TY - JOUR
T1 - The Measure of Population Aging in Different Welfare Regimes: A Bayesian Dynamic Modeling Approach
AU - Paroli, Roberta
AU - Consonni, Guido
AU - Rosina, Alessandro
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
KW - Age cutoff
KW - Aging indicator
KW - Bayesian hierarchical dynamic model
KW - Kullback–Leibler divergence
KW - Longevity
KW - Welfare regime
KW - Age cutoff
KW - Aging indicator
KW - Bayesian hierarchical dynamic model
KW - Kullback–Leibler divergence
KW - Longevity
KW - Welfare regime
UR - http://hdl.handle.net/10807/143423
UR - http://www.wkap.nl/journalhome.htm/0168-6577
U2 - 10.1007/s10680-019-09531-2
DO - 10.1007/s10680-019-09531-2
M3 - Article
SN - 0168-6577
SP - 363
EP - 385
JO - European Journal of Population
JF - European Journal of Population
ER -