Better understand the drivers of subjective well-being

The second major use of subjective well-being measures is to contribute to a better understanding of the drivers of well-being at an individual level. If it is accepted that measures of subjective well-being are valid, and that they accurately capture the concepts that they claim to measure - an overall evaluation of life or the experienced moods and emotions of an individual over a period of time - then it follows that such measures can be used to provide information on the relative contribution of different factors and circumstances to a person’s well-being - albeit with some noise due to both measurement error and the fact that a person’s subjective perception of their well-being is not necessarily quite the same thing as their overall well-being (for examples see Dolan, Peasgood and White, 2008; Helliwell and Wang, 2011; Boarini, Comola, Smith, Manchin and De Keulenaer, 2012).

Measures of subjective well-being can be used to help identify what factors are critical aspects of people’s well-being. In particular, such measures can be used to test intuitions about what factors matter most to people. This is potentially important to the broad agenda of measuring progress, since it provides an empirical way to test whether the outcomes used to measure progress align well with the factors that determine people’s perceptions of their well-being. Although people’s subjective perceptions are not necessarily equivalent to overall well-being for a number of reasons,⁶ measures of subjective well-being are unique in that they provide a relatively robust empirical source of information on such preferences, especially when non-market outcomes are involved. Without using subjective views of what matters the most to people, we would be left to essentially a priori judgements and anecdotal focus group research.

Subjective well-being measures are, however, unique in that they provide a relatively robust empirical source of information on what affects how people feel about their lives, which is an important component of overall well-being. By examining the level of subjective well-being actually achieved as a result of different decisions or approaches, policy-makers and individuals can better understand what matters to people on an empirical (rather than anecdotal) level. For example, subjective measures can be used to test more specific hypotheses about what aspects of policy are most important to people. Halpern (2010), for example, refers to an instance where the Merseyside police, in the United Kingdom, used data on how satisfied members of the public were with the service provided by the local policy, alongside more traditional performance measures on crimes committed and offence resolutions. In contrast to the expected hypothesis - which was that minimising the response time from the police was of crucial importance for public satisfaction - the evidence showed that it was much more important that police arrived when they said they would. For minor issues not involving safety, what mattered was punctuality rather than speed.

Going beyond just identifying what matters for well-being, measures of subjective well-being can assist in developing a better understanding of the trade-offs between different outcomes. Many policy problems require taking a decision about how to compare two fundamentally different types of outcome (see Box 1.2). Dolan and White (2010) note that these types of issue characterise many attempts to encourage “joined-up government”, where there is a need for different government agencies to consider the costs and benefits of a particular intervention not just on their primary outcome of concern, but also in terms of how these affect the outcomes of other government agencies.

Because measures of subjective well-being can capture the combined effect of all different changes in life circumstances on an individual’s perception of their well-being in a single measure, they can be used as a common metric for assessing the relative impact of fundamentally different outcomes. For example, Ferrer-i-Carbonell and Frijters (2004) use measures of overall satisfaction with life and satisfactions with specific outcome domains to assess the relative weights to attach to different outcome areas. Comparing the magnitude of the impact of health satisfaction on overall life satisfaction with the impact associated with housing satisfaction gives a way of quantifying the relative importance of each dimension within a particular sample, given where they started on each measure.⁷ Similarly, DiTella, Oswald and Maculloch (2003) used the coefficients from a regression on life satisfaction to investigate the inflation/unemployment trade-off. While the so-called “misery index” weights the unemployment rate and inflation rate equally as indicators of the negative impact of macroeconomic outcomes, Oswald and Maculloch’s analysis suggests that the impact of unemployment on subjective well-being is significantly greater than that of inflation.