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

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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.

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Acknowledgements

We thank Giovanni Petris for very useful suggestions concerning the implementation of the software dlm. We are indebted to two anonymous reviewers for helpful comments that led to improvements in both the content and the presentation of the article. We acknowledge the support of Università Cattolica del Sacro Cuore, Milan, Italy, through the research grant “I Don’t Want to Be Inactive—A Longer Life: a Generational Challenge and an Opportunity for Society” (D3.2-2014).

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  1. Department of Statistical Science, Università Cattolica del Sacro Cuore, Milan, Italy

    Roberta Paroli, Guido Consonni & Alessandro Rosina

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  1. Roberta Paroli
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  2. Guido Consonni
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  3. Alessandro Rosina
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Correspondence to Roberta Paroli.

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Paroli, R., Consonni, G. & Rosina, A. The Measure of Population Aging in Different Welfare Regimes: A Bayesian Dynamic Modeling Approach. Eur J Population 36, 363–385 (2020). https://doi.org/10.1007/s10680-019-09531-2

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  • DOI: https://doi.org/10.1007/s10680-019-09531-2

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