Models of mortality rates–analysing the residuals

O’hare, C; Li, Y

Models of mortality rates–analysing the residuals

O’hare, C Li, Y

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Publication Type:: Journal Article
Citation:: Applied Economics, 2017, 49 (52), pp. 5309 - 5323
Issue Date:: 2017-11-08

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Field	Value	Language
dc.contributor.author	O’hare, C	en_US
dc.contributor.author	Li, Y https://orcid.org/0000-0002-2142-7607	en_US
dc.date.issued	2017-11-08	en_US
dc.identifier.citation	Applied Economics, 2017, 49 (52), pp. 5309 - 5323	en_US
dc.identifier.issn	0003-6846	en_US
dc.identifier.uri	http://hdl.handle.net/10453/124422
dc.description.abstract	© 2017 Informa UK Limited, trading as Taylor & Francis Group. 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.	en_US
dc.relation.ispartof	Applied Economics	en_US
dc.relation.isbasedon	10.1080/00036846.2017.1305092	en_US
dc.subject.classification	Economics	en_US
dc.title	Models of mortality rates–analysing the residuals	en_US
dc.type	Journal Article
utslib.citation.volume	52	en_US
utslib.citation.volume	49	en_US
utslib.for	1402 Applied Economics	en_US
utslib.for	1502 Banking, Finance and Investment	en_US
utslib.for	1403 Econometrics	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Business
utslib.copyright.status	closed_access
pubs.issue	52	en_US
pubs.publication-status	Published	en_US
pubs.volume	49	en_US

Abstract:

© 2017 Informa UK Limited, trading as Taylor & Francis Group. 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.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/124422