 Mortality and Life Expectancy Forecasting for a Group of Populations in Developed Countries: A Robust Multilevel Functional Data MethodA chapter in Recent Advances in Robust Statistics: Theory and Applications, 2016, pp 169-184 from Springer Abstract: Abstract A robust multilevel functional data method is proposed to forecast age-specific mortality rate and life expectancy for two or more populations in developed countries with high-quality vital registration systems. It uses a robust multilevel functional principal component analysis of aggregate and population-specific data to extract the common trend and population-specific residual trend among populations. This method is applied to age- and sex-specific mortality rate and life expectancy for the United Kingdom from 1922 to 2011, and its forecast accuracy is then further compared with standard multilevel functional data method. For forecasting both age-specific mortality and life expectancy, the robust multilevel functional data method produces more accurate point and interval forecasts than the standard multilevel functional data method in the presence of outliers. Keywords: Markov Chain Monte Carlo; Forecast Error; Prediction Interval; Forecast Accuracy; Functional Principal Component Analysis (search for similar items in EconPapers) There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it. Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-81-322-3643-6_9 Ordering information: This item can be ordered from DOI: 10.1007/978-81-322-3643-6_9 Access Statistics for this chapter More chapters in Springer Books from Springer |
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