Article2017

Forecasting mortality rate by multivariate singular spectrum analysis

Rahim Mahmoudvand · Dimitrios G. Konstantinides · Paulo Canas Rodrigues

25 citations0/0 files storedApplied Stochastic Models in Business and Industry

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Insurance, Mortality, Demography, Risk Management Forecasting Techniques and Applications Statistical and numerical algorithms

Abstract

In this paper, we investigate the possibility of using multivariate singular spectrum analysis (SSA), a nonparametric technique in the field of time series analysis, for mortality forecasting. We consider a real data application with 9 European countries: Belgium, Denmark, Finland, France, Italy, Netherlands, Norway, Sweden, and Switzerland, over a period 1900 to 2009, and a simulation study based on the data set. The results show the superiority of multivariate SSA in comparison with the univariate SSA, in terms of forecasting accuracy.

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References

1992Modeling and Forecasting U. S. Mortality 2006Robust forecasting of mortality and fertility rates: A functional data approach 2009A Quantitative Comparison of Stochastic Mortality Models Using Data From England and Wales and the United States 2012Coherent Mortality Forecasting: The Product-Ratio Method With Functional Time Series Models 2010Evaluating the goodness of fit of stochastic mortality models 2010Backtesting Stochastic Mortality Models 2011Point and interval forecasts of mortality rates and life expectancy: A comparison of ten principal component methods

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2020Time series forecasting using singular spectrum analysis, fuzzy systems and neural networks

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