Category: Learn

Five ways to well-being

In 2008, nef was commissioned by the UK Government’s Foresight Project on Mental Capital and Well-being to review the inter-disciplinary work of over 400 scientists from across the world. The aim was to identify a set of evidence-based actions to improve well-being, which individuals would be encouraged to build into their daily lives.

As an illustration of how government action can be explicitly directed towards improving well-being, the following pages briefly set out the five evidence-based ways to well-being and the sorts of policy interventions which could help to enable them.

Relationship to the policy process

There are good reasons to think that well-being should be treated as both an end of policy, as well as a means of achieving other policy goals. While the elements of well-being are clearly desirable outcomes in themselves, and arguably the ultimate goals of human endeavour, there is also evidence that targeting specific aspects of positive well-being (e.g., autonomy, emotional well-being) might be an effective way to drive desirable behaviour changes. For instance, a sense of individual autonomy – broadly, the extent to which people feel able to make their own decisions – seems likely to enhance outcomes in a range of areas of traditional policy focus, such as people’s interactions with the education system.

Due to its ‘means and ends’ character, it is possible to identify a number of different uses for regular measures of population well-being. They would enable national governments to:

Look back

  • To assess change over time
  • To review and evaluate policy decisions
  • To draw comparisons (e.g. internationally)
  • To assess differences between subgroups of the national population

Look forward

  • To identify areas of need or opportunity
  • To evaluate the potential impacts of policy proposals
  • To shape policy formulation (e.g. content and delivery)
  • To inform the targeting of new policy (e.g. by population subgroup)

The policy cycle

The diagram above, taken from our report, shows the ways in which National Accounts of Well-being could be used to achieve this range of goals at different stages of the policy-making process. While the process is deliberately described in generic terms that can apply to policy-making across developed nations, a number of clearly defined roles for the use of well-being indicators emerge at particular points of the process, from defining policy aims and identifying need, developing and shaping policy proposals, implementing and delivering particular policy interventions, to evaluating the impact of policy actions.

The broader context

Despite the wealth of information within the results of our national accounting indicators, they do not constitute the full picture of national progress. Two other crucial aspects that governments should equally measure to ensure that they are doing the best for their citizens are:

  • The external conditions of people’s lives – both indicators monitoring material conditions of individuals’ lives, such as the income-based indicators on which top-line societal measurement has been traditionally focused, as well as factors such as employment status and physical health; and also measures of factors which exist across society such as freedom and government accountability.
  • The ecological sustainability of society’s resource use – the degree to which the Earth’s finite resources continue to be available to enable people’s welfare in the future is a crucial issue for governments. Enjoying good experiences today at the cost of substantial pain tomorrow cannot be said to be a mechanism for producing true overall well-being: measures of the ecological sustainability of a society are therefore crucial.

The Canadian statistician Robert Prescott-Allen has specifically addressed the issue of how national indicator sets should best be designed to include measures of subjective well-being alongside measures of welfare from other spheres. The diagram below, taken from the National Accounts of Well-being report, shows an adapted version of one possible structure for national well-being indicators which he has devised. Core measures of human well-being, such as the national well-being accounts presented in this report, are surrounded by measures at society level, such as the economy and governance system through which human well-being is enabled. This human layer of activity exerts pressure on the overall eco-system well-being which is described via measures such as resource use and biodiversity.

This type of multilayered structure of national indicators provides an explicit mechanism for exploring the links between how lives are subjectively experienced and:

  • the societal systems within which those lives are embedded
  • the ecological system on which the lives ultimately depend.

nef’s Happy Planet Index is an example of an indicator which takes these different aspects and summarises them into an easily communicable indicator of the ecological efficiency with which nations deliver human well-being. However a multilayered national accounting structure of the kind we are proposing would allow the relationships between these elements to be unpacked, so that we better understand how actions within one sphere impact on the others.

Further developing the framework

Our working model highlights a number of questions about how National Accounts of Well-being should best be composed, structured and measured. We hope that this will generate a new wave of research to produce a robust and well-validated framework that governments will be able to use to reliably measure population well-being. Issues for further exploration include:

  • Refining the components of well-being included in the framework. The components in our National Accounts of Well-being framework were designed based on considerations of the best current theory about the elements that constitute human well-being together with the possibilities offered by the data available in the European Social Survey. New attempts to construct similar frameworks might consider including additional components or grouping up measures in different ways to form new components.
  • Improving survey measures. The well-being module of the European Social Survey on which our working model for National Accounts of Well-being is based was designed by a cross-national group of well-being experts. But there are likely to be a number of possible improvements to the measures that were used, including: changes to question wording to improve clarity, comprehensibility and cross-country comparability, developing additional measures so that no construct is measured by a single question and adding measures to explore further components of well-being or to examine well-being within specific life domains.
  • Exploring geographically nested and detailed sub-group measurements. The sampling methodology of the European Social Survey is based on randomly selecting representative samples within a country as a whole so that the resulting data provide a reliable indication of average well-being at national level, as well as of well-being among key population subgroups. However, with more complex sample designs, well-being could be measured at local and regional levels, providing well-being accounts at local authority and regional level, which could then be grouped up to the national level. Alternatively, over-sampling of particular sub-groups in the population, for example particular minority ethnic groups, would allow more detailed exploration of the well-being of subgroups for which otherwise there would not be sufficient numbers in a random population sample.

Indicator scores

National Accounts of Well-being indicators are designed so that they are measured on 0-10 scales, calibrated so that 5 always represents the average score across Europe. This average is calculated from the data for all the respondents in the 22 countries included in these National Accounts. Scores above 5 therefore show that well-being is higher than this average level and scores below 5 that is below the average.

The rest of this page describes in detail how indicator scores were calculated.

Calculating indicator scores

The subcomponent and component indicators within the framework are a set of composites which each combine responses to several questions (apart from two single item subcomponents). Subcomponents and components are then aggregated to create overall personal and social well-being scores. The groupings in which measures are combined derive from an iterative process based on analysis of well-being theory, the substantive content of the question wordings, and the statistical structure of the data.

After deciding on the groupings, indicators were calculated in a three-stage process.

First, scores for the original survey questions were standardised to allow meaningful comparison using standardised z-scores, measured in standard deviation units. Second, questions were aggregated to produce subcomponent and component scores by taking the unweighted mean of the z-scores for the lower level indicators or questions.

Third, the results were transformed on to 0–10 scales, calibrated so that 5 always represents the average score for respondents across Europe (the 22 included countries). In order to achieve this, the transformation was carried out using a curvilinear relationship. This allowed the scaling factor by which the z-scores are multiplied alter across the range of possible scores, and so that responses at the upper end of the distribution are spread out. The curvilinear relationship is described by the formula:
where zi is the z-score that we want to transform and ti is the transformed score.

mi and ci are determined from the theoretical minimum and maximum z-scores for the indicator in question, according to the following formulae. Note that the formulae shown below are correct and revise an error in those printed in Appendix 2 of the National Accounts of Well-being report.

where min is a negative value and max a positive value.

The resulting indicator scores allow for comparison on a single indicator between countries and demographic groups and would allow comparison over time should more data be collected. They also allow meaningful comparison between performance on different components and subcomponents. What they do not do is allow the comparison of performance with absolute targets or thresholds. Whilst 10 is the theoretical maximum score for any of the national accounts indicators, there is no definition of how high you have to score to have high well-being, other than the fact that scoring above 5 means scoring above the European average.

While their design means that the scores presented here are intrinsically relative to the average well-being levels measured in 2006/2007 in the group of 22 European countries included, this sort of relativity is in effect a feature of any national accounting system. In the same way, knowing the level of a country’s GDP in a particular quarter has little meaning, without knowing how its GDP has changed over the preceding period and how it compares to the GDP of other countries. The indicators therefore gain meaning when they are used to compare the experiences of groups located in different social and geographical space, and over different times.

You can download the country scores for each of the National Accounts of Well-being indicators in standardised units.

European Social Survey data

Since 2001, the European Social Survey (ESS) has begun mapping long-term attitudinal and behavioural change in Europe. Covering attitudes to religion, politics, discrimination and pressing policy concerns, the data reveal intriguing contrasts and similarities between amongst over 30 European countries. It is the first social science project to win Europe’s prestigious Descartes Prize “for excellence in collaborative scientific research”, and is also one of the first to become a European Commission ‘Infrastructure’, in recognition of its high technical and academic standards and their impact on advancing the field of comparative social measurement.

In 2005, Professor Felicia Huppert of the University of Cambridge, asked nef, together with four other research centres, to join an ultimately successful application to the ESS to develop a 50-item questionnaire module to assess ‘personal and social well-being’ across Europe. A key aim in the design of the module was to measure both the ‘feelings’ and ‘functionings’ aspects of well-being, as well as psychological resources, such as resilience and self-esteem. A further aim was to go beyond individualistic aspects of well-being, by also incorporating measures of interpersonal, social well-being.

The survey fieldwork was carried out using face-to-face interviewing across Europe from autumn 2006 onwards with data released in autumn 2007 (Round 3, edition 3.1). In each country a sample of over 1500 adults was drawn using random probability methods. The resulting dataset therefore contains detailed measures of the individual experiences of just under 45,000 people. These data have been used to construct the national accounts framework reported here, for 22 European countries participating in the survey, covering both EU and non-EU members. The dataset can be downloaded (Round 3, edition 3.1)., and the individual survey questions explored online, at the ESS data website.

We used the weighted dataset for 22 European countries, excluding Romania and Lativa, for whom full survey weights were not available, and Russia. In addition respondents who had missing data on any of the questions included in the accounts (except for one question not asked in Hungary – see Appendix 2 of the report for details) were also excluded. Russia was excluded because its large population means that the data have to have large weights applied (a quarter of the total weighted count for the combined dataset). This high weight could have lead to distortion in analysis. Furthermore as conditions in Russia are not typical in ‘Europe’, and indeed much of Russia is not geographically in Europe, we decided not to include it in the national accounts.

Read more about how we used ESS data to calculate indicator scores .

The indicators: an overview

The National Accounts of Well-being indicators on this website represent a working model of measures which governments can use to monitor the well-being of their citizens.

The indicators have been constructed by nef, using data from the 2006-2007 European Social Survey . This is the most comprehensive and detailed international survey of well-being ever undertaken.

The resulting survey dataset was used to develop an indicator set around two headline measures of personal well-being and social well-being : the two crucial aspects of how people experience their lives. As the diagram shows, each headline indicator is broken down into component indicators (and in places also subcomponent indicators) which reflect the different aspects which together comprise experienced well-being. The seven main components of personal and social well-being are also the elements used to create national Well-being Profiles (with emotional well-being split into its subcomponents).

In addition, the personal well-being and social well-being indicators can be brought together in different ways to form versions of a combined well-being indicator . As an example of a well-being indicator within a specific life domain, we have also created a satellite indicator of well-being at work . In the report we also analyse indicators of the dispersion of personal well-being and of social well-being, which reveal how equally levels of well-being are distributed within group.

The indicators were created by standardising and transforming the survey data so that all results are presented on 0–10 scales, with a score of 5 always representing the average score across the 22 European countries included.

Read more about how the indicators were constructed.

Developing a framework

The challenge in devising a framework for National Accounts of Well-being is to match the multiplicity and dynamism of what constitutes and contributes to people’s well-being with what gets measured. Our recommended framework for National Accounts of Well-being is therefore based on capturing:

  • More than life satisfaction. Understanding subjective well-being as a multifaceted, dynamic combination of different factors has important implications for the way in which it is measured. This requires indicators which look beyond single item questions and capture more than simply life satisfaction, the survey question on which much well-being research to date has been based. There are a number of reasons for this, including the multi-dimensional nature of well-being and the errors which are known to arise from using a single question to measure a psychological state. There is also evidence that the specific question on life satisfaction is problematic because it leads people to focus on some aspects of their lives but leave out others, is subject to bias because of its general nature, and is not very sensitive to policy changes. This makes it a very blunt tool on which to base government decisions, and suggests advantages to using a broader set of well-being indicators, of which the constituent parts have clear links to defined policy areas.
  • Personal and social dimensions. A focus on the quality of people’s experiences of their lives might suggest that the predominant concern of National Accounts of Well-being is with people as individuals, aggregating different people’s reports of how they are feeling within themselves and experiencing life from their personal standpoint. But research shows that a crucial factor in affecting the quality of people’s experience of life is the strength of their relationships with others. There is plentiful evidence that feeling close to, and valued by, other people is a fundamental human need and one that contributes to functioning well in the world. Our approach, therefore, advocates a national accounting system which measures the social dimension of well-being (in terms of individuals’ subjective reports about how they feel they relate to others) as well as the personal dimension.
  • Feelings, functioning and psychological resources. The traditional focus on happiness and life satisfaction measures in well-being research has often led to an identification of well-being with experiencing good feelings and making positive judgements about how life is going. Our framework for National Accounts of Well-being moves beyond that to also measure how well people are doing, in terms of their functioning and the realisation of their potential. Psychological resources, such as resilience, should also be included in any national accounts framework and reflect growing recognition of ‘mental capital’ as a key component of well-being.

Easterlin: why there is still a paradox

Richard Easterlin argues here, based on previously unpublished findings, that research which claims to have found evidence of a relationship between economic growth and well-being as measured via life satisfaction in developed nations, is based on an incorrect interpretation of the data. He says that economic growth has in fact, in most countries, been associated with increasing life satisfaction.

He writes:

“It is gratifying to see that scholars and policymakers are starting to pay serious attention to what people say about their well-being; over the past two to three decades surveys of subjective well-being have grown rapidly. At the University of Southern California in the past year or so my research associates and I have been trying to find out what the data for countries throughout the world tell us about an important question: ‘Does happiness improve commensurately with the rate of economic growth?’

Our interest has been to establish the facts without preconceptions as to the answer, pro or con. We tried to find countries with at least three comparable measurements of subjective well-being in a time series of at least a decade, making sure that the question asked is always the same and that there are no shifts in the question context or geographic coverage of the surveys so great as to invalidate comparisons at different dates. Here is what we have found:

  1. In sixteen developed countries with time series at least 21 years in length, there is no significant relation between the rate of economic growth and the improvement in life satisfaction.
  2. In seven countries transitioning to free market economies with time series that are at least 14 years in length and include a measurement before or close to the beginning of transition, there is no significant relation between the rate of economic growth and the improvement in life satisfaction.
  3. In thirteen developing nations spanning Asia, Africa, and Latin America with time series at least 10 years in length (the average being 15 years), there is no significant relation between the rate of economic growth and the improvement in subjective well-being.
  4. Pooling the data for all thirty-six countries above, there is no significant relation between the rate of economic growth and the change in life satisfaction.

How is it possible that able and serious analysts working with much the same data have come to a different conclusion – that well-being is positively associated with economic growth? There are several reasons, but the principal one is that they mistake a short term positive association between well-being and GDP per capita for the long term relationship. In major economic contractions and expansions, life satisfaction tends to follow the V-shaped pattern of GDP per capita, resulting in a positive association between the two over the short term. This is demonstrated most dramatically by the countries that have been undergoing economic transition since around 1990. But when the time span of the analysis is lengthened to the point where these short term movements cancel out, the positive relation between happiness and GDP per capita disappears. There is therefore good reason to regard the Easterlin paradox as alive and well as a problem for classical economic theory.”

The limits to measuring growth

In a now-classic paper from 1974, the American economist Richard Easterlin used survey data to show that aggregate levels of subjective life satisfaction in the US had not risen in line with post-War economic growth – this result was termed the ‘Easterlin paradox’: richer people at any given point in time may be happier, but as we all get richer, we don’t all get happier. Easterlin attributes this paradox to the importance of relative income to well-being. Once a certain absolute level of income is reached, gains in well-being are only due to having higher income relative to other people, not simply from having higher income per se.

These findings have been widely replicated in the empirical literature, but they have not gone unquestioned. A 2008 research paper by economists Stevenson and Wolfers has cast doubt on whether the Easterlin paradox holds in general for all countries. But here, Easterlin argues , based on previously unpublished results, that this interpretation of the data is incorrect and that economic growth has not, in most countries, been associated with increasing life satisfaction.

This debate will doubtless continue as more and better data are collected. But there are some key reasons why economic indicators fail to give a true picture of national well-being.

1. As the economies of developed countries have grown, improvements in well-being have stagnated

Even where increases in well-being are observed, the magnitude of any increase is small even in those countries where it may be statistically significant. Increases are not observed in all countries where they might be expected – no-one makes the case that life satisfaction has risen in the US, for instance, and there is evidence that US women have actually become less satisfied since the 1970s.

2. Well-being is much less strongly influenced by income than by other aspects of people’s lives

A review of the extensive research in this area suggests that only a small proportion of the variation in subjective well-being is attributable to material and environmental circumstances – perhaps as little as 10 per cent. Around 50 per cent is due to relatively stable factors such as personality, genes, and environment during the early years and 40 per cent is linked to the ‘intentional activities’ in which people choose to engage: what they do and how they behave (both on their own and with others), their attitudes to the events in their lives, and the sorts of goals they are motivated to pursue.

3. Wealth based on growth does not lead to equality of distribution

Modern economies are organised explicitly around the need to increase GDP, with relatively little regard for how it is distributed; business models are predicated on maximising profits to shareholders; and people are led to believe that the more disposable income they have – and thus the more they consume – the happier they will be. But economic indicators tell us nothing about whether people are in fact experiencing their lives as going well. There is a pressing need for a better, more direct way to measure society’s performance against its overarching goal of improving well-being.