A Global Indicator to Track Well-Being in the Silver and Golden Age

Abstract

In this work, we design a protocol to obtain global indicators of health and well-being from weighted and longitudinal heterogeneous multivariate data. First, we consider a set of thematic sub-indicators of interest observed in several periods. Next, we combine them using the Common Principal Component (CPC) model. For this purpose, we put a new straightforward CPC model to cope with weighted and longitudinal data and develop a new statistic to test the validity of the CPC-longitudinal model, whose distribution is obtained by stratified bootstrap. To illustrate this methodology, we use data from the last three waves of the Survey of Health, Ageing and Retirement in Europe (SHARE), which is the largest cross-European social science panel study data set covering insights into the public health and socio-economic living conditions of European individuals. In particular, we first design four thematic indicators that focus on general health status, dependency situation, self-perceived health, and socio-economic status. We then apply the CPC-longitudinal model to obtain a global indicator to track the well-being in the silver and golden age in the 18 participating European countries from 2015 to 2020. We found that the latest survey wave 8 captures the early reactions of respondents successfully. The pandemic significantly worsens people’s physical health conditions; however, the analysis of their self-perceived health presents a delay. Tracking the performances of our global indicator, we also found that people living in Northern Europe mainly have better health and well-being status than in other participating countries.