Models of mortality rates–analysing the residuals

O’hare, Colin; Li, Youwei

Abstract

The area of mortality modelling has received significant attention over the last 25 years owing to the need to quantify and forecast improving mortality rates. This need is driven primarily by the concern of governments, 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 article, we test several of the leading time series 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.

Citation

O’hare, C., & Li, Y. (2017). Models of mortality rates–analysing the residuals. Applied economics, 49(52), 5309-5323. https://doi.org/10.1080/00036846.2017.1305092

• Journal Article Type: Article
• Acceptance Date: Mar 23, 2017
• Online Publication Date: Mar 23, 2017
• Publication Date: Nov 8, 2017
• Deposit Date: Mar 19, 2019
• Publicly Available Date: Sep 8, 2020
• Journal: Applied Economics
• Print ISSN: 0003-6846
• Publisher: Routledge
• Peer Reviewed: Peer Reviewed
• Volume: 49
• Issue: 52
• Pages: 5309-5323
• DOI: https://doi.org/10.1080/00036846.2017.1305092
• Keywords: Mortality; Stochastic models; Residuals; Hurst exponents
• Public URL: https://hull-repository.worktribe.com/output/1113411
• Publisher URL: https://www.tandfonline.com/doi/full/10.1080/00036846.2017.1305092
• Additional Information: Peer Review Statement: The publishing and review policy for this title is described in its Aims & Scope.; Aim & Scope: http://www.tandfonline.com/action/journalInformation?show=aimsScope&journalCode=raec20