The name is absent



upward by reverse causation, as happiness may well be a productive trait in some occupations, raising income. A different
perspective, from offered by Kahneman, et al. (2006), suggests that within-country comparisons overstate the true
relationship between subjective well-being and income because of a “focusing illusion”: the very nature of asking about
life satisfaction leads people to assess their life relative to others, and they thus focus on where they fall relative to others
in regard to concrete measures such as income. Although these specific biases may have a more important impact on
within-country comparisons, it seems likely that the bivariate well-being-GDP relationship may also reflect the influence
of third factors, such as democracy, the quality of national laws or government, health, or even favorable weather
conditions, and many of these factors raise both GDP per capita and well-being (Kenny, 1999).29 Other factors, such as
increased savings, reduced leisure, or even increasingly materialist values may raise GDP per capita at the expense of
subjective well-being. At this stage we cannot address these shortcomings in any detail, although, given our reassessment
of the stylized facts, we would suggest an urgent need for research identifying these causal parameters.

V. Economic Growth and Happiness

The last two sections have shown that wealthier societies have greater subjective well-being than poorer societies
and that, to a similar degree, wealthier members of a society are happier than their poorer counterparts. This then leads to
our final question: do societies get happier through time as they become richer? Easterlin argues that the possibly
confounding “cultural influences on international happiness comparisons underscore the importance of national time
series evidence... for inferring the relationship between subjective well-being and economic development” (1995, pp. 43-
44). Indeed, the core of the Easterlin paradox lies in Easterlin’s failure to isolate statistically significant relationships
between average levels of happiness and economic growth through time. Easterlin’s 1974 and 1995 papers contain three
important datasets, tracking the time series of happiness within Europe, Japan, and the United States.

Our analysis is based on three observations about the inferences that existing datasets can support. First, absence
of evidence should not be confused with evidence of absence. This is particularly important given both the variability of
happiness aggregates between surveys and the limited range of variation in time series rather than cross-national
comparisons of GDP per capita. Second, when we reanalyze these data, we find that happiness has in fact risen in Japan
and Europe. The failure of happiness to rise in the United States remains a puzzling outlier, although the extent to which it
constitutes a sharp exception should not be overstated. Third, as more data have become available, in the form of both
extended national time series and observations from new countries, evidence that happiness rises with GDP per capita has
started to accumulate.

Indeed, the World Values Survey has been running since 1981, and across its four waves we now have repeated
observations on a large number of countries, spread across several decades. Figure 14 shows the movement of both life
satisfaction and real GDP per capita across the waves for all countries for which this survey offers repeated observations.

29 Kenny argues directly for reverse causation running from happiness to income.

16



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