, Rostock, Germany)

Abstract

The old age population in developed countries has been increasing remarkably, yet internationally comparable high quality data on oldest-old mortality remain relatively scarce. The Kannisto-Thatcher Old Age Mortality Database (KTD) is a unique source providing uniformly recalculated old-age mortality data for 35 countries. Our study addresses a number of data quality issues relevant to population and death statistics at the most advanced ages. Following previous studies by Väinö Kannisto, we apply the same set of measures. This allows us to identify dubious or irregular mortality patterns. Deviations such as this often suggest that the data quality has serious problems. We update previously published findings by extending the analyses made so far to thirty five countries and by adding data on longer historical periods. In addition, we propose a systematic classification of country- and period-specific data, thus simultaneously accounting for each indicator of data quality. We apply conventional procedures of hierarchical cluster analysis to distinguish four data quality clusters (best data quality, acceptable data quality, conditionally acceptable quality, and weak quality). We show that the reliability of old-age mortality estimates has been improving in time. However, the mortality indicators for the most advanced ages of a number of countries, such as Chile, Canada, and the USA should be treated with caution even for the most recent decade. Canada, Ireland, Finland, Lithuania, New Zealand (Non-Maori), Norway, Portugal, Spain, and the USA have particular problems in their historical data series. After having compared the KTD with official data, we conclude that the methods used for extinct and almost extinct generations produce more accurate population estimates than those published by national statistical offices. The most reliable official data come from the countries with fully functioning population registers.

Suggested Citation

  • 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.
    • Handle: RePEc:dem:wpaper:wp-2008-013
    DOI: 10.4054/MPIDR-WP-2008-013
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    References listed on IDEAS

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    1. 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.
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    5. 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.
    6. James W. Vaupel & Roland Rau & Carlo Giovanni Camarda & Kristin G. von Kistowski, 2006. "Can Heterogeneity of Populations Explain Differences in Mortality?," Working Papers, Center for Retirement Research at Boston College wp2006-10, Center for Retirement Research.
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    10. Ira Rosenwaike, 1979. "A new evaluation of United States census data on the extreme aged," Demography, Springer;Population Association of America (PAA), vol. 16(2), pages 279-288, May.
    11. 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.
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    Cited by:

    1. Jackie Li & Jia Liu, 2020. "A modified extreme value perspective on best-performance life expectancy," Journal of Population Research, Springer, vol. 37(4), pages 345-375, December.
    2. Dana Glei & Andres Barajas Paz & Jose Manuel Aburto & Magali Barbieri, 2021. "Mexican mortality 1990‒2016: Comparison of unadjusted and adjusted estimates," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 44(30), pages 719-758.
    3. 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.
    4. Olga Penina & Dmitri A. Jdanov & Pavel Grigoriev, 2015. "Producing reliable mortality estimates in the context of distorted population statistics: the case of Moldova," MPIDR Working Papers WP-2015-011, Max Planck Institute for Demographic Research, Rostock, Germany.
    5. Marília R. Nepomuceno & Cássio M. Turra, 2020. "The Population of Centenarians in Brazil: Historical Estimates from 1900 to 2000," Population and Development Review, The Population Council, Inc., vol. 46(4), pages 813-833, December.
    6. Baten, Joerg & Llorca-Jaña, Manuel, 2021. "Inequality, low-intensity immigration and human capital formation in the regions of Chile, 1820-1939," Economics & Human Biology, Elsevier, vol. 43(C).
    7. 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.
    8. Jia Liu & Jackie Li, 2019. "Beyond the highest life expectancy: construction of proxy upper and lower life expectancy bounds," Journal of Population Research, Springer, vol. 36(2), pages 159-181, June.
    9. Magali Barbieri, 2018. "Investigating the Difference in Mortality Estimates between the Social Security Administration Trustees' Report and the Human Mortality Database," Working Papers wp394, University of Michigan, Michigan Retirement Research Center.
    10. Dennis M. Feehan, 2018. "Separating the Signal From the Noise: Evidence for Deceleration in Old-Age Death Rates," Demography, Springer;Population Association of America (PAA), vol. 55(6), pages 2025-2044, December.

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    More about this item

    Keywords

    World; data evaluation; mortality; old age;
    All these keywords.

    JEL classification:

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

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