A comparison of ten principal component methods for forecasting mortality rates

Han Lin Shang, Rob Hyndman and Heather Booth

No 8/10, Monash Econometrics and Business Statistics Working Papers from Monash University, Department of Econometrics and Business Statistics

Abstract: 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.

Keywords: Mortality forecasting; life expectancy forecasting; principal component methods; Lee-Carter method; interval forecasts; forecasting time series (search for similar items in EconPapers)
JEL-codes: C14 C23 (search for similar items in EconPapers)
Pages: 28 pages
Date: 2010-04-09
New Economics Papers: this item is included in nep-age, nep-for and nep-hea
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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