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Forecasting mortality for small populations by mixing mortality data

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  • Ahcan, Ales
  • Medved, Darko
  • Olivieri, Annamaria
  • Pitacco, Ermanno

Abstract

In this paper we address the problem of projecting mortality when data are severely affected by random fluctuations, due in particular to a small sample size, or when data are scanty. Such situations may emerge when dealing with small populations, such as small countries (possibly previously part of a larger country), a specific geographic area of a (large) country, a life annuity portfolio or a pension fund, or when the investigation is restricted to the oldest ages. The critical issues arising from the volatility of data due to the small sample size (especially at the highest ages) may be made worse by missing records; this is the case, for example, of a small country previously part of a larger country, or a specific geographic area of a country, given that in some periods mortality data could have been collected just at an aggregate level.

Suggested Citation

  • Ahcan, Ales & Medved, Darko & Olivieri, Annamaria & Pitacco, Ermanno, 2014. "Forecasting mortality for small populations by mixing mortality data," Insurance: Mathematics and Economics, Elsevier, vol. 54(C), pages 12-27.
  • Handle: RePEc:eee:insuma:v:54:y:2014:i:c:p:12-27 DOI: 10.1016/j.insmatheco.2013.10.013
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    References listed on IDEAS

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    1. 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.
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    1. repec:eee:insuma:v:75:y:2017:i:c:p:151-165 is not listed on IDEAS

    More about this item

    Keywords

    Mortality projections; Mortality trends; Multi-population mortality models;

    JEL classification:

    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies

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