Modelling mortality: are we heading in the right direction?

Colin O'Hare, Youwei Li

Research output: Contribution to journalArticleResearchpeer-review

3 Citations (Scopus)

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 modelsusing 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.
Original languageEnglish
Pages (from-to)170-187
Number of pages18
JournalApplied Economics
Volume49
Issue number2
DOIs
Publication statusPublished - 8 Jan 2017

Keywords

  • mortality
  • stochastic models
  • structural breaks
  • forecasting

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