Abstract
There is considerable evidence from a variety of sources to suggest that well-being is a function of relative income. These findings have been used to explain the Easterlin Paradox, whereby a rise in income for all does not lead to a rise in average happiness in a country (even though the cross section relationship between income and happiness is positive). This relativity of utility has led to calls for policy to focus away from GDP. I here first discuss some of the evidence that well-being is indeed relative in income, but then consider two relatively little-analysed issues to suggest that there may continue to be a role for GDP per capita in happiness-based policy: the inequality of subjective well-being, and the specific case of those in income poverty.
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Notes
In the European Social Survey data discussed in Clark and Senik (2010), the most commonly cited income reference group was work colleagues. In the analysis of American Life Panel data in Dahlin et al. (2014), income comparisons are more likely to be carried out regarding family and friends, work colleagues, and people of the same age, but are less likely with respect to geographical reference groups. The conclusions in Goerke and Pannenberg (2015) using three SOEP pre-test modules are similar: comparisons are more likely to be made to people in the same occupation, work colleagues and those of the same age; they are the least likely to be made to parents and neighbours.
It is also possible that different groups in society do not undertake the same types of comparisons. In the analysis of British and German data in Fitzroy et al. (2014), comparison income is positively correlated with subjective well-being for respondents under the age of 45 but negatively correlated for those aged over 45.
Satisfaction and income comparisons was the first topic that I worked on in subjective well-being. And it was almost the last. Andrew Oswald and I started thinking about this in the context of subjective well-being in late 1991 using data from the pilot of the first wave of the nascent BHPS. We had both been exposed to the idea of income comparisons earlier, through our work on trade-union bargaining where wage differentials between different occupational groups often appeared explicitly as a union goal. That our paper was not published until 1996 hints at the trouble we had: it was conclusively rejected by five top economics journals (with most of the referees not understanding why on earth, even if we were interested in the esoterica of income comparisons, we would also want to look for them in self-reported happiness data). Luckily for my career, times have changed, with self-reported data now being found in many areas of economic research, and subjective well-being and income comparisons have been addressed in a variety of contributions.
Life satisfaction did not appear in the BHPS until 1996.
Reference income here (the income that ‘people like me earn’) is predicted from a Mincer wage equation.
The comparison income here is the individual’s own past income. The corresponding well-being function, W it = W(y it , y it−1, …) implies habituation, so that individuals become used to higher income.
A similar signal effect is found in the Danish-linked employer–employee data in Clark et al. (2009). Satisfaction with work is shown to be positively correlated with earnings at the 75th percentile of the wage distribution within the establishment (for respondents who were in the first three quartiles of the establishment wage distribution).
A far more detailed discussion of these other approaches appears in Clark et al. (2008b).
Somewhat along the same lines, Perez-Truglia (2015) uses a natural experiment in Norway (the easy provision of information regarding others’ income) to argue that this greater income transparency produced a more positive relationship between income rank and both happiness and life satisfaction.
Striatal activity has been shown to predict both hedonic outcomes (subjective well-being) and physiological outcomes (cortisol output: the body’s response to stress).
Intriguing work by Sacks et al. (2013) suggests that the between-country and within-country estimated coefficients on log GDP per capita for some well-being measures are remarkably similar, which is consistent with there being no relative income effects at work at all within countries. See however Easterlin (2016) regarding the estimation of short run (business cycle) rather than long-run (trend) relationships between subjective well-being and income: it is the latter that interest us in terms of the Easterlin Paradox.
The type of work listed in Sect. 2 has established that W 2 < 0 in the well-being function W = W(y, \(y^{*}\), …). Regarding social interactions, we are also interested in the sign of W 12: does the marginal utility of my own income depend on reference-group income? If the cross-partial derivative is positive (W 12 > 0), then a rise in others’ income makes my own income more valuable. Such a set-up has been used to explain social interactions in hours of work: as others work more and earn more, my best reaction is to work more and earn more myself: but this leads others (who compare to me) to react by working more and earning more, and so on. See Clark and Oswald (1998) and Schor (1992).
Other work has not related satisfaction to the level of own and others’ income, but rather to individual income rank: this is another way of showing that own income compared to that of others is important for well-being. Boyce et al. (2010) analyse seven years of BHPS data, and show that life satisfaction is strongly positively correlated with income rank (within the same region-year, sex-education-year and age group-year cells), but not correlated with log income. Similarly Daly et al. (2015) find that income rank predicts a variety of health outcomes in BHPS and English Longitudinal Study of Aging (ELSA) data, while income level does not when both level and rank are introduced simultaneously into health equations. If only income rank matters, then there will be no relationship between satisfaction and a change in GDP per capita, as the amount of rank in a society is fixed by definition.
It may be that reference groups in France are different to those in other countries (see footnote 1), or that there is less precision in the measurement of regional income, leading to attenuation bias.
As 0.142 × ln 2 = 0.098.
The Household, Income and Labour Dynamics in Australia dataset.
This is the same method that was used to consider adaptation to unemployment, marriage, divorce, widowhood and children in SOEP data by Clark et al. (2008a).
The potentially complicated relationship between income distribution and subjective well-being in an economy is analysed in Clark and D'Ambrosio (2015).
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Acknowledgements
I am grateful to the Editor and an anonymous referee for useful suggestions. I thank Christopher Boyce, Conchita D’Ambrosio, Dick Easterlin and seminar participants at the AISSEC Workshop (Rome), the HEIRS Happiness Conference in Rome and Nanyang Technological University for help and useful comments. I am grateful for support from CEPREMAP, the US National Institute on Aging (Grant R01AG040640), the John Templeton Foundation and the What Works Centre for Wellbeing. Sarah Flèche kindly helped with the figures.
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