Modeling Mortality with a Bayesian Vector Autoregression

39 Pages Posted: 8 Mar 2011 Last revised: 12 Apr 2011

See all articles by Michael Sherris

Michael Sherris

University of New South Wales - ARC Centre of Excellence in Population Ageing Research and School of Risk and Actuarial Studies; UNSW Australia Business School

Carolyn Njenga

University of New South Wales (UNSW) - School of Actuarial Studies

Date Written: March 3, 2011

Abstract

Mortality risk models have been developed to capture trends and common factors driving mortality improvement. Multiple factor models take many forms and are often developed and fitted to older ages. In order to capture trends from young ages it is necessary to take into account the richer age structure of mortality improvement from young ages to middle and then into older ages. The Heligman and Pollard (1980) model is a parametric model which captures the main features of period mortality tables and has parameters that are interpreted according to age range and effect on rates. Although time series techniques have been applied to model parameters in various parametric mortality models, there has been limited analysis of parameter risk using Bayesian techniques. This paper uses a Bayesian Vector Autoregressive (BVAR) model for the parameters of the Heligman-Pollard model and fits the model to Australian data. As VARmodels allow for dependence between the parameters of the Heligman-Pollard model they are flexible and better reflect trends in the data, giving better forecasts of the parameters. Forecasts can readily incorporate parameter uncertainty using the models. Bayesian Vector Autoregressive (BVAR) models are shown to significantly improve the forecast accuracy of VAR models for mortality rates based on Australian data. The Bayesian model allows for parameter uncertainty, shown to be a significant component of total risk.

Keywords: mortality, parameter risk, vector auto-regression, Bayesian, Heligman-Pollard model

JEL Classification: J11, C11, G22

Suggested Citation

Sherris, Michael and Njenga, Carolyn Ndigwako, Modeling Mortality with a Bayesian Vector Autoregression (March 3, 2011). UNSW Australian School of Business Research Paper No. 2011ACTL04. Available at SSRN: https://ssrn.com/abstract=1776532 or http://dx.doi.org/10.2139/ssrn.1776532

Michael Sherris (Contact Author)

University of New South Wales - ARC Centre of Excellence in Population Ageing Research and School of Risk and Actuarial Studies ( email )

UNSW Business School
Risk and Actuarial Studies
Sydney, NSW 2052
Australia
+61 2 9385 2333 (Phone)
+61 2 9385 1883 (Fax)

HOME PAGE: http://www.asb.unsw.edu.au/schools/Pages/MichaelSherris.aspx

UNSW Australia Business School ( email )

Sydney, NSW 2052
Australia

Carolyn Ndigwako Njenga

University of New South Wales (UNSW) - School of Actuarial Studies ( email )

Sydney, NSW 2052
Australia

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