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

Roberta Paroli¹, Guido Consonni¹, Alessandro Rosina¹

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

European Journal of Population = Revue Europeenne De Demographie

|April 8, 2020

Summary

This study introduces endogenous age cutoffs, determined by a country's age distribution, to better define aging stages. This approach offers a dynamic alternative to fixed thresholds, improving policy relevance and understanding of population aging.

Keywords:

Age cutoff Aging indicator Bayesian hierarchical dynamic model Kullback–Leibler divergence Longevity Welfare regime

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Area of Science:

Demography
Gerontology
Sociology

Background:

Defining age thresholds for life stages (e.g., elderly) is crucial for policy and public opinion.
Fixed age cutoffs are conventional and fail to account for evolving life expectancy and age structures.
Endogenous age cutoffs, relative to a population's age distribution, offer a more adaptable and relevant approach.

Purpose of the Study:

To establish a relationship between welfare regimes and age distribution/aging processes.
To identify country clusters based on distinct welfare models and aging patterns.
To develop a Bayesian hierarchical dynamic model for estimating endogenous age cutoffs.

Main Methods:

Analysis of country welfare regimes and their correlation with age distribution characteristics.
Identification of country clusters representing distinct welfare and aging models.
Application of a Bayesian hierarchical dynamic model to estimate time-varying, country-specific endogenous age cutoffs.

Main Results:

Identified four distinct clusters of countries based on welfare regimes and aging patterns.
Provided model-based, country-specific estimates of endogenous age cutoffs.
Generated novel cluster-specific estimates, enhancing the generalizability of findings.

Conclusions:

Endogenous age cutoffs provide a more accurate and dynamic measure of aging stages compared to fixed thresholds.
Welfare regimes are significantly associated with national age distributions and aging processes.
The developed Bayesian model effectively estimates endogenous age cutoffs and their variations across countries and clusters.