Models of Mortality - Analysing the Residuals

34 Pages Posted: 28 Oct 2014

See all articles by Colin O'Hare

Colin O'Hare

Monash University - Department of Econometrics & Business Statistics

Youwei Li

Hull University Business School

Date Written: October 28, 2014

Abstract

The area of mortality modelling has received significant attention over the last 20 years owing to the need to quantify and forecast improving mortality rates. This need is driven primarily by the concern of governments, professionals, insurance and actuarial professionals and individuals to be able to fund their old age. In particular, to quantify the costs of increasing longevity we need suitable model of mortality rates that capture the dynamics of the data and forecast them with sufficient accuracy to make them useful. In this paper we test several of those models by considering the fitting quality and in particular, testing the residuals of those models for normality properties. In a wide ranging study considering 30 countries we find that almost exclusively the residuals do not demonstrate normality. Further, in hurst tests of the residuals we find evidence that structure remains that is not captured by the models.

Keywords: Mortality, stochastic models, forecasting, structural breaks. hurst exponents

JEL Classification: C51, C52, C53, G22, G23, J11

Suggested Citation

O'Hare, Colin and Li, Youwei, Models of Mortality - Analysing the Residuals (October 28, 2014). Available at SSRN: https://ssrn.com/abstract=2512573 or http://dx.doi.org/10.2139/ssrn.2512573

Colin O'Hare (Contact Author)

Monash University - Department of Econometrics & Business Statistics ( email )

Wellington Road
Clayton, Victoria 3168
Australia

Youwei Li

Hull University Business School ( email )

University of Hull
Hull, HU6 7RX
United Kingdom

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