Modelling Mortality with Common Stochastic Long-Run Trends
Details
Serval ID
serval:BIB_E1620DE65208
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Modelling Mortality with Common Stochastic Long-Run Trends
Journal
The Geneva Papers on Risk and Insurance - Issues and Practice
Working group(s)
Arnold (-Gaille) S.
ISSN
1018-5895
Publication state
Published
Issued date
10/2011
Peer-reviewed
Oui
Volume
36
Number
4
Pages
595-621
Language
english
Abstract
Modelling mortality and longevity risk is critical to assessing risk for insurers issuing longevity risk products. It has challenged practitioners and academics alike because of first the existence of common stochastic trends and second the unpredictability of an eventual mortality improvement in some age groups. When considering cause-of-death mortality rates, both aforementioned trends are additionally affected by the cause of death. Longevity trends are usually forecasted using a Lee-Carter model with a single stochastic time series for period improvements, or using an age-based parametric model with univariate time series for the parameters. We assess a multivariate time series model for the parameters of the Heligman-Pollard function, through Vector Error Correction Models which include the common stochastic long-run trends. The model is applied to circulatory disease deaths in U.S. over a 50-year period and is shown to be an improvement over both the Lee-Carter model and the stochastic parameter ARIMA Heligman-Pollard model.
Keywords
mortality trends, Heligman-Pollard model, Lee-Carter model, VECM, causes of death, mortality forecasts
Web of science
Open Access
Yes
Create date
15/09/2011 16:47
Last modification date
20/08/2019 17:05