Subjective Well-being

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About Subjective well-being

Subjective well-being measures are designed to capture information about how people experience their lives. They are based on individuals’ self-reports, and common measures include questions about whether people feel satisfied, content and fulfilled in their lives overall, as well as a range of more day-to-day emotions, such as happiness, worry, depression, and sadness. If applied and interpreted carefully, subjective well-being measures can play an important role in complementing quality of life measures based on people’s objective life circumstances. Subjective well-being indicators provide the kind of direct measure of outcomes that is increasingly seen as a desirable way to evaluate and determine policy [1]. It is important to distinguish between subjective well-being (i.e., measures of how people experience their lives), and the more general construct of well-being, which includes both objective and subjective components. [2] [3]. [4]. Many definitions of well-being and child well-being exist. In a broad sense, well-being refers to the quality of people’s lives. Measures of well-being can include people’s material conditions (such as income and wealth, jobs, housing etc.) but usually go well beyond this, to include other outcomes that also matter to people – such as their health, education, environment, personal safety, social connections, and more. [5]; [6]. Subjective well-being measures can be a useful complement to, but not a replacement for, these broader measures of people’s well-being.

Subjective well-being definition

According to Ed Diener, an American psychologist, subjective well-being is multidimensional and includes positive and negative emotions (e.g. the frequency, duration and intensity of joy, pleasure, happiness but also anger, guilt, fear, depression, sadness), as well as global life satisfaction, and satisfaction with different aspects of one’s life (partnership, income, friends) [7]. Aspects of good psychological functioning (including feelings of autonomy, competence and purpose) can also be seen as part of a person’s subjective well-being.
Several different definitions of subjective well-being have been offered:

“Well-being, which we define as people’s positive evaluations of their lives, includes positive emotions, engagement, satisfaction and meaning.” [8]

“Subjective well-being is a broad category of phenomena that includes people’s emotional responses, domain satisfactions, and global judgments of life satisfaction. Each of the specific constructs need to be understood in their own rights, yet the components often correlate substantially […].” (Diener, Suh, Lucas and Smith, 1999)[9].

Kahnemann and Riis (2005)[10] consider subjective well-being as being a hybrid concept with two components, which can be labelled “experienced well-being” and “evaluated well-being”. Both components are subjective and refer to a time of reference. The first component is concerned with very short-term (or momentary) affective states – i.e., life as lived. The second component covers a much longer (or indefinite) time period, and refers to global subjective evaluations of one’s life overall – which could be considered life as remembered. In many instances, these two components can be expected to be highly correlated with each other. However, they are not always. The determinants and consequences of happiness are often treated as unitary but they should be measured separately. [11]

Reconciling these various definitions, the 2013 OECD Guidelines on Measuring Subjective Well-Being [12] takes an inclusive approach, where subjective well-being is understood as: “Good mental states, including all of the various evaluations, positive and negative, that people make of their lives, and the affective reactions of people to their experiences”. In practice, the measurement framework proposed by the OECD distinguishes between three components of subjective well-being, each of which need to be measured separately:

  • Life evaluation – which refers to reflective assessments of a person’s life as a whole, or some specific aspect of life. For example, classic evaluation measures can include questions about satisfaction with life as a whole, or satisfaction with specific domains of life (such as health or income).
  • Affect – which refers to both positive and negative feelings and emotions, such as happiness, contentment, worry, sadness, depression, anger, fear, etc. Affect measures are usually captured with reference to a specific time period (such as feelings “yesterday” or feelings “in the last four weeks”).
  • Eudaimonia – a diverse and (as yet) less well-defined construct, often used to refer to feelings of meaning and purpose in life (capturing the idea of a life “lived well”), but which can also be used in the context of good psychological functioning or “flourishing” (including feelings of autonomy, competence, social engagement, caring, and interest in learning/ personal growth).
Model of SWB.jpg

Source: OECD (2013), OECD Guidelines on Measuring Subjective Well-being, OECD Publishing.

Why does subjective well-being matter?

In general, people’s own views about their lives, and the quality of their day-to-day experiences, can play an important part in building up a picture of the well-being of the population. There are several reasons why it can be helpful to use subjective well-being as a complement to other more objective measures of life circumstances:
First, people’s feelings about life, and their emotional states, can be seen as intrinsically important for their quality of life. Someone who is deeply unsatisfied with their life, who feels that their life has no meaning or purpose, or who experiences extreme depression and sadness is unlikely to be viewed as having a good quality of life. While it is clear that people are sometimes willing to trade short-term feelings of happiness for other outcomes of value, it is also clear that people regard subjective well-being as an important outcome in its own right. [13], [14], [15]
Second, subjective well-being measures seem to be able capture aspects of life that other more conventional economic indicators can fail to highlight. For example, the importance of mental health, the quality of a person’s relationships, and feelings of freedom, autonomy and trust. Rising economic prosperity is a very important mechanism for improving people’s well-being, but rising GDP alone does not always guarantee political stability, social harmony, or increasing happiness. For example, data from the Gallup World Poll suggests that in Egypt and Tunisia people’s subjective well-being sharply declined in the years preceding the start of the Arab Spring in 2010, even though real GDP per capita was growing [16]. Life satisfaction has also been shown to help to explain the choices people make about moving between countries, over and above the economic factors that drive migration, such as GDP per capita [17].
Thirdly, there is evidence to suggest that low subjective well-being can be a precursor to other issues and problems in people’s lives, while high levels of subjective well-being have been associated with a range of positive life outcomes. Subjective well-being has been prospectively linked to objective well-being outcomes in fields such as health, experiences of work, and aspects of social connections – as reviewed by De Neve, Diener, Tay and Xuereb (2013); Diener and Chan (2011); Lyubomirsky, King and Diener (2005); and Pressman and Cohen (2005). [18], [19], [20] [21].

Measures of subjective well-being have a wide variety of potential uses and audiences. These can include:

  • Complementing other outcome measures (such as economic, social and environmental measures) to help understand whether people’s lives are improving.
  • Helping to better understand the drivers of subjective well-being – which can provide useful insights for policy-makers, charities, institutions and employers, as well as individuals who might seek to improve their own or other people’s quality of life.
  • Support policy evaluation and cost-benefit analysis, particularly where non-market outcomes are involved.

Subjective well-being offers a useful complement to (but not necessarily a replacement for) more traditional economic measures currently used in these fields.

Is subjective well-being relevant to public policy?[edit]

The question of whether subjective well-being should become a goal for public policy has been widely debated [22], [23] [24], [25] [26].

Even if maximising people’s happiness (or minimising people’s suffering) are not set as explicit policy goals, however, governments still play a role in establishing the societal conditions enabling individuals to become happy (Frey and Gallus, 2013), as well as those enabling people to avoid misery and suffering. There is also increasing evidence to suggest that policy can and does affect people’s subjective well-being, whether this impact is intended by policy-makers or not. This is largely part because government policy has a direct impact on some of the important drivers of subjective well-being, including health, material conditions, employment status, and how people spend their time. The delivery and quality of a wide variety of public services (ranging from healthcare to education) is also likely to affect how people feel.

Several recent publications have examined the role that subjective well-being could play in policy-making – for example, Diener et al., 2009 [27],; [28]; Chapple, 2010 [29]; Stoll, Michaelson and Seaford, 2012 [30]; O’Donnell 2013 [31] [28] and a recent review published by the U.S. National Research Council, 2013 [32].

Use of subjective well-being indicators

  • Subjective indicators can give an overall picture of how a population or a group within the population are faring, as for example in relation to socioeconomic events (recession, …).
  • Subjective indicators can be used to highlight groups and individuals experiencing low well-being. This in turn, can inform decisions about service delivery and priorities.
  • Subjective indicators could be used to evaluate the impact of policy or service-level decisions.

Paul Dolan, Richard Layard and Robert Metcalfe (2011) [33] recommend the choice of one of the three broad types of subjective well-being measures (SWB) in accordance with the policy purpose. In particular, they recommend a routine collection of columns 1 and 2 and that at least column 1 is collected in all government surveys. Policy appraisal needs to include more detailed measures.


Table1 SWB.png

Figure replicated from Dolan, P., Layard, R. and Metcalfe, R. (2011), “Measuring Subjective Wellbeing for Public Policy: Recommendations on Measures”, special Paper No. 23, Center for Economic Performance, Marche. Available at:]

Methods for measuring subjective well-being[edit]

Subjective well-being is usually self-reported by the individual concerned, and is typically measured through survey questions (such as those included in general household surveys, labour force surveys, community surveys etc). Surveys might be conducted through face-to-face interviews, telephone interviews, pen-and-paper questionnaires, or web-based surveys.
Many alternatives to classical survey methods also exist. For example, subjective well-being measures have been included in time use studies, such as those using the Day Reconstruction Method, as well as in Experience Sampling Method (ESM) studies, or Ecological Momentary Assessment (EMA), each described below. All three of these methods are particularly suited to capturing aspects of people’s short-term affect (moods, feelings and emotions), and how these may vary over time and in line with different activities, locations, and social company (friends, partners, strangers etc). Smartphone applications have also been developed to capture people’s subjective well-being on a moment-by-moment or day-to-day basis (e.g. Mappiness MacKerron, G. and S. Mourato (2013), [34]). Attempts have also been made to assess feelings of subjective well-being through forms of social media, such as twitter [35] [32], or through textual analysis of other popular media [36].
The Day Reconstruction Method (DRM), developed by Kahnemann, Krueger, Schkade and Schwarz in 2004 [37] [34], requires participants to think about the preceding day, break it up into episodes, and describe each episode in detail (such as the activities and emotions experienced during episodes). The DRM involves memory, but is its designed to increase the accuracy of emotional recall by inducing retrieval of the specifics of successive episodes. The DRM also provides data on time-use, thus enabling subjective well-being measures to be linked to different activities, and also different interaction partners (colleagues, spouse, etc.) [38].
The “gold standard” for measuring short-term affective experiences is often considered to be Experience Sampling Method (ESM) or Ecological Momentary Assessment (EMA), in which participants are prompted at irregular intervals to record their current circumstances and feelings in real-time. In this method, participants often carry a handheld computer that prompts them several times during the course of the day (or days) to answer a set of questions immediately. This method minimizes the role of memory and therefore recall bias, but it can be expensive, intrusive, and difficult to implement among large samples. [39] [36] That said, mobile technology and the development of smartphone applications is rapidly reducing some of these traditional constraints.
The ideal measurement method will depend on the aspect of subjective well-being that is of most interest (life evaluations, affect, eudaimonia etc.), as a well as the use to which the data will be put – including the covariates that are planned for use in analyses. For example, if the research question concerns whether spending time in natural environments makes people feel happy emotions, the experience sampling method used in Mappiness might be appropriate. If, on the other hand, the research question concerns the impact that major life events (such as being made unemployed, or becoming disabled) has on feelings of satisfaction with life, a longitudinal household survey may be a useful method to adopt.

Example measures of subjective well-being

The OECD Guidelines on Measuring Subjective Well-Being (2013) [40] include a conceptual framework for measurement, and a set of six draft question modules that can be used to capture different aspects of subjective well-being in a variety of different study designs.
The OECD’s “core” question module is intended to provide a minimal set of measures of subjective well-being, covering life evaluation, affect and eudaimonia. It has been developed with national statistical agencies in mind as a key audience, and is suitable for use in household and other surveys where sample sizes are large, but space for additional questions can be extremely limited. The OECD Guidelines encourage national statistical agencies to implement the core question module in its entirety (and unmodified), to provide a solid foundation for comparisons among countries, population groups, and over time.


Core Questions .jpg

Source: OECD (2013), OECD Guidelines on Measuring Subjective Well-being, OECD Publishing.

Other question modules included in the OECD Guidelines offer examples of how different elements of subjective well-being can be examined in greater depth. These modules are not intended to be used in their entirety or unaltered, but provide a resource for those developing their own questionnaires. These supplementary modules include:

  • Module B, Life evaluation questions – this module includes a wider range of options for measuring life evaluations, including the Cantril Ladder and questions about past and future subjective well-being (as used in the Gallup World Poll), as well as Ed Diener’s Satisfaction With Life Scale.
  • Module C, Affect questions – a more detailed module covering a wider range of positive and negative affective states, drawing on items used in the Gallup World Poll and the European Social Survey.
  • Module D, Eudaimonic well-being – containing questions about people’s psychological functioning, based on elements of the European Social Survey and Diener et al.’s (2010) Flourishing scale.
  • Module E, Domain evaluation –which concerns people’s satisfaction with more specific aspects of their lives (e.g. satisfaction with health; satisfaction with personal relationships; satisfaction with your job etc). The items in this module are drawn from the Personal Wellbeing Index (International Wellbeing Group, 2006), developed and extensively tested by Bob Cummins and colleagues at Deakin University.
  • Module F, Experienced well-being – this module focuses on questions that could be included in a time-use survey, and shows examples from the day reconstruction method (DRM) used in the United States Bureau of Labour Statistics’ American Time Use Survey, as well as questions used in the Enquête Emploi du temps 2011, administered by INSEE, the French National Statistical Office.

The 2013 ad-hoc module of the EU Survey of Income and Living Conditions (EU-SILC) includes a range of subjective well-being measures similar to those included in the OECD’s core module. The EU-SILC survey, compiled by Eurostat, covers 27 EU countries as well as Croatia, Iceland, Norway, Switzerland and Turkey.
Since 2011, the UK Office of National Statistics (ONS) has included four experimental subjective well-being questions in their Annual Population Survey, which samples around 160,000 individuals per year.–2012-13/index.html

The personal well-being questions that ONS asks on its household surveys are:

  • Overall, to what extent do you feel the things you do in your life are worthwhile? (eudemonic approach)
  • Overall, how happy did you feel yesterday? (affect/ experienced well-being)
  • Overall, how anxious did you feel yesterday? (affect/ experienced well-being)

All questions are answered using a 0 to 10 scale where 0 is ‘not at all’ and 10 is ‘completely’. Further information on the ONS approach to measuring personal well-being can be found in the paper ‘Measuring Subjective Well-being’ [41] published by ONS in July 2011.
Several other national statistical offices also collect subjective well-being data at a national level – including Australia. Canada. France, Italy, Mexico, and Morocco. The United States Bureau of Labour Statistics’ American Time-Use Survey also includes measures of affect (experienced well-being). [42] [38]
Meanwhile, the European Social Survey in 2006 and the new economics foundation used the following questions in their questionnaires assessing subjective dimensions of well-being:

Subjective well-being dimension Example Question

SWB sample question.jpg

This table has been replicated from New Economics Foundation (2009), “A guide to measuring children’s well-being. Backing the Future: Practical Guide 2”, London, 16 September. Available at:

Validity, reliability, and methodological considerations

There is a large body of evidence on the reliability and validity of measures of subjective well-being, and on the methodological challenges involved in collecting and analysing such data. Indeed, given the academic interest in the topic and the challenging nature of the subject, the body of evidence on the strengths and weaknesses of measures of subjective well-being may even exceed that available for many measures regularly collected as part of official statistics (Smith, 2013) [43]. Although subject to some important methodological limitations, it is clear that for many potential uses, measures of subjective well-being, when carefully collected, are able to meet the basic standard of “fitness for purpose”.


Reliability concerns the extent to which a measure yields consistent results (i.e. whether it has a high signal-to-noise ratio):

  • Test-retest scores for measures of subjective well-being are generally lower than is the case for commonly collected statistics such as education and income, but higher than those found for more cognitively challenging economic concepts (such as household expenditure).
  • The more reliable multi-item measures of subjective well-being, such as Diener’s Satisfaction With Life Scale, exhibit higher reliability, although still less than for demographic or educational statistics.
  • Looking at country averages, the reliability of life satisfaction measures is generally well above the required threshold for acceptable reliability.
  • Measures of affect have, as expected, lower test-retest reliability than is the case for evaluative measures because moods change more frequently.
  • There is relatively little evidence on the reliability of eudaimonic measures.



Validity is the extent to which an indicator actually captures the underlying concept that it purports to measure:

  • Evidence strongly suggests that measures of both life evaluation and affect capture valid information.
  • The evidence base for eudaimonic measures is less clear. While some specific measures – such as those relating to “meaning” and “purpose” clearly capture unique and meaningful information, the picture with respect to eudaimonia as a whole is more ambiguous. This suggests that further work is needed before a definitive position can be taken on the validity of these measures.
  • While a range of issues could place limits on the validity of subjective measures of well-being, many of these have either a marginal impact on fitness for purpose (i.e. they do not substantively affect the conclusions reached) or can be dealt with through appropriate survey design and carefully considered analysis and interpretation of the data.
  • While cultural factors may not substantively bias multivariate analysis, there are reasons to be cautious about cross-country comparisons of average levels of subjective well-being.

Examples of evidence on the validity of subjective well-being measures:

SWB Evidence type.png

Source: OECD (2013), OECD Guidelines on Measuring Subjective Well-being, OECD Publishing.


Methodological considerations

Like all survey measures, subjective well-being data can be affected by the measurement methods used – and there are grounds to believe that subjective measures may be particularly sensitive to variations in survey methodology. Comparable data require comparable data collection methods, and maximising data quality by minimising the risk of bias should be a priority for survey design.

The OECD Guidelines [44] provide reviews and recommendations on a number of methodological issues that require careful consideration when designing surveys that include subjective well-being measures. These include:

  • Question wording and response formats
  • Question order and context effects
  • Survey mode and timing
  • Response styles

Interpreting subjective well-being data

Although the evidence for the reliability, validity, and usefulness of subjective well-being measures is strong, like all measures they are not perfect, and there are limitations that need to be considered by both producers and users of subjective well-being data. In particular, rates of measurement error, frame of reference effects and adaptation to life events mean that subjective well-being measures should be used to complement, rather than replace, other more objective measures of well-being. Subjective well-being can be viewed as an important component of quality of life (OECD, 2011; 2013) [45] [46] [2, 3], but it is not the only outcome that matters. For example, people seem to be willing to trade subjective well-being off with other outcomes, suggesting that feelings of happiness, satisfaction and purpose are not the only goals that individuals set for themselves in life.

Measurement error, response styles and “shared method variance”

Subjective well-being measures have been found to have a relatively high noise-to-signal ratio. For example, in reviewing the evidence, Diener, Inglehart and Tay (2013) [47] estimate that around 60-80% of the variability in life satisfaction scales is associated with long-term factors and that the remaining 20-40% is due to occasion-specific factors and errors of measurement. These occasion-specific factors can include one-off occurrences that affect large numbers of people simultaneously, such as major news events or Valentine’s Day (Deaton, 2011), [48] [42], or circumstantial events that may affect individuals’ momentary mood prior to the survey (Schwarz and Strack, 2003) [49]. Whilst the latter effect should be sufficiently random to wash out of large representative data sets, the former implies that a reasonable number of days, as well as people, need to be sampled to reduce the risk of systematic error.

Response biases refer to particular patterns or distortions in how individuals or groups of individuals respond to questions; response heuristics refer to (often sub-conscious) rules or short-cuts that respondents may use in order to help them select their answers. Where a respondent exhibits a repeated tendency towards a particular response bias or heuristic, this is referred to as a response style. Response styles present particular challenges for data interpretation when they vary systematically between countries or between population sub-groups within countries. This is relevant to all self-reported indicators, and there are not strong grounds for expecting subjective well-being measures to be uniquely affected.

Sound survey design seeks to minimise the risk that respondents will rely on characteristic response styles or heuristics to answer questions. This includes selecting questions that are easily translated and understood, and minimally burdensome on memory, as well as structuring and introducing the survey in a way that promotes respondent motivation. Other empirical approaches include using vignettes to identify response styles, and subsequently correct data [50], [51] [52] [44, 45, 46]. Further work is needed to establish the best way to measure and manage response styles in subjective well-being – and particularly whether or not consistent differences exist between countries in the extent to which certain response styles are present. This could have implications for how international subjective well-being data should be both analysed and reported.

Consistent response styles present a further risk to the analysis of cross-sectional self-report data, due to the issue of shared method variance. If people consistently use a preferred response style (such as more moderate or more extreme responding), this can spuriously inflate the observed correlation between self-reported measures. It could mean, for example, that self-reported health on a 0-10 scale might appear to be more strongly related to subjective well-being reported on a 0-10 scale, in comparison to income reported on a monetary scale – simply because of commonalities in the measurement method for health and subjective well-being (a problem known as “shared method variance”).

The problem of “shared method variance” is certainly not unique to subjective well-being, and requires consideration when reporting analyses of any surveys that rely on self-report (or a mixture of self-report and objective) measures. The use of panel data, and focusing analyses on changes over time, are two methods that can be used help to overcome some of the challenges of interpreting causal relationships among self-reported variables.

Social comparisons, frame of reference effects and adaptation to life events

A person’s responses to questions about subjective well-being will be informed by the limits of his or her own experience. “Frame-of-reference effects” refer to differences in the way respondents formulate their answers to survey questions, based on their own life experiences as well as their knowledge about the experiences of others, including both those they consider as within their “comparison group” and those outside it (Sen, 2002; Ubel et al., 2005; Beegle, Himelein and Ravallion, 2012) [53] [54] [55]. This knowledge and experience sets the frame of reference, relative to which a respondent’s own current circumstances and feelings are felt and evaluated.

Frames of reference produce real differences in how people experience their lives, rather than simply introducing ‘bias’. Thus, frame of reference effects do not challenge the validity of subjective well-being measures as measures of subjective constructs. They do, however, help to explain some of the imperfect relationship between a person’s current objective life circumstances, and the way they feel about life overall – which is informed by a person’s past as well as their present experiences. Framing effects matter when using subjective well-being to compare groups of people, because they concern the extent to which subjective well-being is a relative construct, rather than something reflecting absolute achievements in society. However, the available evidence suggests that, while framing effects may influence the size of group and country differences observed in subjective well-being data, they are not sufficiently large to prevent the impact of life circumstances on subjective well-being from being detected (e.g. Boarini et al., 2012; Fleche, Smith and Sorsa, 2011; Helliwell and Barrington-Leigh, 2010) [56] [57] [58].

Adaptive psychological processes can also either restore or partially repair subjective well-being in the face of some types of adversity (e.g. Cummins et al., 2003; Diener, Lucas and Napa Scollon, 2006; Clark et al., 2008; Riis et al., 2005) [59] [60] Clark, A.E., E. Diener, Y. Georgellis and R.E. Lucas (2008), “Lags and leads in life satisfaction: A test of the baseline hypothesis”, The Economic Journal, Vol. 118, pp. 22-243 </ref> [61]. Adaptation to positive life events such as marriage or winning the lottery has also been observed (Clark et al., 2008; Brickman, Coates and Janoff-Bulman, 1978) [62] [63]. The possibility of shifting reference frames and psychological adaptation again mean that differences over time, between groups and between countries might be smaller than one might expect based on objective changes or differences in current life circumstances.

However, there is strong evidence that adaptation does not always occur (or is incomplete) for a range of policy-relevant life circumstances, such as chronic pain from arthritis or caring for a severely-disabled family member (Cummins et al., 2003) [64] [59], disability (Oswald and Powdthavee, 2008a; Lucas 2007; Brickman, Coates and Janoff-Bulman, 1978) [65] [66] [67]
and unemployment (Lucas et al., 2003) [68]. Focusing on instances of incomplete adaptation could help policy-makers and public service providers to focus on areas where intervention may be most valuable.


EU-Statistics on Income and Living Conditions (2013, ad-hoc module) (EU-SILC, Eurostat)
World Values Survey (WVS)

United States General Social Surveyy (GSS)

American Time Use Survey (ATUS; United States Bureau of Labour Statistics)

European Quality of Life Survey (Eurofound)

Gallup World Poll

Paper and Reports

OECD Guidelines on Measuring Subjective Well-being (OECD, 2013)

How’s Life? 2013: Measuring Well-being (OECD, 2013)

How’s Life? 2011: Measuring Well-Being (OECD, 2011)

Subjective Well-Being: Measuring Happiness, Suffering, and Other Dimensions of Experience (National Research Council, 2013)

World Happiness Report 2013 (Helliwell, Layard and Sachs, 2013)

Third European Quality of Life Survey – Quality of Life in Europe: Subjective well-being (Eurofound, 2013)

Center for Global Development (CGD) essay on subjective well-being (June 2011). This CGD essay examines how we can, or should, use the results of happiness studies to drive policy advice. It advocates for taking considerable caution in the use of subjective well-being (SWB) polls for policymaking, because of the difficulty of interpreting SWB evidence with regard to SWB-maximising policy and given that SWB might not be what policy-makers want to maximise.

See also

Better Life Initiative

The Good Childhood Index

Child Subjective Well-being

Human Well-Being



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