Modelling mortality: are we heading in the right direction?Colin O’hare and Youwei Li Applied Economics, 2017, vol. 49, issue 2, 170-187 Abstract: Predicting life expectancy has become of upmost importance in society. Pension providers, insurance companies, government bodies and individuals in the developed world have a vested interest in understanding how long people will live for. This desire to better understand life expectancy has resulted in an explosion of stochastic mortality models many of which identify linear trends in mortality rates by time. In making use of such models for forecasting purposes, we rely on the assumption that the direction of the linear trend (determined from the data used for fitting purposes) will not change in the future, recent literature has started to question this assumption. In this article, we carry out a comprehensive investigation of these types of models using male and female data from 30 countries and using the theory of structural breaks to identify changes in the extracted trends by time. We find that structural breaks are present in a substantial number of cases, that they are more prevalent in male data than in female data, that the introduction of additional period factors into the model reduces their presence, and that allowing for changes in the trend improves the fit and forecast substantially. Date: 2017 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:taf:applec:v:49:y:2017:i:2:p:170-187 Ordering information: This journal article can be ordered from DOI: 10.1080/00036846.2016.1192278 Access Statistics for this article Applied Economics is currently edited by Anita Phillips More articles in Applied Economics from Taylor & Francis Journals |
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