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Uncertainty in Mortality Forecasting: An Extension to the Classical Lee-Carter Approach

Published online by Cambridge University Press:  09 August 2013

Johnny Siu-Hang Li ,
Mary R. Hardy  and
Ken Seng Tan
Johnny Siu-Hang Li
Affiliation:
Department of Statistics and Actuarial Science, University of Waterloo, Ontario, Canada, E-mail: shli@uwaterloo.ca
Mary R. Hardy
Affiliation:
Department of Statistics and Actuarial Science, University of Waterloo, Ontario, Canada, E-mail: mrhardy@uwaterloo.ca
Ken Seng Tan
Affiliation:
Department of Statistics and Actuarial Science, University of Waterloo, Ontario, Canada, E-mail: kstan@uwaterloo.ca
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Abstract

Traditionally, actuaries have modeled mortality improvement using deterministic reduction factors, with little consideration of the associated uncertainty. As mortality improvement has become an increasingly significant source of financial risk, it has become important to measure the uncertainty in the forecasts. Probabilistic confidence intervals provided by the widely accepted Lee-Carter model are known to be excessively narrow, due primarily to the rigid structure of the model. In this paper, we relax the model structure by considering individual differences (heterogeneity) in each age-period cell. The proposed extension not only provides a better goodness-of-fit based on standard model selection criteria, but also ensures more conservative interval forecasts of central death rates and hence can better reflect the uncertainty entailed. We illustrate the results using US and Canadian mortality data.

Keywords

Confidence intervalheterogeneityLee-Cartermaximum likelihood estimationparametric bootstrap

Information

Type
Research Article
Information
ASTIN Bulletin: The Journal of the IAA , Volume 39 , Issue 1 , May 2009 , pp. 137 - 164
Copyright
Copyright © International Actuarial Association 2009

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