Mortality Density Forecasts: An Analysis of Six Stochastic Mortality Models

Pensions Institute Discussion Paper No. PI-0801

70 Pages Posted: 10 Feb 2009 Last revised: 10 Jul 2009

See all articles by Andrew J. G. Cairns

Andrew J. G. Cairns

Heriot-Watt University - Department of Actuarial Science & Statistics

David P. Blake

City, University of London

Kevin Dowd

Nottingham University Business School (NUBS)

Guy Coughlan

Pacific Global Advisors

David Epstein

J.P. Morgan Chase & Co.

Marwa Khalaf-Allah

J.P. Morgan

Date Written: April 1, 2008

Abstract

We investigate the uncertainty of forecasts of future mortality generated by a number of previously proposed stochastic mortality models. We specify fully the stochastic structure of the models to enable them to generate forecasts. Mortality fan charts are then used to compare and contrast the models, with the conclusion that model risk can be significant.

The models are also assessed individually with reference to three criteria that focus on the plausibility of their forecasts: biological reasonableness of forecast mortality term structures; biological reasonableness of individual stochastic components of the forecasting model (for example, the cohort erect); and reasonableness of forecast levels of uncertainty relative to historical levels of uncertainty. In addition, we consider a fourth assessment criterion dealing with the robustness of forecasts relative to the sample period used to fit the model.

To illustrate the assessment methodology, we analyse a data set consisting of national population data for England & Wales, for Males aged between 60 and 90 years old. We note that this particular data set may favour those models designed for application to older ages, such as variants of Cairns-Blake-Dowd, and emphasise that a similar analysis should be conducted for the specific data set of interest to the reader. We draw some conclusions based on the analysis and compare to the application of the models for the same age group and gender for the United States population. Finally, we note the broader application of the approach to model selection for alternate data sets and populations

Keywords: Stochastic mortality model, cohort erect, fan charts, model risk, fore-casting, model selection criteria

Suggested Citation

Cairns, Andrew J. G. and Blake, David P. and Dowd, Kevin and Coughlan, Guy and Epstein, David and Khalaf-Allah, Marwa, Mortality Density Forecasts: An Analysis of Six Stochastic Mortality Models (April 1, 2008). Pensions Institute Discussion Paper No. PI-0801, Available at SSRN: https://ssrn.com/abstract=1340353 or http://dx.doi.org/10.2139/ssrn.1340353

Andrew J. G. Cairns (Contact Author)

Heriot-Watt University - Department of Actuarial Science & Statistics ( email )

Edinburgh, Scotland EH14 4AS
United Kingdom

David P. Blake

City, University of London ( email )

106 Bunhill Row
London, EC1Y 8TZX
Great Britain
+44 (0) 20-7040-8600 (Phone)
+44 (0) 20-7040-8881 (Fax)

HOME PAGE: http://www.pensions-institute.org/

Kevin Dowd

Nottingham University Business School (NUBS) ( email )

Jubilee Campus
Wollaton Road
Nottingham, NG8 1BB
United Kingdom

Guy Coughlan

Pacific Global Advisors ( email )

535 Madison Avenue
Floor 14
New York, NY 10022
United States
+1-212-405-6340 (Phone)

HOME PAGE: http://www.PacificGlobalAdvisors.com

David Epstein

J.P. Morgan Chase & Co. ( email )

60 Wall St.
New York, NY 10260
United States

Marwa Khalaf-Allah

J.P. Morgan ( email )

25 Bank Street
London, E14 5JP
United Kingdom