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The double-gap life expectancy forecasting model

Pascariu, Marius D.; Canudas Romo, Vladimir; Vaupel, James W.

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Life expectancy is highly correlated over time among countries and between males and females. These associations can be used to improve forecasts. Here we propose a method for forecasting female life expectancy based on analysis of the gap between female life expectancy in a country compared with the record level of female life expectancy in the world. Second, to forecast male life expectancy, the gap between male life expectancy and female life expectancy in a country is analysed. We present...[Show more]

dc.contributor.authorPascariu, Marius D.
dc.contributor.authorCanudas Romo, Vladimir
dc.contributor.authorVaupel, James W.
dc.date.accessioned2018-01-12T00:23:21Z
dc.identifier.issn0167-6687
dc.identifier.urihttp://hdl.handle.net/1885/139181
dc.description.abstractLife expectancy is highly correlated over time among countries and between males and females. These associations can be used to improve forecasts. Here we propose a method for forecasting female life expectancy based on analysis of the gap between female life expectancy in a country compared with the record level of female life expectancy in the world. Second, to forecast male life expectancy, the gap between male life expectancy and female life expectancy in a country is analysed. We present these results for various developed countries. We compare our results with forecasts based on the Lee–Carter approach and the Cairns–Blake–Dowd strategy. We focus on forecasting life expectancy at age 0 and remaining life expectancy at age 65.
dc.format.mimetypeapplication/pdf
dc.publisherElsevier
dc.rights© 2017 The Authors.
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourceInsurance: Mathematics and Economics
dc.subjectLife expectancy forecasting
dc.subjectMortality modelling
dc.subjectBest-practice trends
dc.subjectSex-gap
dc.subjectTime series models
dc.titleThe double-gap life expectancy forecasting model
dc.typeJournal article
dc.date.issued2017
local.publisher.urlhttps://www.elsevier.com/
local.type.statusPublished Version
local.contributor.affiliationCanudas-Romo, V., School of Demography, The Australia National University
local.identifier.doi10.1016/j.insmatheco.2017.09.011
dcterms.accessRightsOpen Access
dc.provenanceThis is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
dc.rights.licenseCC BY license
CollectionsANU Research Publications

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