something interesting, and with eating good tasting food. For most of these assessments the within-country coefficients
are larger than the between-country coefficients, although there are some notable exceptions. Figure 23 plots the
proportion of people having these experiences in each country against GDP per capita and feeling respected, or having
eaten good food display particularly strong relationships with GDP per capita. The proportion of people smiling or
laughing rises with income both within and between countries, although the coefficient estimates point to a somewhat
stronger relationship to income within countries. This last measure is particularly interesting, as smiling has been shown
to be correlated with reported levels of happiness or life satisfaction. Indeed, in these data, people who report smiling
more also tend to report greater life satisfaction. Finally, both Table 6 and Figure 23 point to an increasing ability to
choose how you spent your time during the day as income rises.
All told, these alternative measures of well-being paint a somewhat more nuanced picture of the different
experiences of rich and poor people within countries, and between rich and poor countries. Moreover, these data point to a
robust relationship between greater income and greater reported well-being. We suspect that these intriguing new cross-
country data collections will launch a productive research program aimed at better understanding the drivers of the robust
well-being-income gradient we have identified.
VII. Discussion
This paper has revisited—and where appropriate, revised—the stylized facts regarding the link between subjective
well-being and income. Our analysis encompasses virtually all of the extant data linking happiness or life satisfaction to
income. Moreover, we have endeavored to place this analysis in a single coherent framework that allows us to make
meaningful comparisons across different surveys and different ways of asking about subjective well-being. We were
motivated to better understand the Easterlin paradox, and so we have analyzed separately three relationships between
income and happiness: that obtained from contrasting rich and poor members of a society, that obtained from contrasting
rich and poor countries, and that obtained from observing the paths of average happiness as the average income of
countries change. Our measurement framework allows us to assess the extent to which these relationships may differ.
Our key contribution is the finding that the relationship between subjective well-being and income within
countries (that is, contrasting the happiness of rich and poor members within a country) is similar to that seen between
countries, which in turn is similar to the time-series relationship (comparing the happiness of countries at different points
in time as they get richer or poorer). In multiple datasets from several decades and covering various populations, we
estimate well-being-income gradients that tend to be centered around 0.4. We estimate slightly steeper gradients when
comparing well-being between countries, although reading across datasets and taking account of sampling error, we can
reject neither the hypothesis that the gradients are the same within and between countries, nor the hypothesis that there are
small differences between the two.
28