Common mortality modelling and coherent forecasts. An empirical analysis of worldwide mortality data

Hatzopoulos, P. & Haberman, S. (2013). Common mortality modelling and coherent forecasts. An empirical analysis of worldwide mortality data. Insurance: Mathematics and Economics, 52(2), pp. 320-337. doi: 10.1016/j.insmatheco.2013.10.009

Abstract

A 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”.

Publication Type:	Article
Additional Information:	© 2013, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/
Publisher Keywords:	Fuzzy c-means cluster; Generalized linear models; Sparse principal component analysis; Dynamic linear regression; Mortality forecasting; Residuals; Coherent
Subjects:	H Social Sciences > HD Industries. Land use. Labor
Departments:	Bayes Business School > Actuarial Science & Insurance