What does "better understanding the drivers" mean, and why does it matter?
Understanding the drivers of subjective well-being means identifying variables that appear to have causal relationships with subjective well-being and examining some of the mechanisms through which drivers take their effects. Drivers of subjective well-being can include high-level well-being outcomes, such as income and health conditions, as well as specific life events and circumstances such as unemployment or the onset of disability, or specific patterns of behaviours and time use, such as commuting, watching TV, or interacting with friends and family.
Governments and researchers may be interested in the drivers of subjective well-being for a number of reasons, which are described in more detail in the sections that follow. Organisations and individuals may also have an interest in both the life circumstances and the daily events that influence subjective well-being in order to help inform decisionmaking and increase the well-being of workers and their families (Box 4.5).
Box 4.5. Wider public interest in the drivers of subjective well-being
Drivers of subjective well-being that could interest the general public include:
• Other high-level well-being outcomes (such as income, social connections and health) and the trade-offs
that may exist between them.
• The impact of certain life events, and the factors associated with positive adaptation to life events over
• How time use plays a role in both short-term mood states and longer-term well-being.
For example, Layard (2005) discusses how geographic labour mobility might bring positive economic benefits, but could potentially lead to an overall decrease in well-being, including subjective well-being, through losses in both work and social connections and the weakening of local community ties. The trade-off between economic benefits and the “hidden costs of mobility” (Dolan and White, 2007) can be explored through examining subjective well-being data, which can also be used to illuminate the factors associated with successful adaptation to relocation. This information may be useful for both the individuals making those trade-offs as well as organisations seeking to support the well-being of staff that have been relocated.
Data obtained through a combination of time-use and survey methods may also prove interesting for individual decision-making. Loewenstein and Ubel (2008) view informing the public about the likely consequences of particular actions as the main way in which affect data should be used. Kahneman and Riis (2005) meanwhile suggest that paying more attention to the allocation of time is one of the more practical ways to improve experienced well-being.
Several studies have provided insights into both subjective well-being gained from individual activities and the net impact that time allocation has on national well-being. For example, Kahneman et al. (2004) conducted an investigation of affect among nearly 1 000 working women in Texas using the Day Reconstruction Method. Among this sample, the three work-related activities (the morning commute, time spent at work, and the evening commute) were associated with the lowest average levels of positive affect balance, whilst intimate relations, socialising after work and eating dinner were associated with the highest average levels of positive affect balance. These authors propose calculating national accounts of well-being, based on the proportion of time individuals report being engaged in different activities, and the net affective experience reported during each of those activities (e.g. Krueger et al., 2009).
Individual activities that have been investigated in detail for both their short- and long-term influence on subjective well-being include TV watching, Internet use and commuting. Frey, Benesch and Stutzer (2007) for example reported that people watch more TV than they consider optimal for themselves, and that heavy TV viewers - particularly those with significant opportunity costs of time - report lower life satisfaction. Gross, Juvonen and Gable (2002) examined Internet use among adolescents and found that, whilst the overall duration of time spent online was not associated with evaluative subjective well-being or daily affect, the emotional closeness of instant message communication partners was associated with daily social anxiety and loneliness in school. Finally, Stutzer and Frey (2008) found that people with longer commuting times reported systematically lower satisfaction with life overall - consistent with the finding from Kahneman et al. (2004, above) that commuting is associated with low levels of positive affect balance.
Because of the various challenges associated with interpreting analyses of drivers, however, it may be misleading to place too much emphasis on comparing the relative effect sizes of the different drivers (see below). In communicating with the wider public, then, results of these types of analyses should not be presented as a recipe for subjective well-being, but rather more as a list of ingredients, with a broad indication of their impacts - and allowing flexibility to adapt the recipe according to taste.