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The Longevity Prospects of Australian Seniors: An Evaluation of Forecast Method and Outcome

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  • Tickle Leonie

    (Department of Applied Finance and Actuarial Studies, Macquarie University, Herring Road North Ryde, Sydney, NSW 2109, Australia)

  • Booth Heather

    (Australian Demographic and Social Research Institute, Australian National University, Canberra, NSW, Australia)

Abstract

Continuing rapid changes in the level and pattern of mortality require that forecasts are available that are timely, relevant and reliable. This paper evaluates a previous forecast of the mortality and longevity of Australian seniors, both in terms of the validity of the chosen method – the Booth–Maindonald–Smith (BMS) variant of Lee–Carter – and the accuracy and reliability of the forecast itself. The validity of the method is assessed by a comprehensive review and evaluation of available methods, confirming BMS as the method of choice. The accuracy and reliability of the forecast is assessed by comparing it with actual experience and with a new forecast of period and cohort survival probabilities and life expectancies. The evaluation and the current forecast itself will inform the actuarial profession and wider industry in the areas of mortality and longevity risk as well as public debate and policy in population health and ageing.

Suggested Citation

  • Tickle Leonie & Booth Heather, 2014. "The Longevity Prospects of Australian Seniors: An Evaluation of Forecast Method and Outcome," Asia-Pacific Journal of Risk and Insurance, De Gruyter, vol. 8(2), pages 1-34, July.
  • Handle: RePEc:bpj:apjrin:v:8:y:2014:i:2:p:34:n:1
    DOI: 10.1515/apjri-2013-0004
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    References listed on IDEAS

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    1. Andrew Cairns & David Blake & Kevin Dowd & Guy Coughlan & David Epstein & Alen Ong & Igor Balevich, 2009. "A Quantitative Comparison of Stochastic Mortality Models Using Data From England and Wales and the United States," North American Actuarial Journal, Taylor & Francis Journals, vol. 13(1), pages 1-35.
    2. Murphy, M.J., 1995. "The Prospect of Mortality: England and Wales and the United States of America, 1962–1989," British Actuarial Journal, Cambridge University Press, vol. 1(2), pages 331-350, June.
    3. Rui Zhou & Johnny Siu-Hang Li & Ken Seng Tan, 2013. "Pricing Standardized Mortality Securitizations: A Two-Population Model With Transitory Jump Effects," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 80(3), pages 733-774, September.
    4. Rob Hyndman & Heather Booth & Farah Yasmeen, 2013. "Coherent Mortality Forecasting: The Product-Ratio Method With Functional Time Series Models," Demography, Springer;Population Association of America (PAA), vol. 50(1), pages 261-283, February.
    5. Sithole, Terry Z. & Haberman, Steven & Verrall, Richard J., 2000. "An investigation into parametric models for mortality projections, with applications to immediate annuitants' and life office pensioners' data," Insurance: Mathematics and Economics, Elsevier, vol. 27(3), pages 285-312, December.
    6. Haberman, Steven & Renshaw, Arthur, 2013. "Modelling and projecting mortality improvement rates using a cohort perspective," Insurance: Mathematics and Economics, Elsevier, vol. 53(1), pages 150-168.
    7. Cesare, Mariachiara Di & Murphy, Mike, 2009. "Forecasting Mortality, Different Approaches for Different Cause of Deaths? The Cases of Lung Cancer; Influenza, Pneumonia, and Bronchitis; and Motor Vehicle Accidents," British Actuarial Journal, Cambridge University Press, vol. 15(S1), pages 185-211, January.
    8. Jackie Li, 2013. "A Poisson common factor model for projecting mortality and life expectancy jointly for females and males," Population Studies, Taylor & Francis Journals, vol. 67(1), pages 111-126, March.
    9. Sam Gutterman & Irwin Vanderhoof, 1998. "Forecasting Changes in Mortality," North American Actuarial Journal, Taylor & Francis Journals, vol. 2(4), pages 135-138.
    10. McNown, Robert & Rogers, Andrei, 1992. "Forecasting cause-specific mortality using time series methods," International Journal of Forecasting, Elsevier, vol. 8(3), pages 413-432, November.
    11. Shripad Tuljapurkar & Carl Boe, 1998. "Mortality Change and Forecasting," North American Actuarial Journal, Taylor & Francis Journals, vol. 2(4), pages 13-47.
    12. 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.
    13. Brouhns, Natacha & Denuit, Michel & Vermunt, Jeroen K., 2002. "A Poisson log-bilinear regression approach to the construction of projected lifetables," Insurance: Mathematics and Economics, Elsevier, vol. 31(3), pages 373-393, December.
    14. Renshaw, A.E. & Haberman, S. & Hatzopoulos, P., 1996. "The Modelling of Recent Mortality Trends in United Kingdom Male Assured Lives," British Actuarial Journal, Cambridge University Press, vol. 2(2), pages 449-477, June.
    15. Dimitrova, Dimitrina S. & Haberman, Steven & Kaishev, Vladimir K., 2013. "Dependent competing risks: Cause elimination and its impact on survival," Insurance: Mathematics and Economics, Elsevier, vol. 53(2), pages 464-477.
    16. Carlos Wong-Fupuy & Steven Haberman, 2004. "Projecting Mortality Trends," North American Actuarial Journal, Taylor & Francis Journals, vol. 8(2), pages 56-83.
    17. Shripad Tuljapurkar, 1998. "Forecasting Mortality Change," North American Actuarial Journal, Taylor & Francis Journals, vol. 2(4), pages 127-134.
    18. 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.
    19. Andrew J. G. Cairns & David Blake & Kevin Dowd, 2006. "A Two‐Factor Model for Stochastic Mortality with Parameter Uncertainty: Theory and Calibration," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 73(4), pages 687-718, December.
    20. Nan Li & Ronald Lee, 2005. "Coherent mortality forecasts for a group of populations: An extension of the lee-carter method," Demography, Springer;Population Association of America (PAA), vol. 42(3), pages 575-594, August.
    21. Colin D Mathers & Dejan Loncar, 2006. "Projections of Global Mortality and Burden of Disease from 2002 to 2030," PLOS Medicine, Public Library of Science, vol. 3(11), pages 1-20, November.
    22. Shripad Tuljapurkar & Carl Boe, "undated". "Mortality Change and Forecasting: How Much and How Little Do We Know?," Pension Research Council Working Papers 98-2, Wharton School Pension Research Council, University of Pennsylvania.
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