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.

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Fig. 1

Source: OECD (2011), How’s Life? Measuring well-being. OECD Publishing, Paris

Fig. 2
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Fig. 4


  1. 1.

    In the 1970 s the definition of the OECD-UN guidelines on social indicators was a critical step to the development of internationally harmonised social statistics.

  2. 2.

    More details on the framework and its indicators can be found in OECD (2011, 2013, 2015).

  3. 3.

    The dashboard is published in the biennial report “How’s Life? Measuring Well-Being”.

  4. 4.

    Please, refer to Annex 1 for more details.

  5. 5.

    See for instance the consultation process (http://www.strategie.gouv.fr/publications/synthese-consultations-dela-pib-un-tableau-de-bord-france) put in place in the context of the French Initiative “The New Indicators of Wealth” that led to the definition of a dashboard of 10 indicators on which the Government has to report each year (http://www.strategie.gouv.fr/publications/indicateurs-de-richesse-rapport-gouvernement).

  6. 6.

    See for instance the Green Book developed in the United Kingdom (UK) to perform these techniques: https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/209107/greenbook_valuationtechniques.pdf and some of their applications in the evaluation of UK policy programmes: https://coanalysis.blog.gov.uk/wp-content/uploads/sites/115/2016/01/Policy-Development-for-Well-being.pdf.

  7. 7.

    Notice that in “income” scenarios it understates the weight of income in hypothetical choices.

  8. 8.

    Information on educational level is available only for those users who decide to complete and submit the extended survey.

  9. 9.

    For example in Iceland there is no girl aged 0–24 years in the sample.

  10. 10.

    Asia-Pacific includes: Australia, Japan, Korea and New Zealand; Europe includes: Austria, Belgium, the Czech Republic, Denmark, Germany, Estonia, Finland, France, Greece, Hungary, Iceland, Ireland, Israel, Italy, Luxemburg, the Netherlands, Norway, Poland, Portugal, the Slovak Republic, Slovenia, Spain, Sweden, Switzerland, the United Kingdom and Turkey; North America includes: Canada and the United States; and South America includes: Chile and Mexico.

  11. 11.

    As previously mentioned, the countries included in the analysis are the OECD member countries as of March 2016 (34 countries).

  12. 12.

    The BLI_XX coefficients capture the effect of living in a country with average level of well-being outcomes proxied by the different BLI dimensions on BLI weights. To give an example, the BLIDimension corresponding to the well-being dimension “Health” is BLI_HS = BLI dimension “Health”. BLI_HS is the country’s performance in the “Health” dimension of the BLI, which is the simple average of the country’s score in life expectancy at birth and self-reported health, the two indicators which compose the BLI dimension “Health”. For the list of the indicators included in each dimension, please refer to the website: http://www.oecdbetterlifeindex.org/.

  13. 13.

    The analysis is conducted using the package STATA 14.

  14. 14.

    For the sake of brevity Tables 3 and 4 present only the results for the dimensions in which FMM performs better than OLS. The results for the remaining dimensions are however available from the authors upon request.

  15. 15.

    Results from the post-estimation tests are available from the authors upon request.

  16. 16.

    By clicking on the “Gender differences” button underneath the mixer tool of the weights.

  17. 17.

    By clicking on the “Compare with others” button underneath the mixer tool of the weights.

  18. 18.

    By clicking on the “Share your index” button underneath the mixer tool of the weights, the user has the possibility to share it via Facebook, Twitter, e-mail or to embed it somewhere.


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The views expressed in this article are those of the authors and do not represent the official views of the OECD or of its member countries. The authors thank the two anonymous reviewers for their thoughtful comments and suggestions.

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Corresponding author

Correspondence to Elena Tosetto.


Annex 1

How the BLI works

In the BLI users assign a weight ranging from 0 to 5 to each well-being dimension through the interface of the web tool (Fig. 5). The user can see how countries’ average achievements compare based on her own personal priorities in life: the weights assigned, which are recalculated to sum to 100. Users can also explore gender differences,Footnote 16 compare their choices with peersFootnote 17 and share their index with other people in their network and with the OECD.Footnote 18 When a user decides to compare her BLI, a small section asking the country of origin, the sex and the age group appears. Once the user has filled this in, she can click on “submit your index” and she will be able to compare her results with people from the same country, same sex and belonging to the same age group. The same section appears when she decides to share her BLI, if she did not already go through it in the “compare” step. When the user submits her index, the application stores anonymously her selection. The user has also the possibility to participate to an extended survey, where she is asked about her level of education, occupation, the family structure (married/being together, single, with children), how she heard about the BLI and her satisfaction with her life as a whole and with the 11 well-being dimensions.

Fig. 5

The OECD Better Life Index web application

Annex 2

The Better Life Index Extended Survey

This section lists the questions (and possible replies) that are included in the Better Life Index extended survey:

  • Level of education: Primary/Secondary/University/college

  • Occupation: Employee/Unpaid worker/Professional/Self-employed/Retired/Senior executive/Academic/Student/Unemployed

  • Family structure: Married or Living together/Single

  • With children: (option to be ticked or not)

  • How did you hear about the Better Life Index: Friends/Media/Work/Other

How is Your Life?

In this section all answers are on a 0–10 scale with 0 = not satisfied at all and 10 = most satisfied

Thinking about your own life and personal circumstances, how satisfied are you with your life as a whole?

How satisfied are you with…

  • your income and standard of living?

  • your housing?

  • your job?

  • your health?

  • your education and skills?

  • your work- life balance?

  • your community and support network?

  • your civic engagement opportunities?

  • the quality of your environment?

  • your level of personal safety?

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Balestra, C., Boarini, R. & Tosetto, E. What Matters Most to People? Evidence from the OECD Better Life Index Users’ Responses. Soc Indic Res 136, 907–930 (2018). https://doi.org/10.1007/s11205-016-1538-4

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  • Better life index
  • Composite index
  • OECD
  • Users
  • Preferences
  • Well-being