Determinants of subjective well-being or dimensions of quality of life?
|Convenor||Mr Francesco Sarracino (STATEC, Luxembourg )|
|Coordinator 1||Ms Malgorzata Mikucka (Universite catholique de Louvain)|
This paper discusses findings interim findings from a collaborative project funded through Phase 2 of the ESRC's Secondary Data Analysis Initiative. Key research questions are: How did levels of wellbeing vary across Europe, according to different measures, between 2002 and 2012? What are the drivers of well-being across Europe? Which countries have the largest well-being inequalities? What can we learn about the relationship between individual well-being and societal well-being, where the latter is defined in terms of citizens’ evaluations of their own societies?
It has become accepted that focusing exclusively on income growth may lead to a narrow-sighted measure of changes in well-being. Moreover, it remains blind to the distribution of income and well-being in the society. We propose a set of principles for a measure of well-being. We advocate the use of a measure based on equivalent incomes. We illustrate how this equivalent income approach can be implemented using ESS data for 2008 and 2010. We find that introducing inequality aversion and including other dimensions in the analysis leads to a different perspective on the growth of wellbeing.
The OECD guidelines for measuring Subjective Well-Being underlined the existence of 3 dimensions of this concept (cognitive, emotional and eudaimonics). EU-SILC implemented the recommendations in the 2013 data collection round. This paper questions if well-being is indeed multidimensional.The methods employed are factor analysis (assuming 3 dimensions) and multivariate regressions having as dependent variables the different well-being elements (to test if the set of determinants is the same or not for each of them). The dataset used is EU-SILC 2013 (cross-sectional). The findings have important measurement implications.
Our paper addresses the questions if variables like income, health and satisfaction with special life domains are mainly drivers of quality of life (measured through life satisfaction) or if they have to be considered as complements. In our analyses of Austrian and international data from EU-SILC (especially from the module 2013 on quality of life) we examine the impact of response styles and moods in measuring life satisfaction. Such impact would decrease its validity as single measure for quality of life.
The paper seeks to illustrate how quality of life can be measured using the capability approach. This approach developed first by Nobel economist Amartya Sen proposes that people value acts and states, experiences and opportunities. In this paper we develop data on 1000 adults in each of the USA, UK and Italy with the aid of a market research company YOUGOV to illustrate how the approach can be operationalised. Our main results include inter alia dominance tests, life satisfaction equations which include capabilities as dependent variables and conclude that multiple indicators and experience should all be included.