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Heterogeneity of Australian Population Mortality and Implications for a Viable Life Annuity Market

Author

Listed:
  • Shu Su

    (Australian School of Business, University of New South Wales)

  • Michael Sherris

    (School of Risk and Actuarial Studies and ARC Centre of Excellence in Population Ageing Research, Australian School of Business, University of New South Wales)

Abstract

Heterogeneity in mortality rates is known to exist in populations, undermining the use of age and sex as the only rating factors for life insurance and annuity products. Life insurers underwrite life products using a variety of rating factors to allow for this heterogeneity. In the case of life annuities, there is limited underwriting used. Life insurers rely on an assumption that lives will self select and price the longevity risk with an annuity mortality table that assumes above average longevity.

Suggested Citation

  • Shu Su & Michael Sherris, 2011. "Heterogeneity of Australian Population Mortality and Implications for a Viable Life Annuity Market," Working Papers 201103, ARC Centre of Excellence in Population Ageing Research (CEPAR), Australian School of Business, University of New South Wales.
  • Handle: RePEc:asb:wpaper:201103
    as

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    File URL: http://cepar.edu.au/media/48691/Heterogeneity%20of%20Australian%20Population%20Mortality.pdf
    File Function: First version, 2011
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    References listed on IDEAS

    as
    1. Kenneth Manton & Eric Stallard & James Vaupel, 1981. "Methods For Comparing The Mortality Experience of Heterogeneous Populations," Demography, Springer;Population Association of America (PAA), vol. 18(3), pages 389-410, August.
    2. X. Lin & Xiaoming Liu, 2007. "Markov Aging Process and Phase-Type Law of Mortality," North American Actuarial Journal, Taylor & Francis Journals, vol. 11(4), pages 92-109.
    3. James Vaupel & Kenneth Manton & Eric Stallard, 1979. "The impact of heterogeneity in individual frailty on the dynamics of mortality," Demography, Springer;Population Association of America (PAA), vol. 16(3), pages 439-454, August.
    4. Chris Elbers & Geert Ridder, 1982. "True and Spurious Duration Dependence: The Identifiability of the Proportional Hazard Model," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 49(3), pages 403-409.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Longevity risk; mortality heterogeneity; frailty model; Markov ageing model; physiological age; annuity pricing;
    All these keywords.

    JEL classification:

    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies
    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors
    • J11 - Labor and Demographic Economics - - Demographic Economics - - - Demographic Trends, Macroeconomic Effects, and Forecasts
    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions

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