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Happiness and well-being
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Abstract
1.1 The conventional view of an individual’s well-being, or utility, in standard economic textbooks is that it employs an objective position, based on observable choices made by individuals (see Pindyck and Rubinfeld, 1997; Frank, 2002; Varian, 2002).
1.2 For example, in the study of employment choices, an individual’s utility is assumed to depend on labour income and leisure. An individual is then observed to prefer one bundle of work-leisure choice than another. Given that all the choices made between alternatives satisfy a certain criteria of reasonableness – ie if it is assumed that individuals are rational, fully informed, and seek to maximise utility, a utility function that will explain an individual’s preferences between different bundles of work-leisure choice can be inferred from behaviour.
1.3 Over the last few decades, however, there has been a movement within economics that claims that utility should be considered in terms of happiness, and that it can, and should, be measured.
1.4 This development has been fuelled by findings that preferences are often not a very good guide of the well-being associated with the consequences of choices (see eg Kahneman et al, 1991; Kahneman and Thaler, 2006). According to Daniel Gilbert (2006), people often choose to over work in hopes that they could reap the fruits – in terms of higher incomes – of their misery later. Yet when they get there, the happiness that can be gained from extra money is not as high as they often expected it to be.
1.5 The concern for the poor relationship between preferences and well-being outcomes has led to a surging number of research papers during the last decade that have looked specifically at the determinants of happiness. Over the years, researchers now have some insights into the things that make us happy (for a review, see Layard, 2005; Dolan et al, 2008).
1.6 In this review, I will concentrate on the economics of employment choices, with particular references to the role of income, unemployment, education, and leisure choices.
1.7 Three major trends will be discussed. The next section, however, will be used to discuss how to measure happiness and the validity of the happiness scales. A discussion on discontinuities and uncertainties of the research trends, as well as the implications for education will also be made in the latter section of the review.
Keywords: happiness, well-being, employment, work
Full article
Measuring happiness
2.1 Psychologists have been spending a considerable amount of time analyzing the sources of human satisfaction in detail for decades. In their view, happiness, or subjective well-being (SWB), is conceived to be the degree of how one views one’s life as a whole, or some particular domain of one’s life, as favourable. As an attitude that is not accessible to public observation, psychologists believe that a concept such as SWB can be studied, in part, by asking people how they feel.
2.2 One way to measure an individual’s SWB is through surveys, which may include single-item or multiple-item questions on how one view one’s state of well-being.
2.3 An example of one of the most widely used measures of SWB comes from responses to the standard happiness question in the World Values Survey, which asks people, “Taken all together, how happy would you say you are: very happy, quite happy, not very happy, not at all happy?” Each response then scores one to four points so that one has a numerical scale, running from the lowest well-being level (1. Not at all happy) to the highest well-being level (4. Very happy).
2.4 Another one of the most commonly used, single-item scales is the life satisfaction scale. The standard life satisfaction question, which can be found in the Eurobarometer Survey, asks individuals, “On the whole are you very satisfied, fairly satisfied, not very satisfied, or not satisfied with the life you lead?”
2.5 Among multi-item scales, one of the most prominent measures of an individual’s SWB is the General Health Questionnaire (GHQ) in the British Household Panel Survey (see Taylor et al, 2002). The GHQ focuses on two major areas – 1) the respondent’s inability to carry out normal functions such as the ability to make decisions about things or enjoy normal day-to-day activities, and 2) the appearance of new and distressing phenomena such as depression and loss of confidence.
2.6 The above SWB measures have been validated against neurological evidence (Davidson, 2004), physiological evidence (Steptoe et al, 2005; Blanchflower and Oswald, 2008), and a range of behaviours (Lyubomirsky et al, 2005), including suicide (Bray and Gunnell, 2006). It is the trend in SWB research that is focused on here.
Major trends in SWB research
SWB and income
3.1.1 Perhaps one of the most puzzling findings of all in the happiness literature is how, on average, measures of SWB have not changed much in the United States (Easterlin, 1974, 1995) and in Europe (Oswald, 1997) since the end of World War II, in spite of large increases in real income per capita for the people living in these countries.
3.1.2 For example, we can see from below that there has been a continuing increase in the real GDP per capita in America since mid-70s. Average happiness, on the other hand, does not seem to correspond to the increase in real income for the American people over time.
Source: General Social Survey
3.1.3 The lack of positive correlation in the macro-indicators between real GDP per capita and aggregate happiness levels within a country is somewhat worrying. It simply suggests that an increase in income for all may not translate directly to an increase in happiness for all. The highly counter-intuitive result has further been bolstered by evidence at the micro-level.
3.1.4 Whilst micro-data analysis for advanced industrialised countries often suggests a positive relationship between measures of SWB and income, it is not one would generally call a strong one; a meta-analysis by DeNeve and Cooper (1999) quote a mean correlation coefficient between income and SWB of 0.17 (over 85 independent studies).
3.1.5 This leads to many surveys in the field to conclude that the relationship between money and SWB is slight or non-existent (Myers, 1992; Diener and Biswas-Diener, 2002; Layard, 2005; Nettle, 2005).
3.1.6 There are several potential explanations as to why there is only a small observed correlation between income and SWB. For example, studies that have included measures of relative incomes find that additional income may not increase SWB if those in the relevant income group – such as our colleagues, neighbours, or friends – also gain a similar increase (see, for example, Clark and Oswald, 1996; Frank, 2000; Ferrer-i-Carbonell, 2005; Luttmer, 2005). More recently, studies have shown that measures of SWB also depend on more than simply relative incomes. They also depend upon the ordinal rank of an individual’s income within a comparison group. In other words, human beings care about where they stand on an income ladder in a group that they normally compare themselves with (see Brown et al, 2008; Powdthavee, 2008a).
3.1.7 For a given income level, having high aspirations and expectations reduce SWB (MacDonald and Douthitt, 1992; Stutzer, 2004). Aspirations themselves appear to be driven partly by past incomes, suggesting adaptation to higher levels of income (Stutzer, 2004). Generally, adaptation to income is shown in longitudinal studies to be complete, ie happiness bounces back to the level before the rise in income (Di Tella et al, 2005), although recent evidence seems to suggest that people are more likely to adapt quicker to a rise in income than to a fall in income (Ferrer-i-Carbonell and van Praag, 2008).
3.1.8 Furthermore, most studies on income and happiness failed to control for factors that are highly correlated with incomes such as working hours, time spent away from family and loved ones, and time spent commuting to and from work, all of which are potentially strongly negatively correlated with measures of SWB (for a review, see Powdthavee, 2008b).
3.1.9 There is also a possibility that the positive correlation between income and SWB is due largely to the reverse causation. In other words, it may be possible that an increase in income does not make people significantly happier. Rather, it is those who are happy that work harder and, as a result, earn more than others (for evidence, see Marks and Flemming, 1999; Diener et al, 2002; Graham et al, 2004).
3.1.10 The complex relationship between SWB and income has led to a number of papers attempting to establish the causal link between the two. Using various techniques of instrumental variables and natural experiments, it has been found that income does indeed have a positive, statistically significant, and sizeable effect on different measures of SWB (see, for example, Frijters et al, 2004; Luttmer, 2005; Gardner and Oswald, 2007; Knight et al, 2007; Powdthavee, 2008b).
SWB and unemployment
3.1.11 Previous literature on unemployment and subjective well-being is clear on one point: unemployed persons are significantly less satisfied with life than those who are in full-time employment.
3.1.12 Clark and Oswald (1994, p655), using the first wave of the British Household Panel Survey, conclude that “Joblessness depresses well-being more than any other single characteristic, including important negative ones such as divorce and separation.”
3.1.13 Using German longitudinal data, Winkelmann and Winkelmann (1998) find the effect of unemployment on life satisfaction to be negative, statistically significant, and large: it would require a sevenfold increase in income to compensate for the drop in life satisfaction after the onset of unemployment. They also find that any selection effects due to unemployment, eg unhappy people are more likely to enter unemployment, are minimal. Powdthavee (2008b), using the British panel data, find that the negative effect of unemployment on life satisfaction would require an increase in the annual income of approximately £143,000 to compensate.
3.1.14 While the picture is not always consistent, many studies find the negative unemployment effect to be larger for men than for women (see eg Clark, 2003; Blanchflower and Oswald, 2004) and non-linear in age (Gerlach and Stephan, 1996; Winkelmann and Winkelmann, 1998). More importantly, it should be noted that the above results represent the “non-pecuniary” effect of personal unemployment upon subjective well-being. Income loss, as well as other indirect effects, which may or may not occur alongside personally being unemployed, are controlled for.
3.1.15 The negative effect of unemployment on SWB can be attributed to psychological and social factors (Frey and Stutzer, 2002). The first is the psychological cost: unemployment can lead to a loss of self-esteem and personal control as well as produce depression and anxiety. This is reflected in numerous studies which find that the unemployed have worse mental health records and a higher suicide rate than those in work (for two excellent reviews of the psychological cost of unemployment, see Feather, 1990, and Darity and Goldsmith, 1996).
3.1.16 The psychological cost is significantly higher for those entering unemployment for the first time. In contrast, unemployment is less detrimental for those who have been unemployed longer or more often in the past (see Clark, Georgellis, and Sanfey, 2001; Clark, 2006). In Germany, both Lucas et al (2004) and Clark et al (2008) find that adaptation to unemployment is, however, far from complete, ie happiness does not bounce back to the level that was experienced by the individual before he or she became unemployed. In other words, unemployment starts off bad and stays bad for both men and women.
3.1.17 The second factor negatively affecting life satisfaction is the social cost: being unemployed has a stigma attached to it, especially in a world in which the norm is to have a job. The social cost of unemployment is thus smaller when there are more unemployed people in society (Clark, 2003; Powdthavee, 2007; see also Stutzer and Lalive, 2004, for the role of social work norms on the subjective well-being of the unemployed).
SWB and work hours
3.1.18 While the evidence is relatively clear that unemployment is very detrimental to SWB, the relationship between the amount of work and SWB is less straightforward.
3.1.19 There is ample evidence that inflexible and overtime work hours generally are associated negatively with various aspects of workers’ welfare, one of which is health, eg illness and injury risk, through fatigue and stress (eg Danna and Griffin, 1999; Sparks et al, 2001; Van Der Hulst, 2003).
3.1.20 For example, new workplace practices that lead to greater intensification of work or time doing repetitive tasks often lead to higher incidence of worker cumulative trauma disorders (eg Brenner et al, 2004).
3.1.21 However, one of the clearest negative effects of long work hours on well-being are on workers’ ability to balance their competing work and family responsibilities (Cornell Institute for Workplace Studies, 1999; Berg et al, 2003; Ganster and Bates, 2003).
3.1.22 While work-family imbalance is found consistently to be a by-product of long work hours, relatively little is known about the relationship between long work hours and measures of SWB such as happiness and job satisfaction (Ganster and Bates, 2003).
3.1.23 Results on the impacts of long work hours on personal and family happiness are mixed. The conventional view in economics is that people prefer leisure to work. However, Green (2004) finds that, while relatively longer work hours result in additional work strain, it does not reduce job satisfaction. In fact, working 46 or more hours per week is associated with higher levels of job satisfaction for the individual compared to working 30-45 hours a week. This finding goes against conventional view in economics that often view work as “bad”.
3.1.24 Nevertheless, there is some evidence which suggests that long work hours may be detrimental to some domains of well-being. For instance, Gray et al (2004) find that fathers working more than 40 hours are much less satisfied with their family compared to fathers working 35-40 hours a week. By contrast, a study by Kelly (2001) using Australian data finds that long work hours do not adversely affect men’s satisfaction with marriage or with their children (net of the effects of age, education, and occupational status).
3.1.25 Golden and Wiens-Tuers (2006) find that, while extra hours of work are associated with self-ratings of being in the highest possible health, it is not statistically significantly higher for those whose overtime work is required. Particularly when the work is mandatory, extra hours at work are associated with increased stress at work, fatigue at home and dissatisfaction with work-life balance.
3.1.26 However, much of the empirical research has used cross-section data to examine the relationship between long work hours and SWB, and has not been able to test the causal impacts of working long hours on SWB.
3.1.27 Gray et al (2004) suggest that the direction of the impacts of long work hours on SWB will be determined by the reasons people work those hours. This could range from negative reasons such as financial necessity or fear of job loss to positive reasons such as intrinsic enjoyment of their job.
3.1.28 With regards to the impacts of long work hours on the well-being of other family members, there is statistical evidence that a bad day at work for one partner can result in an increase in the other partner’s stress, as well as the level of dissatisfaction with marriage and family the following day (eg Bolger et al, 1987; Repetti, 1989; Roberts and Krokoff, 1990). Similarly, employed parents with work overload can significantly heighten stress and lower life satisfaction for their children (Crouter et al, 1999; Powdthavee and Vignoles, 2008). The spillover effects can also be long-lasting: a heightened level of stress experienced by parents today can still have an impact on a child’s happiness a year later (Powdthavee and Vignoles, 2008).
3.1.29 Unfortunately, to the best of my knowledge, very little is known about the relationship between the type of work and job satisfaction. More research is needed to look at whether some jobs are associated with higher level of job satisfaction experienced by the individual than others.
SWB and education
3.2 Results on education are mixed. While some researchers have found a positive link between life satisfaction and the level of years spent in formal education (eg Blanchflower and Oswald, 2004; Stutzer, 2004), others have found a negative correlation between education and GHQ (Clark, 2003) and job satisfaction (Clark and Oswald, 1996).
3.3 Education is thought to contribute to SWB through its impacts on health and income (Dolan et al, 2008). However, it may also be possible that education can reduce SWB through comparison effects, where education raises expectation as well as outcomes (Clark and Oswald, 1996; Clark, 2003).
3.4 In addition, level of education completed may also be related to unobserved personality traits such as motivation, intelligence, and optimism. As a result, it would be ideal to look to those studies that control for unobserved heterogeneity. However, because models that control for unobserved personality traits (ie fixed effects models) can only pick up the effect of individuals completing their education or returning to education at a later date and most respondents are unlikely to change their level of education during their time in a panel survey, most studies that used this method have found insignificant effect for education (see eg Meier and Stutzer, 2008; Powdthavee, 2008b).
SWB and leisure choices
Seeing family and friends
3.4.1.1 Studies on the link between SWB and social relationships have concluded that, overall, socialising with family, friends, and neighbours is positively associated with SWB (eg Burt, 1987; Putnam, 2000; Lelkes, 2006; Powdthavee, 2008b).
3.4.1.2 The positive correlation between SWB and seeing friends is observed at the young age (ie aged 11-16) (Powdthavee and Vignoles, 2008) and applies into older age (Ritchey et al, 2001). For example, Ueno (2005) find that, on average, children who are integrated into friendship networks at school have better mental health than those who are socially excluded. This correlation remains even when we take into account the respondents’ socio-economic status such as income, employment and education, as well as the selection effects, ie that happy people are more likely to be extravert and therefore more sociable (Baker et al, 2005; Powdthavee, 2008b).
3.4.1.3 The estimated correlation is also sizeable: According to Powdthavee (2008b), a move from not seeing family or friends for the whole year to seeing them almost every day raises SWB for an average individual as much as he or she receiving an additional income of £85,000 for that year.
3.4.1.4 One explanation for this positive correlation is that SWB tends to increase with the number of people available for discussing important matters. This idea of positive externality is relevant to the notion of social capital (“the influence of past action by peers and others in an individual’s social network and control system”) in order to maximise utility (Becker, 1996). In Becker’s view, social capital is seen as something approximating a public good that enters each individual’s well-being function.
3.4.1.5 However, despite the growing number of research papers on SWB and social relationships, cause and effect remain unclear here.
Community involvement and volunteering work
3.4.1.6 Generally speaking, members in both church and non-church organisations report, on average, higher levels of SWB than non-members (eg Berkman and Syme, 1979; Helliwell, 2003; Pichler, 2006).
3.4.1.7 However, there is little longitudinal evidence to show whether joining either church or non-church organizations leads to higher SWB or happier people are more likely to join these organizations than less happy people.
3.4.1.8 The finding on volunteering work is mixed. For example, Haller and Hadler (2006) find no relationship between volunteering and self-rated happiness or life satisfaction. By contrast, Meier and Stutzer (2008) find using German panel data that more regular volunteering work generally increases SWB. However, there is also some evidence that happier people are also more likely to do more voluntary work, which suggests that there may be a reverse causality that runs from SWB to volunteering work (Thoits and Hewitt, 2001).
Other leisure activities
3.4.1.9 Exercise – simple type such as gardening is associated with high levels of SWB (Ferrer-i-Carbonell and Gowdy, 2007). The amount of time engaged in physical activities are found to be positively associated with SWB for the over 60s (Baker et al, 2005).
3.4.1.10 However, little use has been made of large and longitudinal data sets, which makes it difficult to make any conclusion regarding the causality here.
3.4.1.11 One of the leisure activities that have been extensively studied is watching TV. In general, there is a positive correlation between TV watching and positive moods, as well as happiness or life satisfaction (eg Csikszentmihalyi and Kubey, 1981). However, a recent study using a large-scale European data has shown that heavy TV viewing, and in particular those with significant opportunity cost of time, is negatively and statistically significantly correlated with life satisfaction. In addition to this, long TV hours are also associated with higher material aspirations and anxiety (Frey et al, 2007).
Discussions of the trends: uncertainties, discontinuities, and Implications for education
3.5 The main uncertainty for research on SWB is that, at least for the studies on work hours, education, and leisure choices, only correlations – and not causations – had been established. For instance, we can only extrapolate that watching too much TV reduces well-being because studies have found watching too much TV to be negatively associated with measures of SWB. However, it may also be that unhappy people may select themselves to watch more TV than happy people, thus making the causality runs from SWB to TV watching rather than the other way round. Therefore, the challenge is to design a study that randomly allocates people to watching too much TV and record their well-being. Nevertheless, such randomized experiment on a nationally representative sample can be very costly and probably unethical. For this reason, results taken from some of these studies have to be interpreted with care.
3.6 However, we are able to say more about the causal impacts of income and unemployment on SWB. The conclusions in these two areas are that (i) higher incomes can only improve individual’s SWB marginally, and (ii) unemployment is very detrimental to SWB, despite no change in the level of income. The psychic cost of unemployment is large. However, the size of the negative effect seems to depend on the duration of unemployment and the proportion of (other) unemployed people in the area.
3.7 What the above results seem to suggest is that there is clearly an identity, as well as meaning, to having a job that is independent from income. Given that the role of income on SWB is small, large compensations will have to be given to unemployed people to compensate for the drop in their well-being. The implication here is therefore to try and keep people employed at all cost.
3.8 Despite the fact that being employed is significantly better for SWB than being unemployed, achieving the right work-life balance is also important. While the results on the relationship between individual’s SWB and long work hours are mixed, studies have consistently shown that stress and strain experienced by the individual at work can have detrimental impacts on the well-being of other family members. The negative spillover effects can also be long-lasting, as is evident in a study by Powdthavee and Vignoles (2008) which finds parental stress today to still have an impact on a child’s happiness a year later.
3.9 The literature on the relationship between SWB and leisure choices is currently small. However, some conclusions can be made based on the current findings. One in particular is that different types of leisure may have different quantitative impacts on SWB, with one of the largest positive impacts coming from spending time socialising with friends.
3.10 However, looking forward to 2025 and beyond, the probable future is that there may be some changes to these trends. It is possible that, once people realise what makes them happy, they may begin to work fewer hours and take up more leisure time. If the majority of a country’s population does this, then this can have a significant impact on its economy as a whole and can, in turn, negatively affect individual’s SWB, eg the standard of living for all may fall beyond an acceptable level, thus leading to a fall in SWB for all (see Easterlin, 1979; Graham and Pettinato, 2002).
3.11 Consequently, how should we change the nature of education in order to best prepare citizens for life in the future? How could we shape education so that it can be used to help people find their balances?
3.12 There would, of course, be none provided that individuals are already fully aware of the well-being outcomes of their choices and that preferences always match their experiences. However, as suggested earlier in this review, research has shown that there are important discrepancies between what people ‘believe’ may make them happy and what actually makes them happy. More importantly, the literature does not suggest that individuals are constantly learning by themselves to correct such discrepancies.
3.13 For example, the extremely small economic significance of income, which is one of the key findings in the literature since late 1970s, raises many serious challenging questions. One important question in particular is: if extra incomes hardly make people in the developed world happier, why do we still spend most of our time striving for them?
3.14 One explanation for this is that, despite the finding is well-known amongst people working with SWB data, most of general population do not know that, after a certain level, an increase in income hardly makes us any happier. Most of us also do not even know about the quantitative trade-offs in terms of SWB between income, work hours, and leisure time. Thus, the question of interest is: how should we change education in order to inform young children about what their choices could mean in terms of their well-being in the future?
3.15 The first is for the educational authority to make these research findings available to everyone. Creating awareness is the first key to changing social norms and values.
3.16 Second, which is already under way, is that young children should be taught in the curriculum about how they could improve their well-being through making better choices in life. For example, this could include lessons on emotional intelligence, which will teach students to better manage their emotions that often govern our behaviours (see eg Goleman, 1995), as well as positive psychology, which is a recent branch of psychology that studies the strengths and virtues that enable individuals and communities to thrive (see eg Seligman, 1990). This type of education should be different to the current nature of education that has been shown to raise aspirations and expectations for students which, in turn, lower SWB.
3.17 By offering this type of education to young children, it may be possible for us to achieve a preferable future in terms of work and education for everyone involved. This would be a future where individuals are able to make life choices that match their well-being consequences perfectly. In other words, a preferable future is where measures of observable preferences are true reflections of people’s subjective experiences.
3.18 In sum, it seems that equipping citizens with knowledge of these research findings, as well as emotional skills, can help them make better informed decisions about their future choices.
References
Becker, G.S. (1996) Accounting for tastes. Part I: Personal capital; Part II: Social capital. Cambridge, MA., Harvard University Press.
Baker, L.A., Cahalin, L.P., Gerst, K. and Burr, J.A. (2005) Productive activities and subjective well-being among older adults: The influence of number of activities and time commitment. Social Indicators Research, 73, pp.431-458.
Berg, P., Kalleberg, A. and Appelbaum, E. (2003) Balancing work and family: the role of high commitment environments. Industrial Relations, 42 (2), pp.168-188.
Berkman, L.F. and Syme, S.L. (1979) Social networks, host resistance, and mortality: A nine-year follow-up study of Alameda county residence. American Journal of Epidemiology, 109, pp.186-204.
Blanchflower, D.G. and Oswald, A.J. (2004) Well-being over time in Britain and the USA. Journal of Public Economics, 88, pp.1359-1386.
Blanchflower, D.G. and Oswald, A.J. (2008) Hypertension and Happiness across Nations. Journal of Health Economics, 27, pp.218-233.
Bolger, N., DeLongis, A., Kessler, R.C. and Wethington, E. (1989) The contagion of stress across multiple roles. Journal of Marriage and the Family, 51, pp.175-183.
Bray, I. and Gunnell, D. (2006) Suicide rates, life satisfaction and happiness as markers for population mental health. Social Psychiatry and Psychiatric Epidemiology, 41, pp.333-337.
Brenner, M.D., Fairris, D. and Ruser, J. (2004) Flexible work practices and occupational safety and health: exploring the relationship between cumulative trauma disorders and workplace transformation. Industrial Relations, 43 (1), pp.242-266.
Brown, G.D.A., Gardner, J., Oswald, A.J. and Qian, J. (2008) Does wage rank affect employees’ well-being? Industrial Relations, 47 (3), pp.355-389.
Burt, R.S. (1987) Strangers, friends, and happiness. Social Networks, 9, pp.311-331.
Clark, A.E. (2003) Unemployment as social norm: psychological evidence from panel data. Journal of Labor Economics, 21 (2), pp.289-322.
Clark, A.E. and Oswald, A.J. (1994) Unhappiness and Unemployment. Economic Journal, 104 (424), pp.648-659.
Clark, A.E. and Oswald, A.J. (1996) Satisfaction and comparison income. Journal of Public Economics, 61, pp.359-381.
Cornell University Institute for Workplace Studies (CUIWS) (1999) Overtime and the American worker. Ithaca, NY, New York State School of Industrial and Labour Relations.
Crouter, A.C., Bumpus, M.F., Maguire, M.C. and McHale, S.M. (1999) Linking parents’ work pressure and adolescents’ well-being: Insights into dynamics in dual-earner families. Developmental Psychology, 35 (6), pp.1453-1461.
Csikszentmihalyi, M. and Kubey, R. (1981) Television and the rest of life: a systematic comparisons of subjective experiences. Public Opinion Quarterly, 45, pp.317-328.
Davidson, R.J. (2004) Well-being and affective style: neural substrates and bio-behavioural correlates. Philosophical Transaction of the Royal Society, 359, pp.1395-1411.
Danna, K. and Griffin, R.W. (1999) Health and well-being in the workplace: a review and synthesis of literature. Journal of Management, 25 (3), pp.357-384.
Darity, W. and Goldsmith, A.H. (1996) Social psychology, unemployment and macroeconomics. Journal of Economic Perspectives, 10 (1), pp.121-140.
DeNeve, K.M. and Cooper, H.M. (1999) The happy personality: a meta analysis of 137 personality traits of subjective well-being. Psychological Bulletin, 125, pp.197-229.
Di Tella, R., Haisken-DeNew, J. and MacCulloch, R. (2005) Happiness adaptation to income and to status in an individual panel. NBER Working Paper, No. W13159.
Diener, E., Lucas, R.E., Oishi, S. and Suh, E. (2002) Looking up and looking down: weighing good and bad information in life satisfaction judgments. Personality and Social Psychology Bulletin, 28 (4), pp.437-445.
Diener, E. and Biswas-Diener, R. (2002) Will money increase subjective well-being? Social Indicators Research, 57 (2), pp.119-169.
Dolan, P., Peasgood, T. and White, M. (2008) Do we really know what makes us happy? A review of the economic literature on the factors associated with subjective well-being. Journal of Economic Psychology, 29, pp.94-122.
Easterlin, R.A. (1974) Does economic growth improve the human lot? Some empirical evidence. In: David, P.A. and Reder, M.W. (eds), Nations and households in economic growth: Essays in Honour of Moses Abramowitz. New York, Academic Press.
Feather, N.T. (1990) The psychological impact of unemployment. New York, Springer-Verlag.
Ferrer-i-Carbonell, A. (2005) Income and well-being: an empirical analysis of the comparison income effect. Journal of Public Economics, 89, pp.997-1019.
Ferrer-i-Carbonell, A. and Gowdy, J.M. (2007) Environmental degradation and happiness. Ecological Economics, 60 (3), pp.509-516.
Ferrer-i-Carbonell, A. and van Praag, B.M.S. (2008) Do people adapt to changing circumstances? The discussion is not finished yet. ICREA and Institut d’Anàlisi Econòmica (IAE-CSIC), working paper.
Frank, R.H. (2000) Luxury Fever: Money and Happiness in an Era of Excess. Princeton University Press.
Frey, B.S., Benesch, C. and Stutzer, A. (2007) Does watching TV make us happy? Journal of Economic Psychology, 28, pp.283-313.
Frey, B.S. and Stutzer, A. (2002) What can economists learn from happiness research? Journal of Economic Literature, 40, pp.402-435.
Frijters, P., Haisken-DeNew, J.P. and Shields, M.A. (2004) Money does matter! Evidence from increasing real income and life satisfaction in East Germany following reunification. American Economic Review, 94 (3), pp.730-740.
Gardner, J. and Oswald, A.J. (2007) Money and mental well-being: A longitudinal study of medium-sized lottery wins. Journal of Health Economics, 26, pp.49-60.
Ganster, D. and Bates, C. (2003) Do long work hours decrease general wellbeing and increase family conflict? Manuscript. In: Annual Meeting of the Academy of Management, Seattle.
Gerlach, K. and Stephan, G. (1996) A paper on unhappiness and unemployment in Germany. Economics Letters, 52 (3), pp.325-330.
Gilbert, D.T. (2006) Stumbling on happiness. Knopf, New York.
Golden, L. and Wiens-Tuers, B. (2006) To your happiness? Extra hours of labour supply and worker well-being. Journal of Socio-Economics, 35, pp.382-397.
Goleman, D. (1995) Emotional intelligence. New York, Bantam Books.
Graham, C., Eggers, A. and Sukhtankar, S. (2004) Does happiness pay? An exploration based on panel data from Russia. Journal of Economic Behavior and Organization, 55 (3), pp.319-342.
Graham, C. and Pettinato, S. (2002) Happiness and hardship: opportunity and insecurity in new market economies. Washington DC, Brookings Institution Press.
Gray, M., Qu, L., Stanton, D. and Weston, R. (2004) Long work hours and the wellbeing of fathers and their families. Australian Journal of Labour Economics, 7 (2), pp.255-273.
Green, F. (2004) Work intensification, discretion and the decline in well-being at work. Eastern Economic Journal, 30 (4), pp.615-625.
Haller, M. and Hadler, M. (2006) How social relations and structures can produce happiness and unhappiness: An international comparative analysis. Social Indicators Research, 75, pp.169-216.
Helliwell, J.F. (2003) How’s life? Combining individual and national variables to explain subjective well-being. Economic Modelling, 20, pp.331-360.
Kelly, J. (2001) Consequences of working long hours. Australian Social Monitor, 4, pp.99-102.
Kahneman, D., Knetsch, J.L. and Thaler, R.H. (1991) Anomalies: the endowment effect, loss aversion, and status quo bias. Journal of Economic Perspectives, 5 (1), pp.193-206.
Kahneman, D. and Thaler, R.H. (2006) Anomalies: utility maximisation and experienced utility. Journal of Economic Perspectives, 20 (1), pp.221-234.
Knight, J., Song, L. and Gunatilaka, R. (2007) Subjective well-being and its determinants in rural China. University of Oxford, Department of Economics, Working Paper No. 334.
Layard, R. (2005) Happiness: Lessons from a new science. Allen Lane, London.
Lelkes, O. (2006) Knowing what is good for you. Empirical analysis of personal preferences and the “objective” goods. Journal of Socio-economics, 35, pp.285-307.
Luttmer, Erzo. F.P. (2005) Neighbours as negatives: relative earnings and well-being. Quarterly Journal of Economics, 120 (3), pp.963-1002.
Lyubomirsky, S., King, L. and Diener, E. (2005) The Benefits of Frequent Positive affect: Does Happiness Lead to Success? Psychological Bulletin, 131, pp.803-855.
Macdonald, M., and Douthitt, R. A. (1992) Consumption theories and consumers’ assessments of subjective wellbeing. Journal of Consumer Affairs, 26 (2), pp.243-261.
Marks, N.F. and Flemming, N. (1999) Influences and consequences of well-being among Australian young people: 1980-1995. Social Indicators Research, 46, pp.301-323.
Meier, S. and Alois, A. (2008) Is volunteering rewarding in itself? Economica, 75 (1), pp.39-59.
Myers, D.G. (1992) The pursuit of happiness. Morrow, New York.
Nettle, D. (2005) Happiness: The science behind your smile. Oxford, Oxford University Press.
Pichler, F. (2006) Subjective quality of life of young Europeans. Feeling happy but who knows why? Social Indicators Research, 75, pp.419-444.
Powdthavee, N. (2007) How much does money really matter? Estimating the effects of causal income on happiness. University of York, Department of Economics and Related Studies. Manuscript.
Powdthavee, N. (2008a) How important is rank to individual perception of economic standing? A within-community analysis. Journal of Economic Inequality, forthcoming.
Powdthavee, N. (2008b) Putting a price tag on friends, relatives, and neighbours: using surveys of life satisfaction to value social relationships. Journal of Socio-Economics, 37 (4), pp.1459-1480.
Powdthavee, N. and Vignoles, A. (2008) Mental health of parents and life satisfaction of children: A within-family analysis of intergenerational transmission of well-being. Social Indicators Research, 88, pp.397-422.
Putnam, R.D. (2000) Bowling alone: The collapse and revival of American community. New York, Simon and Schuster.
Repetti, R.L. (1989) Effects of daily workload on subsequent behaviour during marital interaction: The role of social withdrawal and spouse support. Journal of Personality and Social Psychology, 57, pp.651-659.
Ritchey, L.H., Ritchey, P.N. and Dietz, B.E. (2001) Clarifying the measurement of activity. Activities, Ageing and Adaptation, 26, pp.1-21.
Roberts, L.J. and Krokoff, L.J. (1990) A time-series analysis of withdrawal, hostility, and displeasure in satisfied and dissatisfied marriage. Journal of Marriage and the Family, 52, pp.95-105.
Seligman, M. (1990) Learned optimism: how to change your mind and your life. Free Press.
Sparks, K., Faragher, B. and Cooper, C. (2001) Well-being and occupational health in the 21st century workplace. Journal of Occupational and Organizational Psychology, 74 (4), pp.489-509.
Steptoe, A., Wardle, J. and Marmot, M. (2005) Positive affect and health-related neuroendocrine, cardiovascular, and inflammatory processes. Proceedings of the National Academy of Science of the United States, 102, pp.6508-6512.
Stutzer, A. (2004) The role of income aspirations in individual happiness. Journal of Economic Behavior and Organization, 54 (1), pp.89-109.
Taylor, M. F., Brice, J., Buck, N. and Prentice-Lane, E. (2002) British Household Panel Survey User Manual. Colchester, University of Essex.
Thoits, P.A. and Hewitt, L.N. (2001) Volunteering work and well-being. Journal of Health and Social Behavior, 42, pp.115-131.
Ueno, K. (2005) The effects of friendship network on adolescent depressive symptoms. Social Science Research, 34, pp.484-510.
Van Der Hulst, M. (2003) Long work hours and health. Scandinavian Journal of Work Environment Health, 29 (3), pp.171-188.
Winkelmann, L. and Winkelmann, R. (1998) Why are the unemployed so unhappy? Economica, 65 (257), pp.1-15.
http://www.campaign-for-learning.org.uk/cfl/events/promoting_pupil_wellbeing_a_dcsf_consultation_19september2008.asp
This document has been commissioned as part of the UK Department for Children, Schools and Families’ Beyond Current Horizons project, led by Futurelab. The views expressed do not represent the policy of any Government or organisation.
