City Research Online

Abstract

We consider a compositional data analysis approach to forecasting the age distribution of death counts. Using the age-specific period life-table death counts in Australia obtained from the Human Mortality Database, the compositional data analysis approach produces more accurate one- to 20-step-ahead point and interval forecasts than Lee-Carter method, Hyndman-Ullah method, and two na¨ıve random walk methods. The improved forecast accuracy of period life-table death counts is of great interest to demographers for estimating survival probabilities and life expectancy, and to actuaries for determining temporary annuity prices for various ages and maturities. Although we focus on temporary annuity prices, we consider long-term contracts which make the annuity almost lifetime, in particular when the age at entry is sufficiently high.

Publication Type:	Article
Additional Information:	This article has been accepted for publication in Annals of Actuarial Sciencehttps://doi.org/10.1017/S1748499519000101. This version is free to view and download for private research and study only. Not for re-distribution or re-use. © Institute and Faculty of Actuaries 2019.
Publisher Keywords:	Compositional data analysis; Life-table death counts; Log-ratio transformation; Principal component analysis; Single-premium temporary annuity
Subjects:	G Geography. Anthropology. Recreation > GN Anthropology H Social Sciences > HG Finance
Departments:	Bayes Business School > Actuarial Science & Insurance
SWORD Depositor:	Symplectic Administrator

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