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Mortality and Life Expectancy Forecasting for a Group of Populations in Developed Countries: A Robust Multilevel Functional Data Method

In: Recent Advances in Robust Statistics: Theory and Applications

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  • Han Lin Shang

    (Australian National University, Research School of Finance, Actuarial Studies and Statistics)

Abstract

A robust multilevel functional data method is proposed to forecast age-specific mortality rate and life expectancy for two or more populations in developed countries with high-quality vital registration systems. It uses a robust multilevel functional principal component analysis of aggregate and population-specific data to extract the common trend and population-specific residual trend among populations. This method is applied to age- and sex-specific mortality rate and life expectancy for the United Kingdom from 1922 to 2011, and its forecast accuracy is then further compared with standard multilevel functional data method. For forecasting both age-specific mortality and life expectancy, the robust multilevel functional data method produces more accurate point and interval forecasts than the standard multilevel functional data method in the presence of outliers.

Suggested Citation

  • Han Lin Shang, 2016. "Mortality and Life Expectancy Forecasting for a Group of Populations in Developed Countries: A Robust Multilevel Functional Data Method," Springer Books, in: Claudio Agostinelli & Ayanendranath Basu & Peter Filzmoser & Diganta Mukherjee (ed.), Recent Advances in Robust Statistics: Theory and Applications, pages 169-184, Springer.
    • Handle: RePEc:spr:sprchp:978-81-322-3643-6_9
    DOI: 10.1007/978-81-322-3643-6_9
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