Ensemble interval forecasts of mortality

In this paper, we investigate the use of ensemble interval forecasts in mortality modelling. The construction of ensemble interval forecasts involves combining the prediction intervals generated from different mortality models in order to improve the interval coverage. We consider a wide range of combination methods, including the simple and weighted averaging, median, mode, envelope, interior and exterior trimming, and probability averaging of endpoints and simple averaging of midpoints. For the mortality models, we adopt the Lee-Carter and Cairns-Blake-Dowd families of models, as well as autoregressive models. Using the mortality data of six populations, we find that the prediction intervals produced by the proposed ensemble approach generally outperform those generated individually from a single mortality model.

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Publication Details

Journal
Scandinavian Actuarial Journal
Published
2024-12-26
DOI
https://doi.org/10.1080/03461238.2024.2444565
Citations
1
Primary Topic
Insurance, Mortality, Demography, Risk Management
Type
article
Field-Weighted Citation Impact
1.71
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article

Ensemble interval forecasts of mortality

Jia Liu, Mingke Wang, Leonie Tickle, Jackie Li
1 citations
Scandinavian Actuarial Journal
Insurance, Mortality, Demography, Risk Management
1.71
article

Ensemble interval forecasts of mortality

Jia Liu, Mingke Wang, Leonie Tickle, Jackie Li
article en
1 citations

Abstract

In this paper, we investigate the use of ensemble interval forecasts in mortality modelling. The construction of ensemble interval forecasts involves combining the prediction intervals generated from different mortality models in order to improve the interval coverage. We consider a wide range of combination methods, including the simple and weighted averaging, median, mode, envelope, interior and exterior trimming, and probability averaging of endpoints and simple averaging of midpoints. For the mortality models, we adopt the Lee-Carter and Cairns-Blake-Dowd families of models, as well as autoregressive models. Using the mortality data of six populations, we find that the prediction intervals produced by the proposed ensemble approach generally outperform those generated individually from a single mortality model.

Scandinavian Actuarial JournalVol. 2025(6)
Australian National University (AU), Australian Regenerative Medicine Institute (AU), Monash University (AU), Macquarie University (AU)
Openalex Percentile: Top 11%
Insurance, Mortality, Demography, Risk Management
1.71
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Ensemble interval forecasts of mortality — Jia Liu, Mingke Wang, et al. · Scandinavian Actuarial Journal (2024) | TGRS Research Map | TGRS