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Predicting Longevity: An Analysis of Potential Alternatives to Life Expectancy Reports

Jiahua Xu and Adrian Hoesch
The Journal of Retirement Spring 2018, 5 (4) 9-24; DOI: https://doi.org/10.3905/jor.2018.5.4.009
Jiahua Xu
is a research associate in the Institute of Insurance Economics at the University of St. Gallen in St. Gallen, Switzerland
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Adrian Hoesch
is a student at Hult International Business School in London, U.K
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Abstract

Retirees, pension funds, and the insurance industry have all been negatively affected by the wrongful estimation of longevity. The inaccuracies in current life expectancy (LE) reports primarily result from misinterpretations of the influence of resilience factors on longevity. This study examines different and more accurate measurement metrics to minimize the risks related to biased LE calculations. By using both qualitative and quantitative research approaches, this research develops a new conceptual model: a two-factor-LE-analysis model with a telomere test as a medical basis (physiological factors) and a big data approach to filter the psychological factors to longevity. The authors suggest that the new model, together with the insights of the existing LE-projection methodologies, has considerable potential to improve LE predictions.

TOPICS: Retirement, risk management, statistical methods

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The Journal of Retirement: 5 (4)
The Journal of Retirement
Vol. 5, Issue 4
Spring 2018
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Predicting Longevity: An Analysis of Potential Alternatives to Life Expectancy Reports
Jiahua Xu, Adrian Hoesch
The Journal of Retirement Apr 2018, 5 (4) 9-24; DOI: 10.3905/jor.2018.5.4.009

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Predicting Longevity: An Analysis of Potential Alternatives to Life Expectancy Reports
Jiahua Xu, Adrian Hoesch
The Journal of Retirement Apr 2018, 5 (4) 9-24; DOI: 10.3905/jor.2018.5.4.009
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  • Article
    • Abstract
    • THE LIFE EXPECTANCY REPORT
    • BIG DATA
    • ALTERNATIVE PREDICTION EXAMPLES FOR LIFE EXPECTANCIES
    • COMBINATION OF MEDICAL AND BIG DATA APPROACH
    • CONCLUSION
    • LIMITATIONS
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