What Matters Most to People? Evidence from the OECD Better Life Index Users’ Responses

The OECD Better Life Index is an interactive composite index that aggregates a country’s well-being outcomes through the weights defined by online users. This paper analyses these weights by analysing the responses given by close to 88,000 users since 2011 to date. The contribution of this paper is threefold. First, it investigates the factors shaping users’ preferences over a set of 11 well-being dimensions, while most of the previous empirical works in the area have focused on factors affecting support for a specific well-being domain (e.g. redistribution, environmental concerns) at a time. Second, it provides insights into users’ preferences for a large group of countries, which differ in terms of culture and living conditions. Third, a finite mixture model (FMM) approach is used to test for heterogeneity in the effect of satisfaction levels on the weight attached to a given BLI dimension across sub-population groups. Various empirical models are used to identify responses’ patterns and see whether they can be accounted for respondents’ characteristics and their perceived level of well-being. The paper finds that health, education and life satisfaction are the aspects that matter the most in OECD countries. Descriptive statistics show that men assign more importance to material conditions than women; while women in general value quality of life more than men. Environment, housing, civic engagement, safety and health become more important with age, while life satisfaction, education, work-life balance, jobs and income are particularly important for those younger than 35. There are also regional patterns in users’ findings, for instance civic engagement is particularly important in South America, while safety and work-life balance matter tremendously in Asia-Pacific. Furthermore, an additional analysis carried out on a subset of observations finds that for several well-being dimensions (i.e. jobs, housing, community, health, education, civic engagement, safety, life satisfaction and work-life balance) there is a positive and linear relationship between individual preferences and self-reported satisfaction in those dimensions. Finally, the check for heterogeneity in the relationship of satisfaction to preferences in well-being dimensions, via an FMM analysis, reveals that, in the case of income and education, two classes of individuals with distinct effects of satisfaction levels on preferences are identified.