In this spirit we examine the relationship between happiness and income in the United States from 1972 through
2006 using the General Social Survey (GSS), produced by the National Opinion Research Center. Figure 8 plots the
coefficients from an ordered probit regression of happiness on income category by year fixed effects against family
income. The x-axis, family income, is converted from income categories to income by fitting interval regressions to the
income data on the assumption that income follows a log-normal distribution.22 Each circle in the Figure represents an
income category in a particular year; the diameter of each circle is proportional to the population in the income category
in that year. The statistical significance of this relationship is not in doubt, largely because each round of the GSS (as with
most happiness surveys) involves over 1,000 respondents. This plot also leaves very little doubt about the functional form:
the linear-log relationship between our happiness index and family income is clearly evident throughout the income
distribution.23
To further investigate the functional form relationship, we investigated the relationship in other datasets for other
countries and find similar evidence pointing to a linear-log relationship between subjective well-being and income. In
Figure 9, we use the Gallup World Poll (as it covers the most countries of any of our data sets) and show estimates from a
regression of life satisfaction on separate income category fixed effects for each country, controlling for country fixed
effects. We have usable household income data for 113 countries.24 The coefficient estimates on the individual country-
household income category fixed effects are plotted against the log of household income, normalized by subtracting off
the country average. This figure also points strongly to a linear relationship between subjective well-being and the log of
family income, with no evidence of satiation.
It is the juxtaposition of these statistically significant cross-sectional findings with statistically insignificant cross-
country and time-series results that gave rise to the Easterlin paradox. Theories emphasizing relative income comparisons
would suggest that the between-country well-being-income gradient would be smaller than the within-country well-being-
income gradient (if relative income comparisons are made intranationally). Yet, the suggestive comparison of the
gradients in Figure 4 with Figure 9 points to the opposite conclusion, with the gradient estimated between countries larger
than that seen within the countries.
While Figure 9 plots the gradient seen when examining all of the countries together, it is worth estimating the
within-country well-being-income gradient separately for individual countries to see the range of estimated within-country
gradients. Thus, for each country we estimate an ordered probit regression of life satisfaction on the natural log of
household income, controlling for gender and a quartic in age, entered separately for men and women. The coefficient
estimates obtained in each regression (rounded to the nearest 0.05) are displayed in Figure 10 as a histogram summarizing
22 We thank Angus Deaton for this suggestion.
23 Because the GSS retained the nominal income categories used in 1973, some very low income cells are somewhat off the regression
line (the circles to the far left of the graph), reflecting both the fact that small cells yield imprecise happiness estimates and the
difficulties in imputing appropriate incomes to the bottom-coded group.
24 We drop Kenya because it lacks labels for income groups, Laos because it contains clearly implausible income groupings, and
Uzbekistan because the income categories listed in the data involve overlapping ranges. Respondent-level income data are unavailable
for Egypt, Iran, Iraq, Jordan, Kuwait, Latvia, Lebanon, Morocco, Pakistan, Palestine, the Philippines, Saudi Arabia, Sri Lanka,
Turkey, the United Arab Emirates, and Yemen. This leaves us with valid household income data for 113 countries.
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