level.21 Figure 7 shows that the log specification yields a better fit, although the difference is small (Deaton, 2008, p. 58).
Viewed either way, there remains robust evidence of a strongly positive well-being-income link for rich countries. We
have re-estimated the well-being-GDP relationship using levels of GDP per capita as the independent variable and found
that the well-being-GDP gradient is about twice as steep for poor countries as for rich countries. That is, consistent with
our earlier findings, a rise in income of $100 is associated with a rise in well-being for poor countries that is about twice
as large as for rich countries. (A 1 percent rise in GDP per capita is associated with much larger income gains, and hence
much larger well-being gains for rich countries.)
Thus, our conclusion that there is strong evidence against a satiation point is robust to whether one conceives of
well-being as rising with log GDP per capita or with its absolute level. As Figure 7 demonstrates, even with observations
on 131 countries, we have insufficient data to draw particularly strong inferences about the appropriate functional form,
although the evidence is certainly suggestive of a linear-log well-being-income relationship. In the next section we turn to
within-country comparisons, and given the much larger samples involved, it will be clear that—at least at the individual
level—well-being is best thought of as rising in log income. It is this finding that guides our choice of the appropriate
functional form for between-country comparisons.
IV. Income and Happiness: Comparing Within-Country and Between-Country
Estimates
A very simple benchmark for assessing the magnitude of the between-country well-being-GDP gradient measured
in the previous section (typically centered around 0.4) is the within-country well-being-income gradient. In particular,
Easterlin argued that “the happiness differences between rich and poor countries that one might expect on the basis of the
within country differences by economic status are not borne out by the international data” (1974, pp. 106-107). Thus, we
now turn to comparing the happiness of richer and poorer members of the same society at a single point in time.
On this question there is a clear consensus in the literature, aptly summarized by Easterlin: “As far as I am aware,
in every representative national survey ever done a significant bivariate relationship between happiness and income has
been found” (2005, p. 67). And indeed, we have made similar comparisons in over 100 countries and have yet to find a
(statistically significant) exception. Although there has been some debate about the magnitude of this effect, income is
clearly an important correlate with happiness. For example, Frank argues for the importance of income for happiness as
follows: “When we plot average happiness versus average income for clusters of people in a given country at a given
time.. .rich people are in fact a lot happier than poor people. It’s actually an astonishingly large difference. There’s no one
single change you can imagine that would make your life improve on the happiness scale as much as to move from the
bottom 5 percent on the income scale to the top 5 percent” (2005, p. 67).
21 In a levels specification, the subjective well-being-income gradient is curvilinear and thus is less steep among wealthier countries.
While the slope is never zero, the flattening out of the curve may be more easily misinterpreted as satiation.
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