Abstract
The statistical analysis of cross-section data very often reveals a U-shaped relationship between subjective well-being and age. This paper uses 18 waves of British panel data to try to distinguish between two potential explanations of this shape: a pure life-cycle or aging effect, and a fixed cohort effect depending on year of birth. Panel analysis controlling for fixed effects continues to produce a U-shaped relationship between well-being and age, although this U-shape is flatter for life satisfaction than for the GHQ measure of mental well-being. The pattern of the estimated cohort effects also differs between the two well-being measures and, to an extent, by demographic group. In particular, those born earlier report more positive GHQ scores, controlling for their current age; this phenomenon is especially prevalent for women.
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Notes
- 1.
The sample in Mroczek and Spiro (2005) actually consists of veterans over the age of 40, so that their finding of an upward-sloping profile is not inconsistent with a U-shape over all ages.
- 2.
Graham and Ruiz Pozuelo (2017) find a U-shape in 44 out of 46 countries investigated in Gallup World Poll data. This conclusion does not however hold for all well-being measures. In Stone et al. (2010), a U-shape is found for the Cantril ladder and positive emotions in Gallup data, but not for negative emotions.
- 3.
Putnam (2000), page 141, concludes that the decline in trust in the US is purely a cohort phenomenon, with each cohort’s trust not changing over time.
- 4.
This is the conclusion reached by Easterlin and Schaeffer (1999), using 20 years of cohort data from the US General Social Survey. Kassenböhmer and Haisken-DeNew (2012) suggest that the U-shape in German Socio-Economic Panel (SOEP) data is entirely explained by individual fixed effects and experience in the panel. Cribier (2005) is an evocative account of the differences in life experience between two cohorts of French workers born only 14 years apart.
- 5.
The wave 1 sample was drawn from 250 areas of Great Britain. Additional samples of 1500 households in each of Scotland and Wales were added to the main sample in 1999, and in 2001 a sample of 2000 households was added in Northern Ireland.
- 6.
More precisely: whether subjective well-being changes systematically in a way that cannot be explained by the standard set of explanatory variables (covering income, employment, health, demographics etc.).
- 7.
One worry is that the GHQ is singularly unsuitable for this kind of analysis, as its constituent parts are explicitly phrased in terms of comparisons to usual. It is worth noting that the empirical literature on GHQ scores treats them unambiguously as indicators of the level of well-being, and it was for this purpose that the instrument was designed. On a practical level, the employed’s GHQ is more strongly correlated with job satisfaction levels in the BHPS data than with job satisfaction changes. Last, with 18 years of balanced panel data, a relatively direct test of the usefulness of the GHQ score in this respect can be envisaged. If events become more ‘usual’ as an individual ages, then the standard deviation of GHQ scores (and of its individual components) will fall with age. There is no evidence of this phenomenon in balanced BHPS panel data.
- 8.
Alternatively, the responses to the GHQ-12 questions can be used to construct what is known as a Likert measure. This is the simple sum of the responses to the 12 questions, coded so that the response with the lowest well-being value scores 3 and that with the highest well-being value scores 0. This count is then reversed, so that higher scores indicate higher levels of well-being. The measure thus runs from 0 (all 12 responses indicating the worst psychological health) to 36 (all responses indicating the best psychological health). Practically, the results are very similar between the Caseness and Likert measures.
- 9.
Income is measured in real terms, having been deflated by the CPI.
- 10.
Nolen-Hoeksema and Rusting (1999) conclude in their survey article that women exhibit higher incidence rates for almost all of the mood and anxiety disorders, but in general report higher levels of happiness.
- 11.
Blanchflower and Oswald (2004) explicitly do not control for health in their statistical analysis.
- 12.
Alternatively, interaction terms between age and wave can be introduced into Table 1’s regressions; these give qualitatively very similar results.
- 13.
Blanchflower and Oswald (2004) carry out a similar test on American General Social Survey data, and conclude that there is only slight evidence that the minimum moves to the right over time. The GSS is not, however, a panel.
- 14.
This is also the approach is taken in Blanchflower and Oswald (2008), where the cohort appears in 10-year blocks. Wunder et al. (2013) do not introduce cohort effects at all, and estimate the age profile semi-parametrically in BHPS and SOEP data, which produces a U-shape (deeper in the BHPS) up until the age of retirement.
- 15.
It has often been observed that income is hump-shaped in age, for example, so that holding income constant will deepen the well-being U-shape. Equally, Glaeser et al. (2002) suggest that social capital is hump-shaped in age. Frijters and Beatton (2012) find that introducing controls deepens the U-shape in their analysis of SOEP, Australian HILDA and BHPS panel data.
- 16.
Easterlin (2006) reaches a similar conclusion for happiness in US cohorts.
- 17.
Blanchflower and Oswald (2008) also find a U-shaped pattern of birth cohort effects in life satisfaction, using 27 years of Eurobarometer data.
- 18.
Such comparisons to the past imply that, in the long run, the correlation between GDP per capita and individual well-being may well be small. For some recent empirical contributions to this debate, see Diener and Oishi (2000), Easterlin (1995) and Oswald (1997). This literature is surveyed in Clark et al. (2008).
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Acknowledgements
I am grateful to Dick Easterlin, Carol Graham, David Halpern, Mike Hagerty, Laurence Hazelrigg, Felicia Huppert, Hendrik Juerges, Nicolai Kristensen, Ken Land, Orsolya Lelkes, Andrew Oswald, Steve Platt, Claudia Senik, Andrew Sharpe, Peter Warr and Rainer Winkelmann for useful discussions. The BHPS data were made available through the ESRC Data Archive. The data were originally collected by the ESRC Research Centre on Micro-social Change at the University of Essex. Neither the original collectors of the data nor the Archive bear any responsibility for the analyses or interpretations presented here.
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Appendices
Appendices
1.1 Appendix A
The 12 questions used to create the GHQ-12 measure appear in the BHPS questionnaire as follows:
-
1.
Here are some questions regarding the way you have been feeling over the last few weeks. For each question please ring the number next to the answer that best suits the way you have felt.
Have you recently… .
-
a)
been able to concentrate on whatever you’re doing?
Better than usual 1
Same as usual 2
Less than usual 3
Much less than usual 4
then
-
b)
lost much sleep over worry?
-
e)
felt constantly under strain?
-
f)
felt you couldn’t overcome your difficulties?
-
i)
been feeling unhappy or depressed?
-
j)
been losing confidence in yourself?
-
k)
been thinking of yourself as a worthless person?
with the responses:
Not at all 1
No more than usual 2
Rather more than usual 3
Much more than usual 4
then
-
c)
felt that you were playing a useful part in things?
-
d)
felt capable of making decisions about things?
-
g)
been able to enjoy your normal day-to-day activities?
-
h)
been able to face up to problems?
-
i)
been feeling reasonably happy, all things considered?
with the responses:
More so than usual 1
About same as usual 2
Less so than usual 3
Much less than usual 4
-
a)
1.2 Appendix B
1.3 Appendix C
GHQ fixed effects by year of birth
Life satisfaction fixed effects by year of birth
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Clark, A.E. (2019). Born to Be Mild? Cohort Effects Don’t (Fully) Explain Why Well-Being Is U-Shaped in Age. In: Rojas, M. (eds) The Economics of Happiness. Springer, Cham. https://doi.org/10.1007/978-3-030-15835-4_17
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