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Identifiability in age/period/cohort mortality models

Published online by Cambridge University Press:  04 June 2020

Andrew Hunt Open the ORCID record for Andrew Hunt [Opens in a new window]  and
David Blake Open the ORCID record for David Blake [Opens in a new window]
Andrew Hunt*
Affiliation:
Cass Business School, City University London, London, UK
David Blake
Affiliation:
Pensions Institute, Cass Business School, City University London, London, UK
*
* Corresponding author. E-mail: andrew.hunt.1@cass.city.ac.uk
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Abstract

The addition of a set of cohort parameters to a mortality model can generate complex identifiability issues due to the collinearity between the dimensions of age, period and cohort. These issues can lead to robustness problems and difficulties making projections of future mortality rates. Since many modern mortality models incorporate cohort parameters, we believe that a comprehensive analysis of the identifiability issues in age/period/cohort mortality models is needed. In this paper, we discuss the origin of identifiability issues in general models before applying these insights to simple but commonly used mortality models. We then discuss how to project mortality models so that our forecasts of the future are independent of any arbitrary choices we make when fitting a model to data in order to identify the historical parameters.

Keywords

Mortality modellingAge/period/cohort modelsIdentification issuesProjectionC15C51C53
Type
Paper
Information
Annals of Actuarial Science , Volume 14 , Issue 2 , September 2020 , pp. 500 - 536
Copyright
© Institute and Faculty of Actuaries 2020

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