An age–period–cohort model in a Dirichlet framework: A coherent causes of death estimation

Though pivotal in longevity studies, multi-outcome modelling is largely neglected in the associated statistical literature. Here, we focus on the case of compositional data, especially relevant in longevity analysis, where overall mortality can be described as the composition of several causes of death. We propose an age–period–cohort model within the Dirichlet framework with a specific interest in its use for modelling longevity with multiple causes of death. We introduce a flexible approach to incorporating the Dirichlet distribution into the age–period–cohort framework. Then, using US cause-specific mortality data, we provide a comprehensive discussion and comparison of alternative modelling approaches.

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Publication Details

Journal
Insurance Mathematics and Economics
Published
2025-11-24
DOI
https://doi.org/10.1016/j.insmatheco.2025.103194
Citations
1
Primary Topic
Insurance, Mortality, Demography, Risk Management
Type
article
Field-Weighted Citation Impact
5.59
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article

An age–period–cohort model in a Dirichlet framework: A coherent causes of death estimation

Andrea Nigri, Rebecca Graziani
1 citations
Insurance Mathematics and Economics
Insurance, Mortality, Demography, Risk Management
5.59
article

An age–period–cohort model in a Dirichlet framework: A coherent causes of death estimation

Andrea Nigri, Rebecca Graziani
article en
1 citations

Abstract

Though pivotal in longevity studies, multi-outcome modelling is largely neglected in the associated statistical literature. Here, we focus on the case of compositional data, especially relevant in longevity analysis, where overall mortality can be described as the composition of several causes of death. We propose an age–period–cohort model within the Dirichlet framework with a specific interest in its use for modelling longevity with multiple causes of death. We introduce a flexible approach to incorporating the Dirichlet distribution into the age–period–cohort framework. Then, using US cause-specific mortality data, we provide a comprehensive discussion and comparison of alternative modelling approaches.

Insurance Mathematics and EconomicsVol. 126
University of Foggia (IT), Bocconi University (IT)
Openalex Percentile: Top 4%
Insurance, Mortality, Demography, Risk Management
5.59
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