Evaluating extensions to coherent mortality forecasting models

Syazreen Shair, Sachi Purcal*, Nick Parr

*Corresponding author for this work

Research output: Contribution to journalArticle

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Abstract

Coherent models were developed recently to forecast the mortality of two or more sub-populations simultaneously and to ensure long-term non-divergent mortality forecasts of sub-populations. This paper evaluates the forecast accuracy of two recently-published coherent mortality models, the Poisson common factor and the product-ratio functional models. These models are compared to each other and the corresponding independent models, as well as the original Lee-Carter model. All models are applied to age-gender-specific mortality data for Australia and Malaysia and age-gender-ethnicity-specific data for Malaysia. The out-of-sample forecast error of log death rates, male-to-female death rate ratios and life expectancy at birth from each model are compared and examined across groups. The results show that, in terms of overall accuracy, the forecasts of both coherent models are consistently more accurate than those of the independent models for Australia and for Malaysia, but the relative performance differs by forecast horizon. Although the product-ratio functional model outperforms the Poisson common factor model for Australia, the Poisson common factor is more accurate for Malaysia. For the ethnic groups application, ethnic-coherence gives better results than gender-coherence. The results provide evidence that coherent models are preferable to independent models for forecasting sub-populations' mortality.

Original languageEnglish
Article number16
Pages (from-to)1-20
Number of pages20
JournalRisks
Volume5
Issue number1
DOIs
Publication statusPublished - Mar 2017

Bibliographical note

Copyright the Author(s) 2017. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

Keywords

  • coherent mortality forecasting models
  • Lee-Carter model
  • mortality forecasting accuracy
  • functional data model

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