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Point and interval forecasts of age-specific life expectancies


  • Han Lin Shang

    (Australian National University)


This paper considers forecasting life table, and proposes a model averaging approach to improve point and interval forecast accuracy. Illustrated by data of eleven countries, we compare point and interval forecasts among ten principal component and two random walk methods. Based on averaged forecast errors, random walk with drift and Lee-Miller methods are two most accurate methods for producing point forecasts. By combining their forecasts, point forecast accuracy is improved. As measured by averaged coverage probability deviance, Hyndman-Ullah methods provide more accurate interval forecasts than Lee-Carter methods. By combining forecasts from two most accurate methods, interval forecast accuracy is improved.

Suggested Citation

  • Han Lin Shang, 2012. "Point and interval forecasts of age-specific life expectancies," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 27(21), pages 593-644, November.
  • Handle: RePEc:dem:demres:v:27:y:2012:i:21

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    References listed on IDEAS

    1. Heather Booth & Rob Hyndman & Leonie Tickle & Piet de Jong, 2006. "Lee-Carter mortality forecasting: a multi-country comparison of variants and extensions," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 15(9), pages 289-310, October.
    2. Hyndman, Rob J. & Khandakar, Yeasmin, 2008. "Automatic Time Series Forecasting: The forecast Package for R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i03).
    3. Hyndman, Rob J. & Shahid Ullah, Md., 2007. "Robust forecasting of mortality and fertility rates: A functional data approach," Computational Statistics & Data Analysis, Elsevier, vol. 51(10), pages 4942-4956, June.
    4. Clemen, Robert T., 1989. "Combining forecasts: A review and annotated bibliography," International Journal of Forecasting, Elsevier, vol. 5(4), pages 559-583.
    5. Han Lin Shang & Heather Booth & Rob Hyndman, 2011. "Point and interval forecasts of mortality rates and life expectancy: A comparison of ten principal component methods," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 25(5), pages 173-214, July.
    6. Alho, Juha M., 1990. "Stochastic methods in population forecasting," International Journal of Forecasting, Elsevier, vol. 6(4), pages 521-530, December.
    7. Ronald Lee & Timothy Miller, 2001. "Evaluating the performance of the lee-carter method for forecasting mortality," Demography, Springer;Population Association of America (PAA), vol. 38(4), pages 537-549, November.
    8. Hyndman, Rob J. & Booth, Heather, 2008. "Stochastic population forecasts using functional data models for mortality, fertility and migration," International Journal of Forecasting, Elsevier, vol. 24(3), pages 323-342.
    9. Carter, Lawrence R. & Lee, Ronald D., 1992. "Modeling and forecasting US sex differentials in mortality," International Journal of Forecasting, Elsevier, vol. 8(3), pages 393-411, November.
    10. Rowland, Donald T., 2003. "Demographic Methods and Concepts," OUP Catalogue, Oxford University Press, number 9780198752639.
    11. Arthur Renshaw & Steven Haberman, 2003. "Lee-Carter mortality forecasting: a parallel generalized linear modelling approach for England and Wales mortality projections," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 52(1), pages 119-137.
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    Cited by:

    1. Shang, Han Lin & Smith, Peter W.F. & Bijak, Jakub & Wiƛniowski, Arkadiusz, 2016. "A multilevel functional data method for forecasting population, with an application to the United Kingdom," International Journal of Forecasting, Elsevier, vol. 32(3), pages 629-649.

    More about this item


    Booth-Maindonald-Smith method; functional data analysis; Hyndman-Ullah method; Lee-Carter model; Lee-Miller method; principal components analysis;

    JEL classification:

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


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