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Bayesian Modeling of Mortality in Italian Regions: A Three-Component Approach Incorporating Cohort Effects

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F24%3A00588342" target="_blank" >RIV/67985807:_____/24:00588342 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.1007/978-3-031-64273-9_25" target="_blank" >https://doi.org/10.1007/978-3-031-64273-9_25</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-031-64273-9_25" target="_blank" >10.1007/978-3-031-64273-9_25</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Bayesian Modeling of Mortality in Italian Regions: A Three-Component Approach Incorporating Cohort Effects

  • Original language description

    The increases in life expectancy over the last decades have strongly impacted the distribution of ages at death. Its parametric estimation can be complicated by cohort effects. Our addresses the issue by extending a recent three-component parametric model to include cohort effects in a Bayesian framework. The model is fit to male mortality data from five diverse Italian regions between 1974 and 2022. Our results demonstrate significant regional variations in mortality, influenced by cohort effects, particularly among cohorts born around World War I. The model effectively captures the evolution of mortality components, with cohort effects markedly improving fit of complex, even multi-modal curves.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10103 - Statistics and probability

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2024

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Mathematical and Statistical Methods for Actuarial Sciences and Finance. MAF2024 Conference Proceedings

  • ISBN

    978-3-031-64272-2

  • ISSN

  • e-ISSN

  • Number of pages

    5

  • Pages from-to

    149-153

  • Publisher name

    Springer

  • Place of publication

    Cham

  • Event location

    Le Havre

  • Event date

    Apr 4, 2024

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    001299654100025