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A comparison of ten principal component methods for forecasting mortality rates

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journal contribution
posted on 2022-11-01, 04:49 authored by Han Lin Shang, Heather Booth, Rob J HyndmanRob J Hyndman
Using the age- and sex-specific data of 14 developed countries, we compare the short- to medium-term accuracy of ten principal component methods for forecasting mortality rates and life expectancy. These ten methods include the Lee-Carter method and many of its variants and extensions. For forecasting mortality rates, the weighted Hyndman-Ullah method provides the most accurate point forecasts, while the Lee-Miller method gives the best point forecast accuracy of life expectancy. Furthermore, the weighted Hyndman-Ullah method provides the most accurate interval forecasts of mortality rates, while the robust Hyndman-Ullah method provides the best interval forecast accuracy of life expectancy.

History

Classification-JEL

C14, C23

Creation date

2010-04-09

Working Paper Series Number

8/10

Length

28 pages

File-Format

application/pdf

Handle

RePEc:msh:ebswps:2010-8