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Wednesday 15th July, 11:00 - 12:30 Room: N-131

Determinants of subjective well-being or dimensions of quality of life?

Convenor Mr Francesco Sarracino (STATEC, Luxembourg )
Coordinator 1Ms Malgorzata Mikucka (Universite catholique de Louvain)

Session Details

The literature distinguishes mainly two approaches to measuring well-being. The first one is adopted by institutions and policy-oriented bodies that adopt multidimensional indexes of quality of life. Such indexes supplement the more commonly used income-based measures of well-being and allow a detailed description of living conditions and an assessment of societies’ progress in achieving citizens’ quality of life.

The second approach considers subjective well-being measured with a single variable, usually life satisfaction or happiness, and investigates its economic and non-economic determinants.

These two approaches treat differently the same set of variables. For example, income or health would be regarded as dimensions of quality of life in the first approach, but they would be seen as determinants of subjective well-being in the second approach.

This session invites analyses of advantages, disadvantages, and implications of the choice between the two approaches to measuring well-being. We invite papers addressing the following and related questions:
(1) Are there any ways to empirically assess the correctness of each of the two approaches? Can we test if a factor should be treated as an outcome (i.e. a dimension of quality of life) or rather as a determinant of subjective well-being?
(2) What is the relationship between the single measure of subjective well-being and the multiple dimensions of quality of life?
(3) Policy-oriented initiatives propose lists of dimensions of quality of life, but do we actually need multiple indicators? How to make sense of multidimensional indexes of well-being?
(4) Which lessons about well-being can we learn by using each of these approaches?

Paper Details

1. Mapping the Landscape: Patterns in Individual, Social and Societal Wellbeing in Europe since 2002
Dr Eric Harrison (City University London)

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?

2. Beyond GDP: Using equivalent incomes to measure well-being in Europe
Professor Koen Decancq (University of Antwerp)
Professor Erik Schokkaert (KULeuven)

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.

3. Is subjective well-being multidimensional?

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.

4. Is it sufficient to measure life satisfaction in order to measure quality of life?
Dr Kathrin Gärtner (Statistics Austria)
Dr Franz Eiffe (Statistics Austria)
Mr Matthias Till (Statistics Austria)

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.

5. Life Quality Measurement for the Assessment of Progress
Professor Paul Anand (The Open University)

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.