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Constrained Mortality Extrapolation to Old Age: An Empirical Assessment

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  • Dalkhat M. Ediev

    (International Institute for Applied Systems Analysis
    North-Caucasian State Humanitarian-Technological Academy
    Lomonosov Moscow State University)

Abstract

This paper aims to improve the accuracy of parametric extrapolations of the death rates into old age by constraining the extrapolation model on presumed life expectancy at old age. Such a task is particularly important in cases where the data quality at old age, in particular the age exaggeration, is not sufficient for reliable mortality estimates. Our tests are based on period data from the Human Mortality Database and the use of the Horiuchi–Coale and Mitra formulas for reducing the bias of life expectancy in the open age interval. We show that extrapolation accuracy is substantially improved when the extrapolation is constrained by either the empirical life expectancy or the Horiuchi–Coale or Mitra estimates. Unconstrained extrapolations and those constrained by conventional life table estimates of life expectancy in the open age interval show substantial biases and should be avoided. Combining extrapolation with life expectancy estimates which are robust to the effects of age exaggeration appears to be a valuable way of improving mortality estimation.

Suggested Citation

  • Dalkhat M. Ediev, 2018. "Constrained Mortality Extrapolation to Old Age: An Empirical Assessment," European Journal of Population, Springer;European Association for Population Studies, vol. 34(3), pages 441-457, August.
    • Handle: RePEc:spr:eurpop:v:34:y:2018:i:3:d:10.1007_s10680-017-9434-4
    DOI: 10.1007/s10680-017-9434-4
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    References listed on IDEAS

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    1. Trifon I Missov & László Németh & Maciej J Dańko, 2016. "How much can we trust life tables? Sensitivity of mortality measures to right-censoring treatment," Palgrave Communications, Palgrave Macmillan, vol. 2(1), pages 1-10, December.
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    3. Camarda, Carlo G., 2012. "MortalitySmooth: An R Package for Smoothing Poisson Counts with P-Splines," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 50(i01).
    4. Sergei Scherbov & Dalkhat Ediev, 2011. "Significance of life table estimates for small populations: Simulation-based study of estimation errors," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 24(22), pages 527-550.
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    Cited by:

    1. Filipe Costa Souza & Wilton Bernardino & Silvio C. Patricio, 2024. "How life-table right-censoring affected the Brazilian social security factor: an application of the gamma-Gompertz-Makeham model," Journal of Population Research, Springer, vol. 41(3), pages 1-38, September.
    2. Yassmin Ali & Ming Fang & Pablo A. Arrutia Sota & Stephen Taylor & Xun Wang, 2019. "Social Security Benefit Valuation, Risk, and Optimal Retirement," Risks, MDPI, vol. 7(4), pages 1-31, December.

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