Would You Like to Know What Makes People Happy? An Overview of the Datasets on Subjective Well-Being
2015; Wiley; Volume: 48; Issue: 3 Linguagem: Inglês
10.1111/1467-8462.12105
ISSN1467-8462
Autores Tópico(s)Optimism, Hope, and Well-being
ResumoAustralian Economic ReviewVolume 48, Issue 3 p. 314-320 Data SurveyFree Access Would You Like to Know What Makes People Happy? An Overview of the Datasets on Subjective Well-Being Nattavudh Powdthavee, Nattavudh PowdthaveeCentre for Economic Performance, The London School of Economics and Political Science, London WC2A 2AE United Kingdom, and Melbourne Institute of Applied Economic and Social Research, The University of Melbourne, Victoria 3010 Australia; email < n.powdthavee@lse.ac.uk>.Search for more papers by this author Nattavudh Powdthavee, Nattavudh PowdthaveeCentre for Economic Performance, The London School of Economics and Political Science, London WC2A 2AE United Kingdom, and Melbourne Institute of Applied Economic and Social Research, The University of Melbourne, Victoria 3010 Australia; email < n.powdthavee@lse.ac.uk>.Search for more papers by this author First published: 31 August 2015 https://doi.org/10.1111/1467-8462.12105Citations: 11 AboutSectionsPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Abstract This article provides a guide for young economists wishing to conduct well-being research. It describes the different data sources commonly used in the study of people's subjective well-being, as well as provides a brief discussion on the types of well-being measures available within each dataset. 1 Introduction Economics is changing. There are now more researchers studying the determinants of people's life satisfaction, happiness and mental well-being than ever before.1 We are inevitably drawing closer to psychology and medicine. Having recognised the potentials for empirical research in this area, many household surveys around the world have started to incorporate a series of questions aimed specifically to elicit people's subjective well-being (SWB) into their standard set of questionnaires. This includes, but is not limited to, questions that ask survey participants to self-rate their satisfaction with life as a whole, their happiness yesterday and their usual state of mental well-being. From studying how people respond to these subjective questions across time and space,2 researchers have been able to provide insights into some of the most important philosophical issues in economics, including whether or not people adapt to adverse life events, such as disability and unemployment (Lucas et al. 2004; Clark et al. 2008; Oswald and Powdthavee 2008); whether economic growth is good for society in the long run (Easterlin 1974, 1995); and whether we can figure out a better way to value non-market goods, such as health and the environment (Van Praag and Baarsma 2005; Rehdanz and Maddison 2008; Luechinger 2009; Powdthavee and van den Berg 2011). Knowing which datasets to use may seem daunting to many young researchers coming into the field for the first time. To help ease the search process, this article seeks to provide readers with a guide to the typical datasets used in the study of human well-being. However, the list is not supposed to be exhaustive and is meant only as a guideline for PhD and young colleagues who are thinking about starting a project that uses SWB data as either the outcome variable or the input variable. The structure of the article is as follows. Section 2 describes the SWB measures and the kind of micro-econometric regression equations typically estimated in the literature. An overview of the SWB datasets can be found in Section 3. Section 4 discusses and concludes. 2 Measuring Subjective Well-Being 2.1 Affective and Cognitive Well-Being There are two main components of SWB (Diener et al. 1999). The first is affective well-being (AW) and the second is cognitive well-being (CW).3 By definition, AW represents moods and emotions, which can either be positive or negative and can fluctuate significantly from moment to moment. On the other hand, CW involves a cognitive evaluation process of how satisfied one is with one's life as a whole. Although both measures are highly correlated within the same dataset, research in psychology has shown that the two constructs are separable and additive (Lucas, Diener and Suh 1996). Affective well-being and CW are generally measured separately and independently. A person's AW can be elicited through a variety of self-reported questionnaires about his or her current (or most recent) moods and emotions; for example, feelings of happiness, pride, joy, anger, guilt, anxiety and depression. One example of an AW question typically elicited in a household survey is: Have you recently been feeling reasonably happy, all things considered? 1. Much less than usual; 2. Less so than usual; 3. Same as usual; 4. Much more than usual. To elicit CW, survey participants are commonly asked the following self-rated life satisfaction question: How dissatisfied or satisfied are you with your life overall? 1. Not satisfied at all … 7. Completely satisfied. Other than a question about satisfaction with life overall, many household surveys also tend to ask their survey participants to self-rate their levels of satisfaction with different areas of life, including satisfaction with health, job, housing, marriage and leisure time. 2.2 Subjective Well-Being Function The general idea is that there exists a reported well-being function: where r is some reported number or level of either AW or CW, u (…) is to be thought of as the person's true well-being, h (·) is a continuous non-differentiable function relating to reported well-being, z is a set of observable characteristics of the individual, t is time, p is a set of personality traits and other unobserved time-invariant characteristics and e is an error term that subsumes, among other factors, the inability of human beings to communicate accurately their well-being level (Blanchflower and Oswald 2004). We assume that h (·) rises in step with u (…). Responses to AW and CW questions are normally treated as ordinal and, hence, are usually estimated using ordinal regression models, such as ordered logit and ordered probit. However, recent research has shown that it makes virtually no difference whether one assumes cardinality or ordinality in the SWB data, although it is important for researchers working with SWB data to properly account for the presence of unobserved characteristics, p, from biasing the estimates of interest (Ferrer-i-Carbonell and Frijters 2004). Generally, a good longitudinal dataset (that is, one with a reasonably large N and T) is required to overcome the problem of unobserved heterogeneity bias in cases where the explanatory variables of interest are not randomly distributed across individuals in the sample. 3 Data 3.1 Cross-National Data Perhaps the most used dataset for cross-national comparisons of SWB is the World Values Survey (WVS). The WVS is a repeated cross-national survey of individuals which has been conducted at the global level since 1981 (Inglehart et al. 2000). There were 10 participating countries featured in the first wave of the WVS (1981–1984). This number grew to 52 participating members in its latest wave (Wave 6, 2010–2014), with some members joining and/or leaving in between waves. Overall, the WVS has interviewed over 80 nations in its history. Although the number of people interviewed in each country varies greatly, a minimum of 1,000 respondents from each member is required.4 Data on life satisfaction are present since Wave 1 for the majority of participating nations in the WVS. The phrasing of the question in English, which has been translated for all participating countries in the WVS, is: 'All things considered, how satisfied are you with your life as a whole these days?', with possible answers ranging from 1 ('Dissatisfied') to 10 ('Satisfied'). The WVS also contains a question about the respondent's happiness, which is more of a measure for AW than CW, and the phrasing of the happiness question is: 'Taking all things together, would you say you are: 1. Very happy; 2. Rather happy; 3. Not very happy; 4. Not at all happy?' Another large-scale collection of cross-national data of well-being is the Gallup World Poll (GWP). Begun in 2006 by the Gallup Organization, the GWP is a repeated cross-national survey of individuals from 132 countries. With the exception of Angola, Cuba and Myanmar, where the samples are urban, the GWP samples are nationally representative of people aged 15 years and older. The questionnaires in the GWP, like WVS, cover many aspects of SWB (for example, life satisfaction, happiness and moods), as well as several aspects of health, family and economic status.5 There are also other similar repeated cross-national surveys of well-being but they are regionally specific and therefore are relatively smaller in terms of scale than the WVS and GWP. This includes the Eurobarometer, Latinobarometer and the Afrobarometer.6 While two of the many advantages of using the WVS, the GWP or the barometer surveys to study well-being lie in their incredibly large sample size and the diversity of their sampled populations, one natural concern for well-being researchers is whether the vast differences in some of the participating members' cultures could potentially bias the estimates of both AW and CW. For example, studies have shown that people from Asia systematically report lower life satisfaction than people in America. Much of these differences, argued by many researchers, can be explained by the differences in cultures (which are largely unobserved to researchers) rather than by the differences in socioeconomic status (for example, Diener, Oishi and Lucas 2003, 2009; Oishi 2006), thus implying that any cross-national results have to be interpreted with care. 3.2 Cross-Sectional Data One of the earliest cross-sectional datasets on SWB is the General Social Survey (GSS), which is a nationally representative, repeated cross-sectional dataset for the United States. Since 1972, the GSS has been asking respondents the following AW question: 'Taken together, how would you say things are these days – Would you say that you are happy, pretty happy or not too happy?' There is, however, no question on life satisfaction in the GSS.7 The GSS has been used in many important studies, including in an article by Richard Easterlin on the unified theory of income and SWB (Easterlin 2001) and an article by Rafael Di Tella, Robert MacCulloch and Andrew Oswald on the relationship between macroeconomic indicators and SWB (Di Tella, MacCulloch and Oswald 2001). Another important source of information on SWB in the United States is the Behavioral Risk Factor Surveillance System (BRFSS). Established in 1984, the BRFSS is a state-based system of health surveys that collects information on health risk behaviours, preventive health practices and health care access primarily related to chronic disease and injury. Currently, data are collected monthly in all 50 US states and more than 350,000 adults are interviewed each year, making the BRFSS the largest telephone health survey in the world. The BRFSS started collecting data on life satisfaction for the first time in 2005, which means that there is currently little work on life satisfaction using this dataset.8 An almost-equivalent survey to the BRFSS is the Health Survey for England (HSE).9 The HSE is an annual, nationally representative survey and is designed to monitor the nation's health. Information is collected through a combination of face-to-face interviews, a self-completed questionnaire and a series of medical examinations conducted by a nurse. There are both AW and CW questions in the HSE, with the AW being elicited through the General Health Questionnaire (GHQ-12) and the CW being elicited through the life satisfaction questionnaire. Both BRFSS and HSE are perhaps two of the best cross-sectional datasets for researchers wishing to study the link between SWB and different measures of physical health, including biomarkers, such as blood pressure and cortisol level. 3.3 Longitudinal Surveys There are perhaps three main nationally representative longitudinal datasets used in the studies of SWB. They are: (i) the British Household Panel Survey (BHPS); (ii) the German Socio-Economic Panel (SOEP); and (iii) the Household, Income and Labour Dynamics in Australia (HILDA) Survey. The BHPS is a multi-purpose study and a nationally representative sample of British households, containing over 15,000 adult individuals in the United Kingdom (Taylor et al. 2002).10 The survey has been conducted between September and Christmas of each year from 1991 to 2008. From wave 1 onward, individuals are asked a battery of self-completed questions about their usual emotional states. These AW questions, more commonly known as the General Health Questionnaire (or GHQ-12), ask respondents to indicate on a four-point scale from 1 ('No more than usual') to 4 ('Much more than usual') how often over the past few weeks they had lost sleep over worry, felt constantly under strain, felt they could not overcome difficulties, been feeling unhappy and depressed, been losing confidence and been feeling like a worthless person. The same individuals are also asked to indicate on a four-point scale from 1 ('Better than usual') to 4 ('Much less than usual') how often over the past few weeks that they had felt that they were playing a useful part in things, felt capable of making decisions, been able to enjoy day-to-day activities, been able to concentrate, been able to face up to problems and been feeling reasonably happy. Researchers typically use the Caseness score of GHQ, in which the number of times the person places himself or herself in the 'Fairly stressed' or 'Highly stressed' category are added up to form the total score, in their analysis. Many medical scholars have considered the scale to be a good proxy for mental stress and strain (for example, Guthrie et al. 1998). Individuals in the BHPS have also been asked to self-rate their level of satisfaction with life as a whole on a seven-point scale from wave 6 onward.11 Satisfaction with other domains of life are elicited in the BHPS, including satisfaction with income, health, housing, job, partner, social life and leisure time. The SOEP is a nationally representative, longitudinal survey that has closely followed approximately 13,500 West German individuals each year since 1984.12 The survey then expanded to include residents of the former East Germany following the reunification of Germany in 1990. Since 1984, individuals in the SOEP have been asked to rate their level of satisfaction with their life as a whole on a 10-point scale. The SOEP also contains other CW questions, including satisfaction with health and job. However, unlike the BHPS, it does not contain a standard set of AW questions that would allow researchers to annually track respondents' usual mental states. The HILDA Survey is a longitudinal survey that has been tracking members of a nationally representative sample of Australian households since 2001, containing an initial sample of nearly 20,000 individuals (Watson and Wooden 2012).13 The members of these participating households form the basis of the panel pursued in subsequent annual survey waves. Similar to the BHPS and the SOEP, interviews are conducted with all adults (defined as persons aged 15 years or older) who are members of the original sample, as well as any other adults who, in later waves, are residing with an original sample member. The main CW question in the HILDA Survey is the 10-point scale life satisfaction question, which has been asked in every wave since the survey's inauguration in 2001. The HILDA Survey also asks its respondents about their satisfaction with different domains of life, including satisfaction with employment opportunity, health, income, job, partner, housing, leisure, local community, children and feeling of safety, thus making both the BHPS and the HILDA Survey two of the most comprehensive longitudinal surveys on CW in the world. From wave 1 onward, the HILDA Survey also asks respondents a battery of mental health (SF-36) questions. These AW questions ask respondents to indicate on a six-point scale how much, during the past 4 weeks, they have been feeling nervous, feeling so down in the dumps that nothing could cheer them up, feeling calm and peaceful, feeling down and feeling happy. The responses are then recoded and added up to make a continuous single-item variable of people's usual mental health state. At present, both the BHPS and the HILDA Survey are among two of the best panel surveys of people's usual mental states measured annually in existence. 3.4 Cohort Surveys More recent research into the determinants of an individual's SWB has started looking at the long-term relationship between childhood characteristics and adult life CW and AW (Frijters, Johnston and Shields 2014; Layard et al. 2014). This requires a special type of data that tracks the same individuals over a long period of time throughout their life cycle. Two examples of such datasets are the National Child Development Study (NCDS) and the British Cohort Study 1970 (BCS). The NCDS is a longitudinal study that tracks the lives of all those living in Great Britain who were born in one particular week in March 1958.14 This covers a cohort of around 17,400 children, with follow-on data having been collected in 1965 (at age 7 years), 1969 (age 11 years), 1974 (age 16 years), 1981 (age 23 years), 1991 (age 33 years), 1999–2000 (age 41–42 years), 2004 (age 46 years) and 2008–2009 (age 50–51 years). Since the 1981 sweep of the data, the cohort member has been the main respondent. At ages 33, 42, 46 and 50 years, participants in the NCDS have been asked to rate on a 10-point scale their level of satisfaction with life as a whole. Similarly to the NCDS, the BCS is a longitudinal study that follows approximately 17,000 children living in Great Britain who were born in a single week in April 1970. Currently, the data are available for nine major follow-up surveys: 1975 (at age 5 years), 1980 (age 10 years), 1986 (age 16 years), 1991 (age 21 years), 1996 (age 26 years), 2000 (age 30 years), 2004 (age 34 years), 2008 (age 38 years) and 2012 (age 42 years). Since the 1991 sweep of the data, the cohort member has been the main respondent. Data on life satisfaction have been collected in the BCS at ages 30, 34 and 42 years. Both NCDS and BCS also collect a battery of indices that had been designed to elicit the person's mental well-being throughout their life course. One example of such index is the Rutter Malaise Inventory scale (Rutter, Tizard and Whitmore 1970), which is an index derived from a number of 'Yes' responses to: having backaches, feeling tired, feeling miserable and depressed, having headaches, worrying, having difficulty in falling asleep or staying asleep, waking unnecessarily early in the morning, worrying about health, getting annoyed by people, having twitches, becoming scared for no reason, being scared to be alone, being easily upset, being frightened of going alone, being jittery, suffering from indigestion, suffering from upset stomach, having poor appetite, being worn out by little things, experiencing racing heart, having bad pains in your eyes, being troubled by rheumatism and having had a nervous breakdown. 4 Conclusion All the data sources I have described should provide young researchers with plenty of opportunities to test different untested ideas and hypotheses about what makes people happy and satisfied with their life. Given that there are often direct policy implications from well-being research, coupled with the fact that many of these datasets are either made publically accessible through the Internet for free via registration or relatively affordable to purchase, compared to many other data sources, there is perhaps no better time to conduct research on the economics of happiness. Endnotes 1 According to Kahneman and Krueger (2006), a cross-tabulation of EconLit suggests that more than 100 published papers included an analysis of happiness and mental well-being data between 2001 and 2005, compared to just four papers from 1991 to 1995. 2 For discussions on the validity of SWB responses, see, for example, Kahneman and Krueger (2006) and Oswald and Wu (2010). 3 Latest research has also argued that there is also a one-third component of SWB, which is eudaimonic well-being (that is, feelings of meaningfulness and purpose) (Huppert and So 2013). 4 For details on the WVS and how to access it, see . 5 For details on the GWP, see . 6 For details on the Eurobarometer, see . For the details on Latinobarometer, see . For the details on Afrobarometer, see . 7 For details on the GSS, see . 8 One recent exception is the work by Oswald and Wu (2010). For details on the BRFSS, see . 9 For details on the HSE, see . 10 For details on the BHPS, see . 11 Except for wave 10, where there is a gap in the implementation of the life satisfaction question. 12 For details on the SOEP, see . 13 For details on the HILDA Survey, see . 14 For details on both the NCDS and the BCS, see . References Blanchflower, D. G. and Oswald, A. J. 2004, 'Well-being over time in Britain and the USA', Journal of Public Economics, vol. 88, pp. 1,359– 86. Clark, A. E., Diener, E., Georgellis, Y. and Lucas, R. E. 2008, 'Lags and leads in life satisfaction: A test of the baseline hypothesis', Economic Journal, vol. 118, pp. F222– 43. Diener, E., Oishi, S. and Lucas, R. E. 2003, 'Personality, culture, and subjective well-being: Emotional and cognitive evaluations of life', Annual Review of Psychology, vol. 54, pp. 403– 25. Diener, E., Oishi, S. and Lucas, R. 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