A Bayesian model for age at death with unequal adult mortality and cohort effects
Bibliographic Data
| ID | 24224861 |
|---|---|
| Authors | Matteo Dimai (0000-0003-1126-5234), Marek Brabec (0000-0001-6367-5791) |
| Year | 2026 |
| Volume | 82 |
| Issue | 1 |
| Publication date | 2026-06-17 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Genus (JOURNAL) |
| Journal identifiers | ISSN: 0016-6987 • E-ISSN: 2035-5556 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1186/s41118-026-00289-0 |
| OpenAlex | W7165000437 |
| Language | EN |
| References cited | 29 |
The conventional approach to modeling age at death through parametric models often employs a three-component mixture as a standard. However, recognizing the need to more accurately reflect the diverse trends in old age mortality, this study introduces a five-component Bayesian mortality model. This model is designed to address data exhibiting cohort effects and transitions in the old age mortality component, which moves from a skew-normal distribution to a mix of Gaussian and skew-normal distributions as the period progresses. The proposed model comprises a point probability for infant mortality, a uniform distribution for background mortality, a Gaussian distribution for premature mortality, and two components for old age mortality (Gaussian and skew-normal). Applied to data from 10 Italian regions spanning 1974–2022, including cohort effects for cohorts born between 1913 and 1947, the model demonstrates a stable interpretation of mortality components over time. In contrast to simpler models, it reveals a significant shift in old age mortality from a skew-normal to a combined Gaussian and skew-normal distribution around the millennium’s turn. This study not only sheds light on the evolution of old age mortality in Italy, highlighting a non-uniform shift and compression of mortality across the population, but also lays the groundwork for future forecasting models by maintaining a consistent parameter interpretation throughout the period.
age at death · Bayesian mixture models · cohort effects · Infant mortality · Italian regions · mortality forecasting · mortality modeling · old-age mortality · premature mortality · Skew normal distribution · Insurance, Mortality, Demography, Risk Management · Statistical Distribution Estimation and Applications · Statistical Methods in Epidemiology
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A Bayesian model for age at death with cohort effects
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| Highly cited | No |
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