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The Measure of Population Aging in Different Welfare Regimes: A Bayesian Dynamic Modeling Approach

Author

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  • Roberta Paroli

    (Università Cattolica del Sacro Cuore)

  • Guido Consonni

    (Università Cattolica del Sacro Cuore)

  • Alessandro Rosina

    (Università Cattolica del Sacro Cuore)

Abstract

Given a population at a specific time point, it is often of interest to identify the entry age into typical stages of life, such as being young, becoming adult and elderly. These age cutoffs are important because they influence the public opinion and have an impact on policy decisions. An issue of great social relevance is defining the threshold beyond which a person becomes elderly. Fixed cutoffs are debatable because of their conventional nature which disregards issues such as changing life expectancy and the evolving structure of the age distribution. The above shortcomings can be overcome if age cutoffs are defined endogenously, i.e., relative to the whole age distribution of each country at a specific time point. We pursue this line of research by presenting an analysis whose main features are: (1) establishing a relationship between a country’s welfare regime and its age distribution and aging process, together with the identification of four clusters of countries corresponding to distinctive welfare models and (2) a Bayesian hierarchical dynamic model which accounts for the uncertainty in the time series of measurements of the endogenous cutoffs for the countries in the sample, as well as for their clustering structure. Our analysis leads to model-based estimates of country-specific endogenous age cutoffs and corresponding aging indicators. Additionally, we provide cluster-specific estimates, a novel contribution engendered by the use of hierarchical modeling, which widens the scope of our analysis beyond the countries which are present in the sample.

Suggested Citation

  • Roberta Paroli & Guido Consonni & Alessandro Rosina, 2020. "The Measure of Population Aging in Different Welfare Regimes: A Bayesian Dynamic Modeling Approach," European Journal of Population, Springer;European Association for Population Studies, vol. 36(2), pages 363-385, April.
  • Handle: RePEc:spr:eurpop:v:36:y:2020:i:2:d:10.1007_s10680-019-09531-2
    DOI: 10.1007/s10680-019-09531-2
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    References listed on IDEAS

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    1. Hippolyte d'Albis & Fabrice Collard, 2013. "Age groups and the measure of population aging," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 29(23), pages 617-640.
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