Demographic Research (Nov 2012)
Point and interval forecasts of age-specific life expectancies: A model averaging approach
Abstract
BACKGROUND Any improvement in the forecast accuracy of life expectancy would be beneficial forpolicy decision regarding the allocation of current and future resources. In this paper, Irevisit some methods for forecasting age-specific life expectancies. OBJECTIVE This paper proposes a model averaging approach to produce accurate point forecasts ofage-specific life expectancies. METHODS Illustrated by data from fourteen developed countries, we compare point and interval forecasts among ten principal component methods, two random walk methods, and two univariate time-series methods. RESULTS Based on averaged one-step-ahead and ten-step-ahead forecast errors, random walk withdrift and Lee-Miller methods are the two most accurate methods for producing point forecasts. By combining their forecasts, point forecast accuracy is improved. As measured by averaged coverage probability deviance, the Hyndman-Ullah methods generally providemore accurate interval forecasts than the Lee-Carter methods. However, the Hyndman-Ullah methods produce wider half-widths of prediction interval than the Lee-Carter methods. CONCLUSIONS Model averaging approach should be considered to produce more accurate point forecasts. COMMENTS This study is a sequel to another Demographic Research paper by Shang, Booth and Hyndman (2011), in which the authors compared the principal component methods for forecasting age-specific mortality rates and life expectancy at birth.
