entails long hours might raise a worker’s evaluative well-being, but the associated stress might reduce experienced well-being, at least in the short term. Similar comparisons could be made across professions. Respondents’ reported differences between experience and evaluative measures might also help explain why some people attach high meaning to work, career, and related time commitments while others focus more on simple day-to-day contentment and how or if these correlations vary across age, income, and other demographic or cohort factors. For education research, measures of multiple dimensions of subjective well-being may help provide an understanding of why students make (or do not make) the investments in schooling choices that they do (or do not) make.

The second new question for 2012 asks whether the respondents’ emotional experience yesterday (the day before the interview) was typical for that day of the week:

Thinking about yesterday as a whole, how would you say your feelings, both good and bad, compared to a typical Monday? Were they better than a typical Monday, the same as a typical Monday, or worse than a typical Monday (respondents answer “better,” “the same,” or “worse”).

This question may provide insights about day of week effects and day to day variation in reported well-being scores.

1.3. Uses of Data on Subjective Well-Being

Data from the SWB module supports the BLS mission of providing relevant information on economic and social issues. The data provide a richer description of work experience; specifically, these data describe how individuals feel (tired, stressed, in pain) during work episodes compared to non-work episodes, and how often workers interact on the job. Data from the module can also be used to measure whether the amount of physical pain that workers experience varies by occupation and disability status. The fact the SWB module can be linked to demographic characteristics of respondents—labor force status, occupation, earnings, household composition, school enrollment status, and other characteristics captured on the core ATUS and CPS—opens up a wide array of possible studies on the correlates of self-reported well-being.7

Collection of data on subjective well-being also supports the mission of the module's sponsor, the National Institute on Aging (NIA), to improve the health and well-being of older Americans. Examples of questions that can be answered include:

•  Do older workers experience more pain than younger workers on and off the job?

•  Is the age-pain gradient related to differences in activities or differences in the amount of pain experienced during a given set of activities?

•  Do those in poor health spend time in different activities relative to those in good health?

To date, much of the research on nonmarket components of health and well-being has been informed by global assessments of positive or negative affect averaged over time that are divorced from measures of time use or context. Nor has that research typically addressed age differences or age-related changes in these associations. In this vein, data from the SWB


7In addition, because the ATUS is conducted through the year, it is possible to study seasonal effects on well-being—a topic of interest in a number of research areas.

The National Academies | 500 Fifth St. N.W. | Washington, D.C. 20001
Copyright © National Academy of Sciences. All rights reserved.
Terms of Use and Privacy Statement