Once a clear set of outputs has been identified based on the analysis required to meet user needs, it will be possible to make specific decisions about survey design, including the most appropriate survey vehicle, collection period, units of measurement and questionnaire design. These decisions should flow logically from the process of working down from user needs through analysis and output. The remainder of this chapter sets out a strategy for the measurement of subjective well-being. This includes both specific proposals for how a national statistical agency might approach the measurement of subjective well-being and more general information that can be used in a wider range of circumstances.
What other information should be collected:Co-variates and analytical variables
All potential uses of subjective well-being data require some understanding of how subjective well-being varies with respect to other variables. This applies whether the goal is understanding the drivers of subjective well-being - which requires understanding the causes of change - or where the main purpose is monitoring well-being over time and across countries - which requires understanding changes in demographics in order to understand a given change is due to changes in average levels or in the ratios of different population groups in society. It is therefore imperative to consider not only how best to measure subjective well-being perse, but also what other measures should be collected alongside measures of subjective well-being for analytical purposes.
A need for additional information to aid in interpreting and analysing results is not unique to subjective well-being. Most statistical measures are collected alongside, at the least, basic demographic data. Demographics matter to subjective well-being measures just as much as they do to labour market statistics. There are pronounced differences in average levels of subjective well-being across a range of different demographic groups, including based on gender, age and migration status (Dolan, Peasgood and White, 2008). For example, one of the best-known features of life satisfaction data is the “U-shaped” relationship between age and average life satisfaction (Blanchflower and Oswald, 2008). Similarly, there are differences between men and women in life satisfaction and affect measures that are not fully accounted for, even when controlling for income and education (Boarini, Comola et al., 2012).
Beyond demographics, subjective well-being affects and is affected by a wide range of different factors. Material conditions (e.g. income, consumption, wealth) affect subjective well-being (Dolan, Peasgood and White, 2008), but so do factors relating to quality of life. Health status, unemployment, social contact and safety all impact on life satisfaction in important ways (Boarini, Comola et al., 2012). In the context of affect data collected through time-use diaries, it is possible to collect information on an additional range of variables, such as the activity associated with a particular affective state.
Finally, there is a strong case for collecting some additional psychological variables alongside measures of subjective well-being. These include measures of personality type, expectations about the future and views about past experiences. Such measures may help to disentangle fixed effects at the personal level when it is not possible to collect panel data.
The precise range of co-variates to collect alongside measures of subjective well-being will vary with the specific aspect of subjective well-being that is of interest and with the research question being examined. Despite this, it is possible to present some general guidelines on the most important information that should be collected alongside measures of subjective well-being.
Most of the co-variates described below are regularly collected by national statistical agencies, and international standards for their collection do exist. No attempt is made here to specify the details of how these variables should be collected, and it is assumed that existing standards apply. This is not true for a few measures, such as those related to personality, trust and belonging. In these cases some general guidelines are provided. However, as many of these issues (such as the measurement of personality traits) are complex topics in their own right, this chapter does not provide detailed recommendations.