Subjective Well-Being: An Intersection between Economics and Psychology. Christopher J. Boyce

Subjective Well-Being:

An Intersection between Economics and Psychology

By

Christopher J. Boyce

Thesis submitted in fulfilment of the requirements for the degree of Doctor of Philosophy in Psychology

University of Warwick, Department of Psychology

September 2009

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1 Subjective Well-Being Research: An Overview ... 1

1.1 The Development of Subjective Well-Being Research in Economics and Psychology .. 2

1.1.1 The Use of Subjective Well-Being Data as a Proxy for Utility ... 3

1.1.2 Subjective Well-Being – A Viable Tool for Economic Analysis ... 6

1.2 Overview of Key Research Areas ... 8

1.2.1 Income and Well-Being ... 9

1.2.1.1 Evidence of a Relationship between Income and Well-Being... 9

1.2.1.1.1 Income and Well-Being over Time... 9

1.2.1.1.2 Income and Well-Being within a Country ... 10

1.2.1.1.3 Income and Well-Being across Countries... 10

1.2.1.2 Explaining the Income and Well-Being Data – Relative Income Effects ... 11

1.2.1.2.1 Relative Income Effects in Economics ... 12

1.2.1.2.2 Relative Judgment Models in Psychology ... 13

1.2.1.2.3 Rank Income Effects ... 14

1.2.1.3 Explaining the Income and Well-Being Data – Income is relatively Unimportant for Well-Being ... 15

1.2.1.4 Explaining the Income and Well-Being Data – Personality ... 18

1.2.1.4.1 Controlling for Personality in Economics... 20

1.2.1.4.2 Personality Interacts with Demographic Characteristics ... 21

1.2.2 Employment Status and Well-Being ... 23

1.2.2.1 Unemployment ... 23

1.2.2.2 Occupational Status ... 24

1.3 Overview of the Thesis ... 25

2 Money and Happiness: Rank of Income, not Income, Affects Life Satisfaction ... 27

2.1 Abstract ... 27

2.2 Introduction ... 28

2.3 Method ... 30

2.4 Results ... 31

2.5 Discussion ... 36

3 Money or Mental Health: The Cost of Alleviating Psychological Distress with Monetary Compensation versus Psychological Therapy ... 38

3.1 Abstract ... 38

3.2 Introduction ... 39

3.3 Money - A Common Metric for valuing Life Events and the Movement towards Compensation ... 40

3.4 The Clinical and Cost Effectiveness of Psychological Therapy ... 41

3.5 A Cost Effectiveness Comparison between Psychological Therapy and Direct Financial Compensation ... 42

3.6 Practical Implications of our Argument ... 45

3.6.1 For Judges ... 45

3.6.2 For Policy Makers and Society ... 47

4 Understanding Fixed Effects in Human Well-Being ... 49

4.1 Abstract ... 49

4.2 Introduction ... 50

4.3 The Use of Personality Measures in Economics ... 56

4.4 Methodology ... 58

4.5 Data ... 63

4.6 Results ... 67

4.7 Conclusion ... 77

4.8 Appendix ... 80

4.8.1 Note to Tables ... 80

4.8.2 Personality Variables in GSOEP ... 81

4.8.2.1 Big Five Personality Inventory ... 81

4.8.2.2 Positive and Negative Reciprocity ... 82

4.8.2.3 Locus of Control ... 83

4.8.2.4 Pessimism ... 83

5 Which Personality Types have the Highest Marginal Utilities of Income? ... 85

5.1 Abstract ... 85

5.2 Introduction ... 86

5.3 Methodology ... 90

5.4 Data ... 92

5.5 Results ... 95

5.5.1 Robustness Tests ... 100

5.6 Conclusion ... 103

5.7 Appendix ... 106

5.7.1 Note to Tables ... 106

5.7.2 Personality Variables in GSOEP ... 106

5.7.2.1 Big Five Personality Inventory ... 107

5.7.2.2 Individual Autonomy ... 107

5.7.2.3 Pessimism ... 108

5.7.2.4 The Construction of Personality Measures ... 108

6 The Dark Side of Conscientiousness: Conscientious People Suffer more from Unemployment ... 110

6.1 Abstract ... 110

6.2 Introduction ... 111

6.3 Method ... 113

6.3.1 Participants and Procedure ... 113

6.3.2 Measures ... 114

6.4 Results ... 115

6.5 Discussion ... 118

7 Do People Become Healthier after Being Promoted? ... 121

7.1 Abstract ... 121

7.2 Introduction ... 122

7.3 Earlier Work... 122

7.4 Methodology ... 125

7.5 Data and Estimation Issues ... 126

7.6 Results ... 129

7.7 Objections and Counter Arguments ... 136

7.7.1 Issue #1: Noise ... 137

7.7.2 Issue #2: Endogeneity ... 137

7.7.3 Issue #3: Poor Health as a Predictor ... 138

7.7.4 Issue #4: Sample Changes ... 139

7.8 Conclusion ... 141

7.9 Appendix ... 142

7.9.1 Notes to Tables ... 142

7.9.2 Sample Construction ... 143

7.9.2.1 Control Groups... 143

7.9.2.2 Treatment Groups ... 143

7.9.3 Definition of GHQ Mental Ill-health ... 144

8 Conclusion ... 145

8.1 Summary ... 145

8.2 Implications for Economic-Psychology Subjective Well-Being Research ... 148

8.2.1 The Use of Large Data Sets in Psychology ... 148

8.2.2 Improved Understanding of Social Comparisons ... 149

8.2.3 Rank Based Comparisons ... 151

8.2.4 Subjective Well-Being Research and Policy ... 151

8.2.5 The Link between Health and Occupational Status ... 152

8.2.6 Personality within Economics... 153

8.3 Conclusion ... 154

9 References ... 155

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Table 2.1: Pooled OLS regression on life satisfaction comparing logarithm of absolute income

and income rank by sample... 32

Table 2.2: Pooled OLS regressions on life satisfaction comparing logarithm of mean income and income rank using various reference groups ... 34

Table 4.1: Summary statistics across the 6 year panel used in analysis and a longer 12 year panel (N = 93016/135486) – non-standardised ... 66

Table 4.2: Fixed effect, REMT and pooled OLS life satisfaction regressions ... 68

Table 4.3: Predicting the fixed effects residual (from column 2 of Table 4.2) using the mean levels of various objective characteristics and personality variables ... 70

Table 4.4: Correlations between observable characteristics and the unobservable component of the fixed effect residual errors ... 73

Table 4.5: Introducing personality into life satisfaction regressions using the fixed effect vector decomposition technique (3rd stage) and the random effects model ... 74

Table 5.1: Summary statistics (N = 93256) – non-standardized ... 94

Table 5.2: Fixed effect and pooled OLS life satisfaction regressions ... 96

Table 5.3: Fixed effects and pooled OLS analysis of income interactions with personality ... 99

Table 5.4: Robustness of the personality-income interactions ... 101

Table 6.1: Two hierarchical regression analyses predicting the life satisfaction of individuals in the years following unemployment ... 116

Table 7.1: Pearson correlation coefficients for the three ill-health measures ... 129

Table 7.2: Ill-health over time within the whole sample ... 129

Table 7.3: Cross-section regression equations for subjective ill-health, visits to the doctor, and mental strain ... 130

Table 7.4: Ill-health among the non-promoted non-supervisors and those promoted to manager (at time T) ... 132

Table 7.5: Ill-health among the non-promoted and those promoted to any category (at time T) 135 Table 7.6: Difference-in-Difference ((T+3)-(T-1)) estimates (with controls) for individuals working in the public sector and in the manufacturing industry, those individuals who stay at the same address across all 5 years and those who stay in the promoted position up until T+5 ... 136

Table 7.7: Probit equations using health at T-1 as a predictor of promotion ... 138

Table 7.8: Regressions showing health differences across promoted groups, and those who subsequently left the workforce or changed role ... 140

Figure 6.1: The life satisfaction change following unemployment as moderated by conscientiousness ... 118

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This thesis would not have been possible without the help, advice and encouragement from so many people. I have been extremely fortunate.

First, I would like to thank Gordon Brown and Andrew Oswald for absolute first rate supervision. Both have always made themselves available to give me great guidance in my academic development. I have taken great pleasure from our many meetings and both have never failed to inspire me. I am also in great debt to Alex Wood who has been pivotal in my

development as a researcher and who helped me develop so many of the ideas in this thesis.

I would also like to thank the department of psychology at the University of Warwick for making the transition from economics to psychology surprisingly easy and providing an excellent academic climate in which to pursue my research. Everyone in my office has been hugely

supportive and I’d like to thank them for lifting my spirits on many a grey day.

I am extremely grateful to Roxanne Rees-Channer whom without I would never have thought it possible for me to do a PhD. Thank you for helping me to believe in myself. There are also many close friends who have shared with me both the good and bad times during the last 3 years. Thank you for listening to my moans. I’d also like to thank everyone I’ve ever had a conversation with about my “happiness” research and for helping me to stay passionate about what I do.

Finally, I’d like to thank my family for their love.

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The research reported in this thesis is my own work unless otherwise stated. No part of this thesis has been submitted for a degree at another institution.

Chapter 2 was written in collaboration with Gordon Brown and Simon Moore. Chapters 3 and 5 were written in collaboration with Alex Wood. Chapter 6 was written in collaboration with Alex Wood and Gordon Brown and Chapter 7 was written in collaboration with Andrew Oswald.

Chris Boyce

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Certain chapters have been previously published during the period of the PhD registration Copyright of these papers resides with the publishers, but under the terms of the copyright

agreements these papers are reproduced as chapters in this thesis. These papers are as follows.

Chapter 2: Boyce, C. J., Brown, G. D. A., Moore, S. C. (in press). Money and happiness: Rank of income, not income, affects life satisfaction. Psychological Science.

Chapter 4: Boyce, C. J. (in press). Understanding fixed effects in human well-being. Journal of Economic Psychology.

Chapters 3, 5 and 7 are currently under review.

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BHPS: British Household Panel Survey CBT: Cognitive Behaviour Therapy FE: Fixed Effects

FEVD: Fixed Effect Vector Decomposition GHQ: General Health Questionnaire GP: General Practitioner

GSOEP: German Socio-Economic Panel OLS: Ordinary Least Squares

R: Income Rank RE: Random Effects

REMT: Random Effects with a Mundlak (1978) Transformation RFT: Range-Frequency Theory

SES: Socio-Economic Status SR: Subjective Income Rank SWB: Subjective Well-Being

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This thesis uses subjective well-being data to understand the impact that an individual’s economic circumstances have on their well-being. Chapters 2, 3, 4 and 5 look specifically at the role of income on well-being; whilst Chapters 6 and 7 focus on the effect of employment status.

This thesis draws heavily on psychological concepts and ideas; highlighting that an

interdisciplinary approach to subjective well-being data can have substantial benefits to the study of well-being.

Chapter 2 seeks to understand how people compare their incomes with one another.

Relative judgment models from psychology are explored and the evidence suggests that

individuals may be concerned with their rank position rather than their absolute position or how they compare relative to a mean level. Applying this idea to relative income studies it is shown that an individual’s rank income provides a better explanation of life satisfaction than either absolute income or their income relative to the mean income of those around them.

Chapter 3 highlights that although more money may reduce psychological distress it is a relatively inefficient way to do so. This chapter provides medical evidence to suggest that psychological therapy is a more efficient way to reduce psychological distress. Income growth does not appear to increase national well-being in developed countries so this chapter suggests that increasing access to mental health care could be a better way to raise national well-being.

Personality, although appropriately controlled for, is mostly ignored by economists researching subjective well-being data. Chapters 4, 5 and 6 therefore explore the use of personality measures in economic subjective well-being research. Chapter 4 proposes a new methodological technique that incorporates personality measures. Chapters 5 and 6 then show that personality interacts with important economic variables. These chapters show that

personality is an important aspect to be understood by economists.

Chapter 7 demonstrates the importance of using longitudinal data to understand causal effects on well-being. Improvements to occupational status have been argued to lead directly to improvements to health. This argument has been based solely on the cross-sectional association that individuals with high occupational status tend to have better health. Chapter 7 shows that improvements to occupational status actually tend to increase mental strain.

Taken altogether these studies suggest that subjective well-being data provides a useful arena in which interdisciplinary research can be conducted.

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1 SUBJECTIVE WELL-BEING RESEARCH:AN OVERVIEW

This thesis takes a cross disciplinary approach to understanding human happiness. How can we improve our lives? How can we be healthier, happier and more satisfied? Such questions seem fundamental to the human condition and have been continually discussed and debated throughout human history. Ancient Greek philosophers, for example, considered eudaimonia – directly translated as “happiness”, but a more accurate meaning would be “human flourishing” – to be the most important of human goals. In the United States’ Declaration of Independence of 1776, the pursuit of happiness, alongside life and liberty, is touted as one of the unalienable rights of its citizens. In the present day some researchers have suggested that well-being indices should be favoured over commonly used economic indices like Gross National Product (Diener, 2000; Easterlin, 1974; Kahneman, Krueger, Schkade, Schwarz, & Stone, 2004; Marks & Shah, 2005). Although the importance of and concern for happiness within an individual’s life is unquestionable, what do we really know about what makes an individual happy?

When compiling research in the 1960s on the characteristics of the happy individual, Wilson (1967) remarked that their had been relatively few advances in the theory of the happy life since the ancient Greeks. Whether this statement was an accurate reflection of the times or not, the research into what makes an individual happy has since thrived. Researchers now routinely use self reported measures of well-being to understand human happiness. Such subjective well-being research, however, includes more than just the study of the transitory emotion of happiness. The term reflects both the cognitive and affective evaluations an individual has about their existence, including aspects of an individual’s physical and mental health. Such evaluations have been shown to be distinctly separate (Lucas, Diener, & Suh, 1996),

having their own set of correlates, which can be usefully analysed. The use of subjective well- being data, therefore, allows researchers to empirically test many of their well-being hypotheses.

It would perhaps be fair to now say that there have been considerable advances in the study of human well-being since the ancient Greeks (Diener, Suh, Lucas, & Smith, 1999).

This thesis attempts to add to our knowledge of what improves human well-being. To do this the thesis focuses entirely on an individual’s economic circumstances, for example their income and employment status. Specifically this thesis considers the importance of income rank for individual well-being, suggests an alternative way of increasing the well-being of our nations besides economic growth, shows that personality measures can help us understand how economic circumstances impact on well-being, and questions whether improvements to occupational status will bring health benefits. The topics covered in this thesis, although wide-ranging, share one common theme: They all draw heavily on concepts and ideas from psychology to answer important economic questions.

1.1 The Development of Subjective Well-Being Research in Economics and Psychology Subjective well-being research forms part of what is often referred to as the positive psychology movement (Seligman & Csikszentmihalyi, 2000). Positive psychology is a focus on the positive elements of the human experience. The movement is concerned with human

flourishing and akin to the Greek’s intended meaning of the word eudaimonia. More simply the movement attempts to understand how individuals can live their lives in more fulfilling and satisfying ways. This concern for understanding the positive aspects of the human experience arose in reaction to a discipline that, post-World War 2, had largely become pre-occupied with the negative. Psychologists had a relatively good understanding of mental illness and its treatment, but could offer very little in the way of help to individuals who, although not

necessarily mentally ill, could neither be defined as mentally healthy. Although early humanistic psychologists, such as Maslow (1954) and Rogers (1959), saw mental health as a continuum and developed theories on how to improve individual functioning and mental health, it is only in recent years that psychology has fully embraced the study of the positive. Subjective well-being research forms an important part of this study of the positive, seeking to understand how

individuals can shine during relatively benign conditions (Seligman & Csikszentmihalyi, 2000).

There has been a great deal of progress in subjective well-being research in recent decades, as the extensive reviews carried out by Wilson (1967), Diener (1984) and Diener et al.

(1999) show. Initially the concern was with determining the individual characteristics that were most strongly correlated with high well-being. Wilson (1967) found – using only bivariate associations – that happy individuals tended to be young, healthy, well-educated, well-paid, extroverted, optimistic, worry-free, religious, married with high self esteem, have high job

morale and modest aspirations. Many of these early conclusions, however, which focused heavily on demographic factors, have since been overturned and psychologists have increasingly focused on psychological factors, such as personality, adaptation, goal striving and coping strategies.

More up to date evidence suggests that individuals with high subjective well-being are those that have a positive temperament, do not ruminate excessively over bad events, live in economically developed societies, have strong social relationships and possess adequate resources to progress towards their goals (Diener et al., 1999).

1.1.1 The Use of Subjective Well-Being Data as a Proxy for Utility

Psychologists have naturally dominated the development of subjective well-being research but in the last decade or so economists have begun to show considerable interest in the area. Economists have recognised that subjective well-being research has the potential to unlock

answers to questions that have previously been thought of as unanswerable by acting as a proxy for an individual’s utility. The concept of utility – the satisfaction derived from consuming goods – permeates modern economic thought. Essentially all economic behaviour is assumed to reflect an attempt to increase one’s utility and therefore any observation of an individual’s behaviour should reveal something about their preferences. This revealed preference approach, pioneered by economists such as Samuleson (1938), is central to modern economic thought and has been for most of the twentieth century. If an individual chooses one bundle of goods over another then theory states that it is simply because it is preferred and therefore must yield more utility.

Although an individual’s decision is based on the principle of utility maximisation this does not necessarily mean the maximum utility will actually be realised. For this to realistically occur, individuals would need to be perfectly rational, have perfect recall and foresight, and have access to all information.

Researchers have pointed out that there is often a wide gap between an individual’s

“decision utility” and their “experienced utility”, and that as a result individuals may conceivably make sub-optimal choices (Kahneman, Fredrickson, Schreiber, & Redelmeier, 1993; Kahneman, Wakker, & Sarin, 1997). It has now been well documented, mostly by psychologists, that

individuals exhibit many cognitive biases and consistently make bad, or seemingly illogical, economic decisions. For instance, it is well known that individuals favour the avoidance of losses over the acquisition of gains and that they subjectively weight probabilities non-linearly

(Kahneman & Tversky, 1979). There are strong endowment effects, whereby individuals tend to place higher values on the objects that they own than ones they do not (Kahneman, Knetsch, &

Thaler, 1990; Thaler, 1980), and an economic decision can be heavily dependent on the way it is framed (Tversky & Kahneman, 1981). Some researchers argue that individuals have neither the

access to all the necessary information nor the time to make truly optimal decisions and therefore rely mainly on heuristics – short cut answers (Gigerenzer & Selton, 2001; Gigerenzer & Todd, 1999).

Nevertheless, in order to understand an individual’s preferences and what brings the greatest utility, economists have generally analysed an individual’s economic decisions.

However, utility, as it was originally conceptualised, was more akin to “experienced utility”. The concept of utility was initially developed by utilitarianists, such as Bentham (1748-1832) and Mill (1806-1873), who suggested using the term utility to represent the tendency for an object or action to increase or decrease overall happiness (Read, 2007). Their proposition was that

individuals ought to desire the things that brought them the most utility. They suggested that, in theory at least, it would be possible to obtain the total utility of some action by summing up the total amount of pleasure that an action brought to an individual. They further argued for the maximisation of social utility and that the morally right action was the one that produced the greatest amount of pleasure for the greatest number of people. Although their theory of utility suggested that individuals desired the greatest amount of utility, at no point did their formulation imply that individuals would necessarily choose the option that would yield the most utility.

The inability to measure utility served as a major limitation to the utilitarianists’ idea of utility. Utility as it was originally conceptualised fell afoul of economists, such as Vilfredo Pareto (1848-1923) and Lionel Robbins (1898-1984) (Vaggi & Groenewegen, 2003), and as discussed in Read (2007), the original conception of utility was eventually abandoned.

Economists soon came to favour the observation of an individual’s behaviour and decisions. At the time economists had not figured out a way to measure utility, and hence actual experienced utility was unobservable. The argument was that behaviour was observable and that decision

utility would in any case make a good approximation to experienced utility. The revealed preference approach, which assumed that rational individuals chose the option according to a stable set of preferences, soon became dominant. In this model utility became of no intrinsic relation to happiness and could not be compared or aggregated across, or even within,

individuals. Utility simply became an abstraction that could be used to state that if an individual had chosen x over y then x must necessarily have a higher utility than y. However, with the rise in subjective well-being research the measurement of utility in the way utilitarianists originally suggested finally seemed a possibility.

1.1.2 Subjective Well-Being – A Viable Tool for Economic Analysis

The use of subjective well-being data rests on the assumption that such data are a suitable proxy for an individual’s utility. Researchers at Leyden University, such as Van Praag (1971) and Kapteyn (1994), were the first to suggest the use of subjective data to measure welfare in economics. The Leyden approach, as it became known, initially focused solely on economic welfare and set out to determine what individuals considered to be, for example, very bad, bad, sufficient, good or very good incomes. The values assigned were found to vary considerably across individuals and were dependent on a number of economic and non-economic factors (Van Praag & Frijiters, 1999). An interest in economic welfare soon developed into a concern for general welfare and well-being. At the time the Leyden approach was particuarly novel and as such came against substantial criticism from economists who generally consider utility as immeasurable (e.g. Seidl, 1994).

Even in the present day economists are unconvinced of the use of subjective data to answer economic questions or inform policy. For example, Johns and Ormerod (2007) comment that national well-being levels, although they may not have risen in line with GNP, have also not

appeared to have risen in line with other aspects that one would firmly expect to contribute to well-being, such as rising longevity, greater gender equality, and improved democratic

institutions. They take this as evidence that subjective well-being data is an insensitive measure of welfare. Will Wilkinson (2007) argues that current well-being measures, due to very simple and sometimes inconsistent questioning, are blunt instruments that cannot be realistically interpreted or aggregated across individuals. Researchers have also warned of increased paternalism (Johns & Ormerod, 2007; W. Wilkinson, 2007), believing that the individual is always in the best position to make decisions that will promote their own well-being. However, many of the findings from the use of subjective well-being data suggest that free-market models might not always be the best way of promoting overall happiness (Layard, 2006a). In economics subjective well-being research is still relatively young and many of the findings challenge economic thought of the last 200 years. Although some scepticism within economics is only natural the current findings are somewhat compelling and need considerable reflection.

There is much less scepticism in psychology where subjective well-being data has been in use for much longer. Psychologists have spent considerable time ensuring that the self-reported measures they use have both reliability and validity. That is, measures of well-being yield consistent results across repeated tests and they truly represent the intended underlying construct (Fordyce, 1988; Lepper, 1998; Lucas et al., 1996; Pavot & Diener, 1993a; Sandvik, Diener, &

Seidlitz, 1993). Further, there is strong evidence that self reported measures predict observable behaviour. For instance, self report measures have been shown to be related to how often an individual genuinely smiles – the Duchenne smile (Ekman, Friesen, & Davidson, 1990), the length of an individual’s life (Palmore, 1969) and coronary heart disease (Sales & House, 1971).

Individuals that report themselves to be satisfied with life are much less likely to commit suicide

(Koivumaa-Honkanen et al., 2001) and positive well-being has been shown to directly relate to health-relevant biological processes. It has additionally been shown that happy countries have less hypertension (Blanchflower & Oswald, 2008).

Ultimately subjective responses from individuals about how happy or satisfied they are with their lives cannot simply be ignored. Self report measures are of course far from perfect. For example, there is still some concern over whether scores can be treated as cardinal or ordinal (Ferrer-i-Carbonell & Frijters, 2004) and, due to it being unlikely that scores will be comparable across individuals, self report measures cannot yet be aggregated across individuals in the way originally suggested by utilitarianists (Read, 2007). Nevertheless, the use of subjective well- being data to proxy for utility has helped researchers understand the contribution that economic circumstances have to an individual’s well-being. Economic subjective well-being research, or

“happiness economics”, as it has popularly and perhaps misleadingly become known, is a rapidly growing area of research. The use of subjective well-being data in economics is seen by some economists as a large step forward and its use is gradually, and rightfully, being acknowledged as a useful counterpart to the revealed preference approach (Frey and Stutzer, 2002).

1.2 Overview of Key Research Areas

Subjective well-being is currently researched by economists and psychologists with equal rigour. In spite of this there are often huge gaps in the way that economists and psychologists approach the topic. In part, this arises due to fundamentally different research questions.

Additionally, however, subjective well-being researchers are not always aware of the progress made outside of their immediate field. Much of the work in this thesis centres on the

relationships between income and well-being and an individual’s employment status and well- being. These relationships have received extensive cross-disciplinary coverage, as the next

section demonstrates, but there are key differences across the disciplines and therefore important gaps. This thesis attempts to highlight this disciplinary divide and show how these gaps could be bridged to benefit both disciplines and ultimately our understanding of human happiness.

1.2.1 Income and Well-Being

The importance of income for well-being is an area in which there has been a healthy amount of interest from both psychologists and economists. This section first discusses the evidence for a relationship between income and well-being. It then discusses possible explanations and offers ways in which these explanations can be explored and refined.

1.2.1.1 Evidence of a Relationship between Income and Well-Being

There are several ways in which to determine whether income is positively related to well-being – researchers can identify the correlation between income and well-being either; over time, within a country or across countries. The evidence for each is discussed below.

1.2.1.1.1 Income and Well-Being over Time

One of the earliest and most influential studies on income and well-being came from the economist, Richard Easterlin in 1974. Many years ahead of the explosion of subjective well- being research in economics, Easterlin (1974) questioned whether economic growth had improved the human lot. Instead of using productivity data or standard of living indexes that would give an objective answer to his question, Easterlin used the proportion of randomly sampled individuals that stated they were “very happy” with their lives. He was able to

demonstrate using this subjective data that, in developed countries at least, economic growth had not seemed to improve the human lot. It appeared that once countries achieved a certain level of economic development, further development was associated with very little increases in average

national well-being. Although there are some that are sceptical of this finding (C. S. Fischer, 2008; Hagerty & Veenhoven, 2003; Stevenson & Wolfers, 2008) it has been replicated on numerous occasions, by both economists and psychologists (Blanchflower & Oswald, 2004;

Diener & Oishi, 2000; Easterlin, 1995; Kenny, 1999). Such a finding could invite one to question why economic growth remains a priority in developed countries.

1.2.1.1.2 Income and Well-Being within a Country

But does money buy happiness at the individual level? If we only observed people’s behaviour then our conclusions would be that it surely must. Utility maximising individuals choose to spend money on goods and services; implying that money, by allowing them to increase the goods and services that they can buy, ought to bring them more utility. Early research into the relationship between income and well-being within a country was mostly carried out by psychologists (Diener, 1984; Diener & Biswas-Diener, 2002; Haring, Stock, &

Okun, 1984; Myers & Diener, 1995; W. Wilson, 1967) and it has consistently been found that within a country individuals with higher incomes tended to also have higher well-being.

Economists have further shown using longitudinal data that this relationship may be truly causal (Frijters, Haisken-DeNew, & Shields, 2004; Gardner & Oswald, 2007).

1.2.1.1.3 Income and Well-Being across Countries

Easterlin (1974) also asked whether richer countries were happier countries. The evidence he presented suggested that richer countries were not happier. However, there were a number of issues with his original research as pointed out in Veenhoven and Hagerty (2003). Easterlin has since updated his work (Easterlin, 1995) and, as has been replicated on numerous occasions, there is in fact a positive relationship between a countries income and their well-being (e.g.

Diener, Sandvik, Seidlitz, & Diener, 1993; Hagerty & Veenhoven, 2003). However, this positive relationship appears to be concave and beyond $10,000, the average income level appears to have very little effect on average well-being (Frey & Stutzer, 2002). The relationship between income and well-being across countries is not entirely reliable. Not only are there cultural limitations to making subjective well-being comparisons across countries but further it is likely that there are other factors that accompany high income per capita, such as democracy (Inglehart, Foa, Peterson, & Welzel, 2008), health or basic human rights (Frey & Stutzer, 2002), that may have resulted in the higher happiness levels.

1.2.1.2 Explaining the Income and Well-Being Data – Relative Income Effects The combination of a correlation between income and well-being within a country and the fact that economic growth does not appear to increase national well-being leaves something of a puzzle to economists researching subjective well-being (Clark, Frijters, & Shields, 2008).

How can increases to income seemingly improve an individual’s utility but not total societal utility? These two findings are commonly referred to as the Easterlin paradox and form the cornerstone of much economic research into well-being. One of the most popular explanations for the Easterlin paradox is that individuals are not concerned with absolute income but with income relative to their peers. Income will improve an individual’s well-being but only if it rises at a faster rate than the income of others. Hence, if everyone’s income increased by the same amount then no one would actually be any better off because relative positions remain unchanged.

1.2.1.2.1 Relative Income Effects in Economics

There has been some debate since using simple cross-sectional data by psychologists over whether the effect of income is relative or absolute (Diener et al., 1993; Hagerty & Veenhoven, 2003; Veenhoven, 1991). Such evidence, however, is based solely on cross-sectional

observations and can only be taken as circumstantial. Simple correlations are not enough to conclusively show that individuals care about relative income. Rather than relying on such circumstantial evidence economists have attempted to show that an individual’s relative income is an important predictor of well-being. For example, relative income variables have been shown to significantly predict various measures of well-being (Clark & Oswald, 1996; McBride, 2001).

Additionally economists have also shown that there is causal link – with increases to an individual’s relative income leading to increases in well-being (e.g. Ferrer-i-Carbonell, 2005;

Luttmer, 2005; Senik, 2004). It now seems fairly clear that individual’s care about their income compared to those around them and will feel less satisfied in the presence of higher earning others.

The presence of relative income effects should come as no surprise to economists. The importance of relative concerns and social comparisons has received discussion throughout the history of economics and can be traced back to the works of Adam Smith (1976) and Karl Marx (1952). Veblen (1899) coined the phrase “conspicuous consumption” to refer to a type of consumption that, although not necessary to our survival, signalled to everyone else something about one’s standing or status in the community. Duesenberry (1949) discussed relative

concerns with respect to savings. He suggested that in order to maintain self esteem individuals were likely to sacrifice their savings to consume goods that other people have. This “keeping up with the Joneses” effect, or “luxury fever” as Frank (1999) terms it, may mean that collectively

individuals may be working too hard and buying things that they don’t really need. However, it has always been difficult to determine whether behaviour is motivated by relative, rather than absolute, effects. Neumark and Postlewaite (1998) demonstrate that the rise in women entering the workforce can, in part, be explained by relative concerns by comparing the employment decisions of sisters and sister-in-laws. However, as Luttmer (2005) points out, to really differentiate between relative and absolute income effects a proxy for utility in the form of subjective well-being data is essential. It is important that the concern for relative performance is appropriately included in an individual’s utility function (Clark & Oswald, 1998).

1.2.1.2.2 Relative Judgment Models in Psychology

Psychologists have carried out extensive research to suggest that individual’s make relative judgments and have therefore been ready to accept that an individual’s utility is influenced by relative income. They have, for example, demonstrated under experimental conditions that judgments are often based on some type of relative concern (Helson, 1964;

Parducci, 1965; Stewart, Brown, & Chater, 2005). Helson (1964) proposed Adaptation Level Theory (ALT) to model how individuals subjectively assessed an objective stimulus within the context of a set of other stimuli. For example, a typical experiment scenario might require an individual to assess how subjectively heavy a weight feels in comparison to other weights, where 1 = “very light” and 10 = “very heavy”. The model is simple and proposes that an assessment is made by intuitively making a comparison with a weighted mean of the background stimuli; in the example above, an average weight in the context of the other weights might be given a 5 or a 6.

If the set of stimuli and mean were to increase so should the comparison level to which an

assessment would be made to. The previously average weight would perhaps now be given a 3 or 4. ALT predicts that the individual’s evaluation of a given stimulus will therefore adapt to the

context of comparison. This approach is very similar to that of economists researching relative income effects. It is assumed that individuals compare with the average level of income of those around them.

However within psychology the data better support an alternative model of how

individuals make subjective assessments: Range-Frequency Theory (RFT) (e.g. Parducci, 1965, 1995). RFT suggests that an assessment is given by a weighting of the stimulus’ rank (frequency) and cardinal position relative to the highest and lowest values (range) within the set of stimuli.

One issue with ALT is that two differently distributed sets of stimuli can have identical means.

The distribution is not considered. An assessment under RFT, however, is modelled on a uniformly distributed rank but anchored by distribution extremes. RFT has been useful in

modelling subjective assessments in an array of stimuli but importantly for economics it has been found to help model assessments of both prices (Niedrich, Sharma, & Wedell, 2001; Qian &

Brown, 2007) and incomes (Brown, Gardner, Oswald, & Qian, 2008; Mellers, 1986). RFT has also been shown to be applicable to social comparisons (R. H. Smith, Diener, & Wedell, 1989).

Outside of experimental conditions the range and skew of an income distribution, as predicted by RFT, affect the average happiness level across communities (Hagerty, 2000).

1.2.1.2.3 Rank Income Effects

The evidence from psychology suggests that the relative income models used in economics can be improved and provides the motivation for Chapter 2. This chapter uses

subjective well-being data to explore two relative income models – the reference income model, where individuals compare to the average income of those around them, and a rank income model, which suggests that it is the rank of their income within the comparison set that is important. The reference income model is dominant within economists’ relative income studies

so we test which model has the greatest explanation of life satisfaction. Our evidence, consistent with RFT, favours the rank income hypothesis. We also further consider that comparison is mostly made with those that are better than oneself. There is already some evidence of upward comparisons using the reference income approach (Blanchflower & Oswald, 2004; Ferrer-i- Carbonell, 2005). However, we investigate upward comparison using the rank income framework and we show that individuals compare up to twice as much with those above than those below.

1.2.1.3 Explaining the Income and Well-Being Data – Income is relatively Unimportant for Well-Being

A further, and perhaps less popular explanation, is that more income might simply not be very important for either national or individual wellbeing. The perceived importance of income for well-being depends heavily on how we choose to interpret statistical associations. Generally economists and psychologists interpret the effects of income on well-being very differently. A recent review, for example, puts the correlation between individual income and well-being within countries at between 0.17 and 0.21 (Lucas & Dyrenforth, 2006). The correlation between income and well-being varies considerably across countries and can often be much larger in developing countries (Howell & Howell, 2008). However, the correlation can also be much smaller, for example, Diener, Sandvik, Seidlitz & Diener (1993) obtained a correlation of 0.12 in the United States. Income and well-being correlations are nearly always strongly significant, owing to the large sample sizes, but correlations of this size might typically be referred to by psychologists as small (Cohen, 1992). These correlations suggest that, at best, income explains 4% of an

individual’s well-being. A psychologist might therefore argue that this small correlation makes

income and well-being largely of little interest, particularly when other factors, such as personality, seem to explain much more of an individual’s well-being.

Economists, on the other hand, do not use correlations to view the effect of income on well-being. Simple correlation coefficients are much more useful for interpreting the non- meaningful scales commonly used within psychology. Income is an objective characteristic that can be meaningfully interpreted, enabling economists to make statements, such as, “£10,000 is associated with a well-being rise of X” or “the well-being increase from some life event is equivalent to having an income rise of X” (e.g. Blanchflower & Oswald, 2004; Di Tella, MacCulloch, & Oswald, 2003; Ferrer-i-Carbonell, 2005). Some researchers have therefore argued that simple correlation coefficients applied to income and well-being studies can actually be misleading. Lucas and Schimmack (2009), in an attempt to convince psychologists sceptical of income effects on well-being, demonstrate that small correlations can be translated into large mean life satisfaction differences between the rich and the poor. For example, they show that the life satisfaction for those earning over $200,000 a year is between 0.79 and 0.88 standard

deviations higher than those earning less than $10,000. This observation could lead one, in spite of the low correlation in their data set of between 0.17 and 0.20, to conclude that income is in fact important for well-being.

However, the figures provided by Lucas and Schimmack (2009) must be interpreted with some caution. Firstly, correlation does not imply causality. Their analysis is based on simple bivariate associations and the association between income and well-being is mostly driven by third variables, such as an individual’s personality (see section 1.2.1.4). Secondly, one must take into consideration the likelihood of an individual’s income increasing from below $10,000 to

$200,000. Unfortunately Lucas and Schimmack (2009) do not present the standard deviation of

household income but it is likely to be around $30,000. This suggests that to go from $10,000 to

$200,000 would require something like a six standard deviation increase in income. When we consider that six standard deviations (3 standard deviations either side of the mean) should contain around 99.7% of the observations in a normally distributed sample, we begin to see how unrealistic a change in income of such a magnitude is likely to be. The correlation coefficient is designed to describe the relationship between two variables in a standardised way. The

correlation coefficient reflects how much one variable will move as a result of a one standard deviation change in the other. Hence, an alternative, and perhaps fairer interpretation, of Lucas and Schimmack (2009) is that an individual who had an income one standard deviation higher (around $30,000) than another individual would be approximately 0.17 to 0.2 standard deviations higher in life satisfaction. If causal effects were considered then typically the association between income and well-being shrinks by about a third (Ferrer-i-Carbonell & Frijters, 2004), suggesting

$30,000 would increase well-being by less than 0.1 standard deviations.

It is the intention of chapter 3 to illustrate how low the correlation between income and well-being actually is relatively to other aspects of life. To do this, we bring together disjoint areas of research from economics, psychology, law and medicine. This chapter centres its

discussion on the law courts and focuses on the use of monetary compensation as a means to help individuals deal with traumatic life events. In recent work Oswald and Powdthavee (2008a, 2008b) use subjective well-being equations to suggest that current recommended compensation payouts are too low. They suggest that to truly compensate someone financially then payouts would actually need to be much higher. We argue that, although this would be a correct interpretation of subjective well-being equations, the high values suggested actually reflect money’s inefficiency at alleviating psychological distress. We make an alternative suggestion –

the use of psychological therapy. We then go on to illustrate, using medical evidence of psychological therapy’s cost-effectiveness, that psychological therapy could be over 30 times more cost effective than money at alleviating psychological distress.

We use this evidence to question the pursuit of income growth as a means to increase well-being in developed countries (Blanchflower & Oswald, 2004; Diener & Oishi, 2000;

Easterlin, 1995; Kenny, 1999). If money is relatively unimportant to well-being then developed societies might be better off pursuing objectives that are more likely to increase national well- being. Mental illness appears to be rising worldwide (Michaud, Murray, & Bloom, 2001) and we suggest that there needs to be a greater focus on mental health and improved access to mental health care, such as psychological therapy. In Chapter 3 we argue that good mental health is undervalued in our societies and that as a result there could be enormous benefit if resources were channelled into mental health care rather than solely focusing on economic growth.

1.2.1.4 Explaining the Income and Well-Being Data – Personality

A further explanation of the data, which shows that national income growth does not lead to increases in well-being and that there is only a small correlation between an individual’s income and their well-being, is that there is a third variable that causes both high income and high well-being. For example, it is likely that aspects of an individual’s personality may drive them to earn a higher income yet also mean they have higher levels of well-being over the course of their life. Psychologists have shown that an individual’s well-being can mostly be explained by either personality or genetic factors. For example, Lykken and Tellegen (1996) show that between 44% and 52% of well-being is the result of individual differences. Once personality is controlled for the effect of income on well-being decreases by up to a third (Ferrer-i-Carbonell &

Frijters, 2004). It has further been argued that demographic factors contribute substantially less to

well-being compared to other factors such as personality (Argyle, 1999). Psychologists have, therefore, begun to focus less on demographic factors and are instead interested in understanding the types of personality and the psychological processes that accompany high well-being (Diener et al., 1999).

One theory of well-being that seeks to understand the role of personality and the psychological processes is the set-point theory of subjective well-being. This is the idea that individuals receive short term fluctuations in their well-being due to changes in their life circumstances, but that given time, they revert back to a baseline level of well-being that is dependent on an individual’s personality (Headey & Wearing, 1989). Lykken and Tellegen (1996) estimate the stable component of well-being to be around 80%. Adaptation to traumatic life events represents a practical application of set-point theory. An early demonstration of adaptation came from Brickman, Coates and Janof-Bulman (1978), who seemed to show that lottery winners were not significantly happier than a control group and that individuals with spinal-cord injuries were not as unhappy as one might expect. However, these early results have often been criticised (Lucas, 2007; Oswald & Powdthavee, 2008b) - not only are the results based on cross-sectional differences using tiny samples of individuals, but the results have often been misinterpreted to support complete adaptation.

Frederick and Loewenstein (1999) provide an in-depth discussion of adaptation and suggest that whilst considerable adaptation seems to take place in some domains (e.g.

imprisonment, disability and income), it does not appear to in others (e.g. noise, cosmetic surgery and food). Recent longitudinal evidence suggests that, although it can take a while, individuals partially adapt to the loss of a loved one (Oswald & Powdthavee, 2008a). Researchers have also observed that individuals appear to fully adapt to marriage, divorce, widowhood and the birth of

child (Clark, Diener, Georgellis, & Lucas, 2008) but not necessarily to unemployment (Clark, Diener et al., 2008; Lucas, Clark, Georgellis, & Diener, 2004). The process of adaptation offers an explanation as to why income growth may not provide as much of an increase to individual and national well-being as one might expect. After the initial benefit of an income increase wears off individuals drift back to a fixed long term level of well-being. Individuals get use to their new wealthier environment (Easterlin, 2001, 2005). Much of the well-being work in psychology attempts to understand what determines this important long term level of well-being.

1.2.1.4.1 Controlling for Personality in Economics

Economists would generally agree that personality explains a substantial component of individual well-being (Ferrer-i-Carbonell & Frijters, 2004). However, in economics personality is only of limited interest. Economists are much more interested in areas of life that can be changed and influenced by policy, hence personality, due to its apparent non-changing nature (Costa &

McCrae, 1980, 1988), seems of little direct intrinsic interest. Economists are very aware of the need to control for non-changing characteristics when trying to establish causal effects on well- being. Their main concern is, therefore, with how to control for personality simply and

effectively. Although economists have brought advanced statistical techniques to subjective well- being research to indirectly control for personality this seems to have precluded an awareness of the huge literature on the development of personality measures. Psychologists routinely use personality measures that have impressive levels of validity and reliability in subjective well- being studies and such measures could prove useful for economic research generally (Borghans, Duckworth, Heckman, & ter Weel, 2008).

This thesis devotes several of its chapters to trying to illustrate that personality measures could be hugely beneficial to economic research into subjective well-being. In turn the thesis also

attempts to demonstrate to psychologists that an understanding of demographic influences on well-being can also be improved with the aid of personality (Gutierrez, Jimenez, Hernandez, &

Puente, 2005). Our work mainly relies on the German Socio-Economic Panel, which is a large data set primarily used by and developed for economists. In a recent wave a number of

personality questions were included. Since psychologists do not routinely use these types of large data sets it is therefore rare to find measures like personality included in them.

In Chapter 4 these personality measures are used to suggest an alternative to the dominant statistical technique used by economists in subjective well-being research. Typically economists use what is often referred to as a fixed effect model to control for unobservable personality characteristics. Essentially the fixed effect model focuses on explaining the within-person variation and controls for the aspects of an individual’s well-being that could be considered fixed. This fixed component of well-being is similar to the long term level of well-being that was addressed earlier and discussed in Lykken & Tellegen (1996). Chapter 4 first tries to determine how much of the fixed effect can be explained by personality. The chapter then goes on to suggest an alternative statistical technique to the standard fixed effect model that exploits

personality measures and then argues that the alternative technique produces more reliable casual estimates on individual well-being for characteristics such as marital status, disability and

income.

1.2.1.4.2 Personality Interacts with Demographic Characteristics

Chapters 5 and 6 extend the argument for using personality measures in economic research. These two chapters demonstrate that personality interacts with variables that economists are typically more interested in, suggesting that personality cannot be simply indirectly controlled for and largely ignored in the way that it has up to now.

Although part of this thesis demonstrates that income is relatively unimportant for well- being this does not mean the topic is of little interest. Economists will always naturally be more interested in the effects of income on well-being simply because income is central to the

discipline. However, there are two further reasons that should make research into income and well-being of interest to researchers across all disciplines. Firstly, income, unlike personality, can be actively changed through policy and secondly, some understanding is needed as to why

income does not bring as much improvement to well-being as one might expect. Although the data seem to suggest that income is relatively unimportant there remains a belief within our societies that more money will bring substantially greater well-being. Individuals desire higher incomes and the use of financial incentives, either through the tax system or through pay bonuses, to change behaviour is endemic in many developed societies. This sets up the motivation for Chapter 5. Most income and well-being studies only focus on average effects across a large sample. We present evidence that the marginal utility of income varies greatly according to an individual’s personality and suggest that policy could benefit from being personality specific.

There has been some call for understanding the interaction between personality traits and external circumstances (Diener et al., 1999) and the work in Chapter 5 answers this call. Chapter 6 offers a further demonstration of when personality can be important for the experience of a life event. Chapter 6 explores the role of conscientiousness when becoming unemployed. The topic of Chapter 6, however, will be discussed in relation to the employment status and well-being literature, which is outlined in the next section.

1.2.2 Employment Status and Well-Being

Another area in which there has been a great deal of cross-disciplinary research with respect to well-being concerns individuals’ employment status. In the standard economic utility function work typically enters negatively, but there is substantial evidence to suggest that work has many benefits for an individual’s well-being that goes beyond the simple acquisition of income (Myers & Diener, 1995). The remainder of the thesis addresses two separate areas: the psychological consequences from unemployment and understanding the positive association between occupational status and physical and mental health. Researchers across the disciplines have approached these areas in fairly similar ways. The largest difference appears to be mainly methodological.

1.2.2.1 Unemployment

Typically individuals suffer deep psychological consequences from unemployment (McKee-Ryan, Song, Wanberg, & Kinicki, 2005) and this goes beyond the simple loss of income. Psychologists have generally been much more interested in the topic of unemployment since, unlike income, it seems to have a substantial impact on an individual’s well-being. For example, in their meta-analysis McKee-Ryan et al. (2005) review over one hundred, mainly psychological, studies, and observe that there is a mental health difference between employed and unemployed of 0.57 standard deviations. Although longitudinal studies are less common they further observe that mental health drops on average by 0.38 standard deviations when an

individual becomes unemployed. Economists, although beginning their research much later, have generally approached the topic of unemployment in a similar way (Frey & Stutzer, 2002).

However, economists have brought the use of large scale longitudinal data sets to subjective well-being research and with the help of their advanced econometric techniques (see for example

work by Clark, Diener et al. (2008), Clark et al. (2001) and Winkelmann & Winkelmann (1998)), they have advanced the understanding of the causal effects of unemployment on well-being.

One issue identified in unemployment studies, as with that of income studies, is that estimates are generally based on the average effect across a sample. Researchers have established specific circumstances under which unemployment is at its most psychologically damaging. For example, the local unemployment rate (Clark, 2003; Powdthavee, 2007; Russell, 1987; Turner, 1995), the length of unemployment (Clark et al., 2001; Creed, Lehmann, & Hood, 2009;

Winefield & Tiggemann, 1989) and the degree of unemployment protection (Nordenmark, Strandh, & Layte, 2006) all moderate the effect that unemployment has on well-being. However, much less is known about which specific types of individuals suffer the most psychologically following unemployment. This provides the motivation for Chapter 6, which presents evidence that individuals with high levels of conscientiousness suffer the most during unemployment.

Typically conscientiousness has a positive relationship with well-being (DeNeve & Cooper, 1998; Hayes & Joseph, 2003) but our finding suggests that under certain circumstances this relationship can be completely reversed.

1.2.2.2 Occupational Status

Individuals with high occupational status tend to have much better mental and physical health (Marmot, Shipley, & Rose, 1984). The idea of status links in with the earlier discussion of the importance of rank. Epidemiologists have been trying to understand the reasons for this strong correlation and the theory that has dominated the literature is that there is a causal relationship going from status to health (Marmot, 2004; R. Wilkinson, 2001). The argument underlying their theory is convincing and suggests that individuals in low status positions have low control over their life. A low control in life results in psychosocial stressors and it is these

stressors that can be detrimental to human health. It therefore follows that any improvement to status will improve an individual’s level of control and psychosocial stressors will diminish. The result should be a direct improvement to an individual’s health. Most of the evidence for a causal link running from status to health, however, comes mainly from cross-sectional evidence.

The problem with relying solely on cross-sectional associations is that it is impossible to determine the direction of causality. A cross-sectional association could be the result of one variable causing a change in another or alternatively it could mean that the two variables move together as a result of a change in a third variable. This means that whilst higher occupational status may lead to health the cross-sectional association another explanation could be simply that healthy individuals get promoted. Alternatively it could be that some other factor, such as

behavioural or genetic factors, causes movements in both. Generally economists are less satisfied with simple cross-sectional associations and much of their subjective well-being research has focused on establishing causal effects. Economists are more aware of the availability of large longitudinal data sets that enable them to control for pre-existing levels of some variable.

Chapter 7 applies a longitudinal analysis to the question of whether occupational status improves an individual’s health. As far as we are aware this is the first longitudinal analysis of its kind. We illustrate that although individuals in high occupational positions have much better health than those in lower occupational positions, a promotion between these positions does not result in better health. We show that in some promotion categories mental strain may even increase.

1.3 Overview of the Thesis

This thesis, although primarily concerned with economic decisions and how they

contribute to well-being, takes a cross disciplinary approach to the study of subjective well-being

data. This thesis uses concepts and ideas from psychology to enhance economic research into subjective well-being. First, a rank income interpretation of well-being is presented (Chapter 2).

Second, the low importance of income for well-being is highlighted and it is further suggested that developed societies could gain substantial well-being benefits by investing in mental health care (Chapter 3). Third, the thesis demonstrates that personality measures can be of considerable use to economists researching subjective well-being by showing that they allow alternative statistical techniques to be used (Chapter 4) and that personality interacts with important economic variables (Chapters 5 and 6). Finally, the thesis demonstrates the importance of longitudinal data to draw causal conclusions by showing that, against common belief, improved job status does not bring health benefits (Chapter 7).

C

2

2 MONEY AND HAPPINESS:RANK OF INCOME, NOT INCOME,AFFECTS LIFE SATISFACTION

2.1 Abstract

Does money buy happiness, or does happiness come indirectly from the higher rank in society that money brings? Here we test a rank hypothesis, according to which people gain utility from the ranked position of their income within a comparison group. The rank hypothesis contrasts with traditional reference income hypotheses, which suggest utility from income depends on comparison to a social group reference norm. We find that the ranked position of an individual’s income predicts general life satisfaction, while absolute income and reference income have no effect. Furthermore, individuals weight upward comparisons more than downward comparisons.

According to the rank hypothesis, income and utility are not directly linked: Increasing an individual’s income will only increase their utility if ranked position also increases and will necessarily reduce the utility of others who will lose rank.

Previously published as: Boyce, C. J., Brown, G. D. A., Moore, S.C. (in press). Money and Happiness: Rank of Income, not Income, Affects Life Satisfaction. Psychological Science

2.2 Introduction

Is there a true causal relation between money and happiness? According to conventional economics, there is: Money can buy happiness because it can be exchanged for goods that will increase an individual’s utility. Thus money and happiness are assumed to be causally linked, and higher incomes should lead to greater happiness. In line with this absolute income hypothesis richer people are happier than those less well off within the same society (Diener, 1984). The correlation between money and happiness is often small, but effect sizes are larger in low-income developing economies (Howell & Howell, 2008) and even small correlations can reflect

substantial real differences in happiness (Lucas & Schimmack, 2009). Such results, however, do not necessarily reflect a simple causal relation between money and happiness. The idea that absolute income leads to increased happiness is unable to account for the Easterlin paradox – that income and happiness are positively associated within a country at a given time, but not (or less well) correlated within a country over time (Easterlin, 1974).

Furthermore, being amongst people richer than oneself can be detrimental to wellbeing variously measured (Blanchflower & Oswald, 2004; Clark, Frijters et al., 2008; Clark & Oswald, 1996; Ferrer-i-Carbonell, 2005; Luttmer, 2005), consistent with income comparison. Self-rated happiness and satisfaction scores have been shown to act as valid and reliable proxies for utility (e.g. Lepper, 1998; Sandvik et al., 1993). The data have therefore been taken to suggest that an individual’s utility is influenced not by absolute level of income but instead by their income relative to that of their peers.

The reference income hypothesis is the dominant model of income comparison and suggests that individuals care about how their income compares to the norm, or reference income, of a socially constructed comparison group. Again, a direct causal link is assumed:

Increased income will lead to increased utility for an individual if all else is held constant.

Individuals gain utility to the extent that their income exceeds the average or reference income of people in their comparison set, and lose it to the extent that their own income falls below the reference level. The average income of an assumed reference group typically negatively and significantly predicts a number of variables related to well-being, consistent with the reference income approach (e.g. Clark & Oswald, 1996).

Here we suggest instead that utility is based on an individual’s ranked position within a comparison group – the rank income hypothesis. According to the rank-based model, people gain utility from occupying a higher ranked position within an income distribution rather than from either absolute income or their position relative to a reference wage (Brown et al., 2008; Clark, Kristensen, & Westergard-Nielsen, 2009a; Clark, Masclet, & Villeval, in press; Hagerty, 2000;

R. H. Smith et al., 1989). For example, people might care about whether they are the second most highly paid person, or the eighth most highly paid person, in their comparison set (which might contain fellow workers of a similar age and qualification level, neighbours, friends from college, etc). The ranked position of an income will be highly correlated with the position of that income relative to a mean, so evidence previously taken to support reference income accounts may be consistent with a rank income account. Not only do rank and reference based models predict very different savings and consumption behaviour (Bilancini & Boncinelli, 2007) but also, according to the rank income hypothesis, there is no simple causal relationship between money and happiness: An increase in income need not increase ranked position and hence need not increase happiness.

A rank based approach to judgment is independently motivated by the fact that judgments about items within a context of other items are known to be influenced by the ranked position of