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Smoothing and forecasting mortality rates

Department of Actuarial Mathematics and Statistics, Heriot-Watt University, Edinburgh, UK, i.d.currie{at}hw.ac.uk

Maria Durban

Departamento de Estadistica y Econometria, Universidad Carlos III de Madrid, Edificio Torres Quevedo, Leganes, Madrid, Spain

Paul HC Eilers

Department of Medical Statistics, Leiden University Medical Center, Leiden, The Netherlands

The prediction of future mortality rates is a problem of fundamental importance for the insurance and pensions industry. We show how the method of P-splines can be extended to the smoothing and forecasting of two-dimensional mortality tables. We use a penalized generalized linear model with Poisson errors and show how to construct regression and penalty matrices appropriate for two-dimensional modelling. An important feature of our method is that forecasting is a natural consequence of the smoothing process. We illustrate our methods with two data sets provided by the Continuous Mortality Investigation Bureau, a central body for the collection and processing of UK insurance and pensions data.

Key Words: forecasting • mortality • overdispersion • P-splines • two dimensions

Statistical Modelling, Vol. 4, No. 4, 279-298 (2004)
DOI: 10.1191/1471082X04st080oa


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