Common mortality modeling and coherent forecasts. An empirical analysis of worldwide mortality data
AbstractA new common mortality modeling structure is presented for analyzing mortality dynamics for a pool of countries, under the framework of generalized linear models (GLM). The countries are first classified by fuzzy c-means cluster analysis in order to construct the common sparse age-period model structure for the mortality experience. Next, we propose a method to create the common sex difference age-period model structure and then use this to produce the residual age-periodmodel structure for each country and sex. The time related principal components are extrapolated using dynamic linear regression (DLR) models and coherent mortality forecasts are investigated. We make use of mortality data from the “Human Mortality Database”.
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Bibliographic InfoArticle provided by Elsevier in its journal Insurance: Mathematics and Economics.
Volume (Year): 52 (2013)
Issue (Month): 2 ()
Contact details of provider:
Web page: http://www.elsevier.com/locate/inca/505554
Fuzzy c-means cluster; Generalized linear models; Sparse principal component analysis; Dynamic linear regression; Mortality forecasting; Residuals; Coherent;
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