point and interval forecasts of mortality rates and life expectancy: a comparison of ten principal component methods

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2011
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Abstract
Using the age- and sex-specific data of 14 developed countries, we compare the point and interval forecast accuracy and bias of ten principal component methods for forecasting mortality rates and life expectancy. The ten methods are variants and extensions of the Lee-Carter method. Based on one-step forecast errors, the weighted Hyndman-Ullah method provides the most accurate point forecasts of mortality rates and the Lee-Miller method is the least biased. For the accuracy and bias of life expectancy, the weighted Hyndman-Ullah method performs the best for female mortality and the Lee-Miller method for male mortality. While all methods underestimate variability in mortality rates, the more complex Hyndman-Ullah methods are more accurate than the simpler methods. The weighted Hyndman-Ullah method provides the most accurate interval forecasts for mortality rates, while the robust Hyndman-Ullah method provides the best interval forecast accuracy for life expectancy.
Reference Key
shang2011demographicpoint Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Han Lin Shang;Heather Booth;Rob Hyndman
Journal journal of urban planning and development
Year 2011
DOI
DOI not found
URL
http://www.demographic-research.org/volumes/vol25/5/
Keywords
life expectancy forecasting mortality forecasting population vital events principal components analysisdemography

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