Appendix B

The Subjective Well-Being Module of the American Time Use Survey: Assessment for Its Continuation

NOTE: For brevity, several pages of front matter and the appendix of Biographical Sketches of Panel Members that appear in the published version of this interim report have been omitted in this version. The reference list for citations in this appendix is at the end of the appendix.

The published report is available from the National Academies Press at http://www.nap.edu/catalog.php?record_id=13535.

Erratum: The citations and reference item given as Boeham and Kobzansky, (2012) should be Boehm and Kobzansky (2012).



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Appendix B The Subjective Well-Being Module of the American Time Use Survey: Assessment for Its Continuation NOTE: For brevity, several pages of front matter and the appendix of Bio- graphical Sketches of Panel Members that appear in the published version of this interim report have been omitted in this version. The reference list for citations in this appendix is at the end of the appendix. The published report is available from the National Academies Press at http://www.nap.edu/catalog.php?record_id=13535. Erratum: The citations and reference item given as Boeham and Kobzansky, (2012) should be Boehm and Kobzansky (2012). 153

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APPENDIX B 155 The Subjective Well-Being Module of the American Time Use Survey: Assessment for Its Continuation Panel on Measuring Subjective Well-Being in a Policy-Relevant Framework Committee on National Statistics Division of Behavioral and Social Sciences and Education

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156 SUBJECTIVE WELL-BEING Panel on Measuring Subjective Well-Being in a Policy-Relevant Framework ARTHUR A. STONE (Chair), Department of Psychiatry and Behavioral Sciences, Stony Brook University NORMAN M. BRADBURN, Department of Psychology, University of Chicago LAURA L. CARSTENSEN, Department of Psychology, Stanford University EDWARD F. DIENER, Department of Psychology, University of Illinois at Urbana-Champaign PAUL H. DOLAN, Department of Social Policy, London School of Economics and Political Science CAROL L. GRAHAM, The Brookings Institution, Washington, DC V. JOSEPH HOTZ, Department of Economics, Duke University DANIEL KAHNEMAN, Woodrow Wilson School, Princeton University ARIE KAPTEYN, The RAND Corporation, Santa Monica, CA AMANDA SACKER, Institute for Social and Economic Research, University of Essex, United Kingdom NORBERT SCHWARZ, Department of Psychology, University of Michigan JUSTIN WOLFERS, The Wharton School, University of Pennsylvania CHRISTOPHER MACKIE, Study Director ANTHONY S. MANN, Program Associate

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APPENDIX B 157 Contents SUMMARY 1 BACKGROUND AND OVERVIEW 1.1 Structure and Content of ATUS and the SWB Module 1.2 Objectives of the SWB Module 1.3 Uses of Data on Subjective Well-Being 2 ONGOING AND POTENTIAL RESEARCH APPLICATIONS 2.1 Time Use, Emotional Well-Being, and Unemployment 2.2 Assessing Validity of Short Versions of the Day Reconstruction Method 2.3 Episode-Based Pain Studies 2.4 End-of-Life Care 2.5 Transportation 3 ASSESSMENT 3.1 Value of the SWB Module Data to Date 3.2 Cost of Discontinuing the Module 3.3 Value of a Third Wave REFERENCES

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158 SUBJECTIVE WELL-BEING Summary The American Time Use Survey (ATUS), conducted by the Bureau of Labor Statistics, included a Subjective Well-Being (SWB) module in 2010 and 2012; the module, funded by the National Institute on Aging (NIA), is being considered for inclusion in the ATUS for 2013. The National R ­ esearch Council (NRC) was asked to evaluate measures of self-reported well-being and offer guidance about their adoption in official government surveys. The charge for the study included an interim report to consider the usefulness of the ATUS SWB module and specifically the value of continuing it for at least one more wave. Among the key points raised in this report are the following: • Value The ATUS SWB module is the only federal government data source of its kind—linking self-reported information on indi­ viduals’ well-being to their activities and time use. Important re- search has already been conducted using the data (for example, on the effects of unemployment and job search on people’s self- reported well-being), and work conducted with other, similar data sets has indicated the potential of the module to contribute to knowledge that could inform policies in such areas as health care and transportation. While the NRC Panel has not yet concluded its assessment of the policy usefulness of including one or more kinds of self-reported well-being measures on a regular basis in govern- ment surveys, it sees a value to continuing the ATUS SWB module in 2013. Not only will another year of data support research, but

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APPENDIX B 159 it will also provide additional information to help refine any SWB measurements that may be added to ongoing official statistics. • Methodological Benefits A third wave of data collection will e ­ nlarge samples by pooling data across years, which will enable more detailed study and comparison than has been possible to date of population subgroups, such as people in a given region and specific demographic groups (e.g., young people, the elderly). Be- cause two new questions—one on overall life satisfaction and one on whether respondents’ reported emotional experiences yesterday were “typical”—were introduced to the module only in 2012, at least one additional wave of the survey is needed to assess changes in responses to those questions over time. • Cost and Effects on the ATUS  As a supplement to an existing sur- vey, the marginal cost of the module, which adds about 5 minutes to the ATUS, is small. While further study of the module’s effects on response and bias in the main ATUS should be undertaken, it appears likely that these effects are modest because the module comes at the end of the survey after people have already been asked to report their activities for the preceding day. • New Opportunities  A third wave of the survey could also be used for experiments to improve the survey structure, should the module become permanent. The ATUS SWB module could be the basis for a standardized set of questions that could be added to other sur- veys which, together, might provide useful information about the causes and consequences of self-reported well-being in the general population.

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160 SUBJECTIVE WELL-BEING 1 Background and Overview 1 Research on subjective or self-reported well-being (SWB) has been ongoing for several decades, with the past few years seeing an increased interest by some countries in using SWB measures to evaluate government policies and provide a broader assessment of the health of a society than is provided by such standard economic measures as Gross Domestic Product (see, for example, Stiglitz, Sen, and Fitoussi, 2009). The National Institute on Aging (NIA) and the United Kingdom Economic and Social Research Council asked a panel of the National Research Council’s Committee on National Statistics to review the current state of research knowledge and evaluate methods for measuring self-reported well-being and to offer guid- ance about adopting SWB measures in official population surveys (see Box 1-1 for the full charge to the panel). NIA also asked the panel to prepare an interim report on the usefulness of the Subjective Well-Being module of the American Time Use Survey (ATUS), with a view as to the utility of continuing the module in 2013. The SWB module is the only national data source in the United States that links self-reported well-being information to individuals’ activities and time-use patterns. It provides researchers with unique insights that are only revealed by melding ratings of affect with time use information. The SWB module, overseen by the Bureau of Labor Statistics (BLS) and sponsored by 1 Thissection draws heavily from a presentation to the panel by Rachel Kranz-Kent of BLS, and from the Federal Register, Volume 76, Number 134 (July 13, 2011): http://webapps.dol. gov/federalregister/HtmlDisplay.aspx?DocId=25169&AgencyId=6&DocumentType=3 (accessed August 24, 2012).

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APPENDIX B 161 BOX 1-1 Panel Charge An ad hoc panel will review the current state of research and evaluate m ­ ethods for the measurement of subjective well-being (SWB) in population sur- veys. On the basis of this evaluation, the panel will offer guidance about adopting SWB measures in official government surveys to inform social and economic policies. The study will be carried out in two phases. The first phase, which is the subject of this statement of task, is to consider whether research has advanced to a point that warrants the federal government collecting data that allow aspects of the population’s SWB to be tracked and associated with changing conditions. The study will focus on experienced well-being (e.g., reports of momentary positive and rewarding, or negative and distressing, states) and time-based approaches (some of the most promising of which are oriented toward monitoring misery and pain as opposed to “happiness”), though their connection with life-evaluative measures will also be considered. Although primarily focused on SWB measures for inclusion in U.S. government surveys, the panel will also consider inclusion of SWB measures in surveys in the United Kingdom and European Union, in order to facilitate cross-national comparisons in addition to comparisons over time and for population groups within the United States. The panel will prepare a short interim report on the usefulness of the American Time Use Survey subjective well-being module, and a final report identifying potential indicators and offering recommendations for their measurement. A later, separate second phase will seek to develop a framework modeled on the National Income and Product Accounts to integrate time-based inputs and outputs, and SWB measures, into selected satellite, or experimental, subaccounts. NIA, was developed with guidance from several noted academics—Angus Deaton, Daniel Kahneman, Alan Krueger, David Schkade, and Arthur Stone among them—working in the field. Though the SWB module has only been in existence since 2010, it is not too early to begin assessing its potential value to researchers and policy makers. The purpose of this report is to inform planning discussions about the module’s future—it discusses the costs and benefits of a third wave of data collection, whether the survey module should be modified, and whether experiments should be done to improve the module should it become permanent. This brief report is intended to fulfill only one narrow aspect of the panel’s broader task as described in Box 1-1. It provides (1) an overview of the ATUS and the SWB module; (2) a brief discussion of research applica- tions to date; and (3) preliminary assessment of the value of SWB module data. The panel’s final report will address issues of whether research has

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162 SUBJECTIVE WELL-BEING advanced to the point that SWB measures—and which kinds of measures— should be regularly included in major surveys of official statistical agencies to help inform government economic and social policies. 1.1  Structure and Content of ATUS and the SWB Module The ATUS is the first federally administered, continuous survey on time use in the United States (and in the world). It is designed to obtain estimates of the time spent by respondents in childcare, at work, traveling, sleeping, volunteering, engaged in leisure pursuits, and a wide range of other ac- tivities. Time-use data augment income and wage data for individuals and families that analysts can use to create a more complete picture of quality of life in a society. Along with income and product data, information about time-use patterns is essential for research that evaluates the contribution of nonmarket work to national economies. The data also enable com- parisons between nations that have different mixes of market and non- market production modes. To illustrate, the households of two countries may enjoy similar home services and amenities—quality of meals, level of home cleaning and maintenance, elder and child care, etc.—but one may perform more of these tasks themselves (home production) while the other may more typically hire the tasks out in the market. The latter economy will register higher per capita gross domestic product even though the standard of living may be comparable in the two countries. Relatedly, countries may vary in the amount of time that individuals must work to achieve a given material standard of living, resulting in different amounts of leisure. This difference would also not show up directly in market (only) measures of economic activity, yet it is likely that it affects well-being. The ATUS provides nationally representative estimates of how people spend their time. It has been conducted continuously since 2003. The survey sample is a repeated cross-section of individuals who are drawn from U.S. households completing their eighth and final month of interviews for the Current Population Survey (CPS). One individual from each household is selected to take part in one computer-assisted telephone interview. Respon- dents are interviewed for the ATUS between two and five months after they rotate out of the CPS. Interviewers ask respondents to report all of their activities for one specified 24-hour day, the day prior to the interview. Respondents also report who was with them during activities, where they were, how long each activity lasted, and if they were paid. For the ATUS (following the core time diary questions but prior to the SWB module) some of the CPS information—for example, about who is living in the household and labor

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APPENDIX B 163 force status—is confirmed and updated.2 Measurement of socioeconomic well-being based on the ATUS is enhanced by its connection to the CPS which is rich in socio-demographic variables—namely, characteristics of the individual and the household including labor force status, income, state of residence, educational attainment, race and ethnicity, nativity, detailed marital status (divorced, never married, etc.), and disability status.3 The SWB module adds to the substantive content of the ATUS by revealing not only what people are doing with their time, but also how they experience their time—specifically how happy, tired, sad, stressed, and in pain they felt while engaged in specific activities on the day prior to the interview.4 This information has numerous practical applications for sociologists, economists, educators, government policy makers, business- persons, health researchers, and others. The module follows directly after the core ATUS; it was administered on an ongoing basis during 2010 and is being done again during 2012. The module surveys individuals aged 15 and over from a nationally representative sample of approximately 2,190 households each month. Respondents are asked questions about three activities selected with equal probability from those reported in the ATUS time diary (the well- being module questions are asked immediately after the core ATUS) (see Box 1-2). A few activities—sleeping, grooming, and private activities—are never included in the SWB module. The time diary refers to the core part of the ATUS, in which respondents report the activities they did from 4 a.m. on the day before the interview to 4 a.m. on the day of the interview. The precodes listed in Box 1-2 are for activities that are straightforward to code, but they are in no way representative of the full activity lexicon used by ATUS coders. The vast majority of ATUS activities are typed into the collection instrument (verbatim) and then coded in a separate processing step.5 The module also collects data on whether respondents were interact- ing with anyone while doing the selected activities and how meaningful the activities were to them. Respondents are asked to rate, for each of the three randomly selected activities, six feelings—pain, happy, tired, sad, stressed, and meaningful— 2 Technical details of the sample design and the survey methodology can be found in the American Time Use Survey User’s Guide: Understanding ATUS 2003-2011. Available: http:// www.bls.gov/tus/atususersguide.pdf [September 3, 2012]. 3 Information about who is living in the household and about labor force status is updated in the ATUS, which is important since the CPS data are a little dated by the time the ATUS interview takes place. 4 The module questionnaire can be found at http://www.bls.gov/tus/wbmquestionnaire.pdf [August 2012]. 5 There are more than 400 possible activity codes; a full list can be found at http://www.bls. gov/tus/lexiconnoex2011.pdf [June 27, 2012].

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172 SUBJECTIVE WELL-BEING behavior and activities with measures of well-being represents a potential policy application of time use and well-being data (Diener, 2006; Steg and Gifford, 2005). Archer et al. (2012, p. 1) describe how transportation fore- casting models may be used to help inform policy and investment decisions; they use the 2010 ATUS and SWB module data to develop a multivariate model designed to “capture the influence of activity-travel characteristics on subjective well-being while accounting for unobserved individual traits and attitudes that predispose people when it comes to their emotional feelings.” They find that “activity duration, activity start time, and child accompaniment significantly impact feelings of well-being for different activities” (includ­ ng travel). The authors add that “by integrating the well- i being model presented in this paper with activity-based microsimulation models of travel demand, measures of well-being for different demographic segments may be estimated and the impacts of alternative policy and invest- ment decisions on quality of life can be better assessed.”

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APPENDIX B 173 3 Assessment 3.1 Value of the SWB Module Data to Date It is still early to gauge the research and policy value of data emerg- ing from the ATUS SWB module. Even so, the kinds of research described above provide a preliminary indication of the insights that can be drawn from the ability to combine time-use information (as it links to specific activities) and self-assessments of well-being during those periods, which have relevance to policies ranging from commuting and home production to eldercare and maintaining good health. Without established and consistent historical data that combine time use and emotional experience, researchers would be limited to analyzing trends in evaluated time use that are difficult to tie to specific determinants. Several characteristics of the SWB module data contribute to its value: • Its status as the only national data source on subjective well-being that is linked to activities and time use. • Its Day Reconstruction Method (DRM)-like capability, unavailable with most other data sources on subjective well-being. • Its large enough sample sizes (especially if pooled over multiple survey years) to accommodate analyses of important subgroups of the population. • Its ability to facilitate research to begin solving difficult measure- ment and conceptual issues that have historically plagued work on subjective well-being.

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174 SUBJECTIVE WELL-BEING The fact that the ATUS SWB module is the only federal government data source of its kind gives it a potentially very high value. In particular, its approximation of the DRM is unique.12 As described above, linking of emotional states to daily experience may be the most directly relevant dimension of subjective well-being to policy. It is important to know how people feel when they are working, commuting, taking care of the old and the young, etc. In addition, identifying the context in which such activities take place, and asking respondents to rate well-being in that context (in the case of the ATUS, of the previous day) has the advantage of eliciting specific memories and, in turn, reducing bias associated with respondent recall. More generally, there has been enough progress in research on the measurement of subjective well-being to pinpoint specific policy domains and questions for which such data are useful. For example, cross-sectional data have proven important for research assessing the relative impact on people of income and unemployment13 and marriage and marital dissolution (­ eaton, 2011, p. 50) and, more generally, on the effect of policies where D large nonmarket components are involved (e.g., standard of living during end-of-life medical treatment). Data on subjective well-being have the po- tential to augment information in any situation in which market data are unavailable or not relevant and policy makers require criteria for choosing one course of action among two or more alternatives. In these cases, a range of evidence—revealed preference, stated preference, and subjective well- being measures—can usefully be drawn upon. And well-being measures that are tied to specific activities add a great deal of subtlety to these analysis; for example, while perhaps unemployed persons are able to engage more in activities they like to do (spend time with friends or relatives, rest, watch 12 The day reconstruction method is itself an approximation of more time-consuming experi- ence sampling and ecological momentary assessment methods; however, the day reconstruc- tion method captures information about episodes while the ecological momentary assessment method typically captures information about moments (Christodoulou, Schneider, and Stone, 2012). Simplified versions of the experience sampling and ecological momentary assessment methods—which, in some, sense represent the gold standard since they involve repeated assess­ ent in real time of people’s current hedonic well-being—are necessitated by burden, m time, and intrusiveness constraints in surveys. Though research is under way on the issue, it is still an open question how well, and under what conditions, the day reconstruction method approximation is adequate and useful. 13 One could reasonably conclude that addressing the recent high rate of unemployment was made even more urgent by findings from research on subjective well-being showing that, in terms of individuals’ utility, more was involved than simply an income effect. As Krueger and Mueller (2012) note, unemployment takes an emotional toll on people even while they are engaged in leisure activities. This calls into question an earlier conclusion by economists that people’s decreases in well-being because of unemployment may be partially compensated by increases in leisure.

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APPENDIX B 175 television, etc.), perhaps they enjoy each of those activities less relative to the employed. It will be a task for this Panel’s final report to provide an assessment of the extent to which subjective measures—including both global, evalua- tive measures and the more experiential measures that are the focus of this module—can or should be used to guide policy. Collecting data within the context of the ATUS has the potential to help researchers and policy makers evaluate whether these measures can be used in this way. 3.2  Cost of Discontinuing the Module The cost of discontinuing the module could be large since—if the value of such data became more apparent at some point in the future—restarting the survey would likely entail repeating start-up tasks and drawing again on political capital to make it happen. More importantly, the data con­inuity t that is now being established (with the 2010 and 2012 waves and the pro- posed 2013 wave) would be lost, affecting the ability of researchers to draw inferences from trends in reported time use and well-being. On the budget side, the marginal financial cost of adding the developed module to ATUS is relatively modest—about $178,000.14 That said, it would be useful to perform a full accounting to assess the quality of survey results and any effects that the addition of the SWB module may have on the quality of the overall CPS and ATUS. At least in terms of respondent burden and response rates, these concerns would seem to be modest for the former and unfounded for the latter. Indeed, by design, the ATUS is asked of those who have rotated out of the CPS, and modules are asked after the core ATUS is completed. This design element prevents modules from impacting response to the core ATUS and CPS.15 Because the SWB ques- tions are the last thing the respondent hears, the impact on the core ATUS is expected to be minimal. Similarly, the SWB module cannot, by design, bias the core diary responses. On the respondent burden question, for the 2012 SWB module, average time spent was approximately 5 minutes, which adds up to an estimated 1,100 hours for the 12,800 respondents (Federal Register). 14 The monetary cost of the 2012 module was higher ($273,000) as it included cognitive testing, data editing, interviewer training, and call monitoring activities by BLS. 15 If ATUS interviewers indicated that the survey will take 5 minutes longer, addition of the module could affect people’s willingness to participate (unit response rates). ATUS response rates have ranged from 52.5 to 57.8 percent. The response rates for 2010 (the first year of the SWB Module) was 56.9 percent.

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176 SUBJECTIVE WELL-BEING 3.3 Value of a Third Wave A third wave of data collection will add significant information beyond what has been collected so far. Most obviously, another year for the survey means an increased capacity for researchers to enlarge samples by pooling data across years. For some purposes—for example, to look at well-being effects associated with changes in employment during recessions (only a small percentage of the population is unemployed) or to investigate differ- ences across population subgroups—the number of observations needed to make valid statistical inferences well exceeds the annual sample size. This is especially true for comparing self-reported well-being score across smaller population subgroups. Almost all of the research to date using ATUS— which covers a wide range of topics, from household production, to work and leisure patterns, to childcare issues—has pooled data across years to increase the robustness of the statistical estimates.16 The need to enlarge samples (pool data) will be true for research applications that rely on the SWB module of the ATUS as well. Crucially, the 2012 module (the second wave) is only the first version of the survey that asks the overall life satisfaction (evaluative) well-being questions. In order to begin looking at sensitivity of measures and changes over time in these questions, at least one additional round of the survey— and ideally several more—are needed. A 2013 module would effectively double the sample size of respondents who have answered the evaluative well-being questions. Fielding another round of the SWB module will also add to the accu- mulating evidence needed to determine the value of incorporating it into the ATUS (and possibly elsewhere) on something more than an experimental basis. More generally, continuing the module will encourage discussion of how measures of subjective well-being can play a useful role in assessing the effects of public policies. On the research side, a third wave of data may shed light on unanswered questions about survey issues, data quality, and reliability (e.g., nonresponse bias, question ordering, context effects). Other technical issues that could be studied include mode of administration effects (is reported well-being lower in face-to-face interviews than for telephone or Internet modes?); activation/valence (are positive and negative affect two ends of the same bipolar dimension or are they separable unipolar di- mensions?), scaling (do populations from difference cultures or age groups systematically respond differently?), and memory bias (e.g., are negative events reported more or less frequently than positive events?). 16 A bibliography of research that has used ATUS data can be found at http://ideas.repec. org/k/atusbib.html (accessed August 7, 2012).

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APPENDIX B 177 A third wave of the survey could also be used to explore opportunities for experimentation designed to move toward an optimal survey structure, should the module become a permanent biannual ATUS supplement. Al- though it is unlikely that major changes could be made for a 2013 module, in the longer term it is certainly worth considering whether modifications could be made to increase its value. Examples of possible modifications to consider include • Split sample surveys—one-half the respondents could receive one question while the other half gets another; this would be useful for testing such things as sensitivity to different scales and question wording.17 • Finding the optimal number of activities to ask about. It is not obvious that three activities is the optimal number of activities to include on the module. It may be useful to ask about hedonic well-being associated with more activities in order to increase the reliability of daily estimates. Importantly, sampling more episodes increases the power to examine activity-specific effects, which may be particularly valuable for addressing policy questions. Doubling or even tripling the number of episodes may be cost-effective, a ­ lthough that benefit would have to be weighed against consider- ations of participant burden and the potential impact on response rates. • Selecting the “right” positive and negative emotion adjectives for module questions. Research supports the separation of positive and negative states but, more generally, should the module be focused more on suffering or happiness. The module could experi- ment with different adjectives and how interpretation varies across populations. • Expanding coverage to pain and other sensations. There are no good conceptual criteria for differentiating between sensations and “pure” emotional states or for how the two link together. Intui- tively, sensations are principally physiological states, in contrast to such feelings as anxiety, stress, and joy, which are principally sub- jective states. • Additional or replacement questions for consideration. A possible example is adding a question or two about sleep, such as: “How many hours of sleep do you usually get during the week?” or “How many hours of sleep do you usually get on weekends?” The 17 In its well-being survey, the UK’s Office for National Statistics has used, or plans to use, split trials to test for such things as sensitivity to different scales, question wording, and order and placement of questions.

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178 SUBJECTIVE WELL-BEING objective of such questions would be to find out if respondents’ reports about behaviors/emotions—feeling happy, tired, stressed, sad, pain—are influenced by (chronic) sleep deprivation or other sleep patterns.18 A methodological question is how well do people recall the previous night’s sleep? • Selecting among competing evaluative measures. Is the current Cantril approach, which is perhaps the most remote from affect measures, optimal? Alternative versions of the evaluative measure are common in the literature. It would also be interesting to make modifications to the SWB module so that day-of-week effects could be tested for different domains—health, education, transportation, etc. The merits of retaining some fraction of the sample for experimental work should be strongly considered, presumably not for 2013 but for sub- sequent years. One such experiment would be to determine sample sizes needed for subgroup analyses (e.g., day reconstruction method questions, which rely on some recall, are systematically answered differently by older and younger populations; in an aging society, it is important to be cognizant of these effects). The ATUS SWB questions could be the model for a standard set of questions that could be added to other surveys. With effective data link- ing, this could yield a rich set of findings about the relation to SWB of a wide range of covariates. If such a strategy were adopted, the experience of the ATUS SWB module will provide insights about how questions might perform on health, economic, and other kinds of surveys; and for determin- ing candidate surveys such as the National Health Interview Survey and the National Health and Nutrition Examination Survey, administered by the National Center for Health Statistics, and the Survey of Income and Program Participation, administered by the U.S. Census Bureau for adding modules. As noted above, there are potentially major advantages in having similar questions embedded across multiple surveys, especially as linking of microdata (including administrative) records becomes increasingly feasible. In light of changing budgets and priorities and emerging alternative data sources (e.g., private label, digital, Web-based), the nation’s statistical agencies have already begun to reexamine the content, modes, and struc- ture of their surveys and data programs more intensively than ever before. 18 Thisidea was raised by Mathias Basner, of the University of Pennsylvania School of Medi- cine, who noted that self-assessments of habitual sleep time overestimate physiological sleep time and that estimates of habitual sleep time based on ATUS overestimate self-assessments of habitual sleep times found in other population studies. Therefore, he suggested that it would be “very elucidating” to compare self-assessments of sleep time for the two questions above against estimates based on ATUS responses for the day before the interview day.

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APPENDIX B 179 New scrutiny of what trends in society are important to measure (such as those recommended by the Commission on the Measurement of Economic Performance and Social Progress; Stiglitz, Sen, and Fitoussi, 2009) may give rise to new opportunities to refocus statistical program coverage (and the surveys on which they are built) and to move into new research areas surrounding SWB. Smaller-scale studies and data collections, such as the ATUS SWB module, are needed to help judge the value and feasibility of embarking on production of national-level SWB statistics, such as those under development in the United Kingdom. Moreover, determination of the place of measures of subjective well-being in monitoring the economy and society cannot be done without the data. The question of whether self- reported measures of well-being should one day be reported alongside more standard economic statistics, such as those for income and employment and for financial markets, is as yet unanswered. A careful assessment of the data emerging from ATUS and the SWB module may help avoid mistakes if self-reported well-being statistics are ever produced on a larger scale. To the extent that evidence can be accu- mulated on the research and policy value of such data, a better basis for making these data collection and statistical program decisions can be estab- lished. The fact that the United States has a decentralized statistical system makes coordinating of the survey content related to subjective well-being a greater challenge than in countries with centralized statistics systems. However, it also affords the option of targeting development in the areas that are identified as the most relevant for policy and measurement—such as health, employment, or education—for which the argument is strongest for adding this kind of content. In light of these arguments, it is the view of the panel that the cost of the proposed 2013 SWB module is quite mod- est given its potential to inform decisions about potentially much larger statistical system investments.

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180 SUBJECTIVE WELL-BEING References Aguiar, M., and Hurst, E. (2007). Measuring trends in leisure: The allocation of time over five decades. The Quarterly Journal of Economics, 122(3), 969–1006, 1008. American Time Use Survey User’s Guide. (2013). Understanding ATUS 2003-2011. Report by the Bureau of Labor Statistics: Washington, DC. Available: http://www.bls.gov/tus/ atususersguide.pdf [September 2012]. Archer, M., Paleti, R., Konduri, K., and Pendyala, R. (2012). Modeling the Connection ­ etween Activity-Travel Patterns and Subjective Well-Being. Paper presented at the 92nd B Annual Meeting of the Transportation Research Board, Washington, DC. Boeham, J.K., and Kubzansky, L.D. (2012). The Heart’s Content: The Association between Positive Psychological Well-Being and Cardiovascular Health.” Psychological Bulletin, online April 17, 2012. Available: http://www.rwjf.org/pioneer/product.jsp?id=73919 (ac- cessed September 7, 2012). Christodoulou, C., Schneider, S., and Stone, A. (2012). Validation of a Brief Yesterday Measure of Hedonic Well-Being and Daily Activities: Comparison with the Day Reconstruction Method. Working Paper, June 4. Deaton, A.S. (2011). The Financial Crisis and the Well-Being of Americans. NBER Working Papers 17128. National Bureau of Economic Research, Inc. Available: http://www.nber. org/papers/w17128 (accessed July 29, 2012). Diener, E. (2006). Guidelines for national indicators of subjective well-being and ill-being. Applied Research in Quality of Life, 1(2), 151–157. Diener, E., Kahneman, D., Tov, W., and Arora, R. (2009). Income’s Differential Influence on Judgments of Life Versus Affective Well-being. Assessing Well-being. Oxford, UK: Springer. Huppert, F.A. (2009). Psychological well-being: Evidence regarding its causes and conse- quences. Applied Psychology: Health and Well-Being, 1, 137–164. Kahneman, D., and Deaton, A. (2010, August). High Income Improves Evaluation of Life but not Emotional Well-Being. Proceedings of the National Academy of Science. Krueger, A.B., and Mueller, A. (2012). Time use, emotional well-being and unemployment: Evidence from longitudinal data. American Economic Review, 102(3), 594–599.

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APPENDIX B 181 Krueger, A.B., and Stone, A.A. (2008). Assessment of pain: A community-based diary survey in the USA. Lancet, 371(May 3), 1519–1525. Meyer, B.D., and Sullivan, J.X.. (2009). Economic Well-Being and Time Use. Working paper, June 22. Steg, L., and Gifford, R. (2005). Sustainable transportation and quality of life. Journal of Transport Geography, 13(1), 59–69. Stiglitz, J., Sen, A., and Fitoussi, J.P. (2009). Report by the Commission on the Measurement of Economic Performance and Social Progress. Available: http://www.stiglitz-sen-fitoussi. fr/documents/rapport_anglais.pdf (accessed August 2, 2012).

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