Striving Scale”. Respondents were shown a picture and told, “Here is a ladder representing the ‘ladder of life.’ Let's
suppose the top of the ladder represents the best possible life for you; and the bottom, the worse possible life for you. On
which step of the ladder do you feel you personally stand at the present time?” Respondents were asked to choose a step
along a range of 0 to 10. As before, we run an ordered probit of the ladder ranking on country fixed effects to estimate
average levels of subjective well-being in each country, and we compare these averages with the log of GDP per capita in
Figure 3. These data show a linear relationship similar to that seen in Figure 2.
The most ambitious cross-country surveys of subjective well-being come from the 2006 Gallup World Poll. This
is a new survey designed to measure subjective well-being consistently across 132 countries. Similar questions were asked
in all countries, and the survey contains data for each country that are nationally representative of people aged 15 and
older. The survey asks a variety of subjective well-being questions, including a ladder question similar to that used in the
2002 Pew survey. As Figure 4 shows, these data yield a particularly close relationship between subjective well-being and
the log of GDP per capita. Across the 131 countries for which we have usable GDP data (we omit Palestine), the
correlation exceeds 0.8. Moreover, the estimated coefficient on log GDP per capita, 0.42, is similar to those obtained
using the World Values Survey, the Pew survey and from the earlier surveys, including those assessed by Easterlin. These
findings are also quite similar to those found by Deaton (2008), who also shows a linear-log relationship between
subjective well-being and GDP per capita using the Gallup World Poll.15 Deaton emphasizes that the clearer relationship
in the Gallup data reflects the inclusion of surveys from a greater number of poor countries.
As discussed previously, the economics literature has tended to treat measures of happiness and life satisfaction as
largely interchangeable, whereas the psychology literature distinguishes between the two. We now turn to assessing the
relationship between measures of happiness and income and comparing these estimates with the estimates of the
relationship between measures of life satisfaction and income considered thus far. (We consider additional measures of
subjective well-being and their relationship to income in a later section.) Figure 5 investigates both the happiness-GDP
link and the life satisfaction-GDP link estimated using the latest wave of the World Values Survey—the life satisfaction
data are those discussed above. Happiness is measured using the following question: “Taking all things together, would
you say you are: ‘very happy,’ ‘quite happy,’ ‘not very happy,’ ‘not at all happy?’” The results suggest that these
measures may not be as synonymous as previously thought: happiness appears to be somewhat less strongly correlated
with GDP than is life satisfaction.16 Although much of the sample shows a clear relationship between log income and
happiness, these data yield several particularly puzzling outliers. For example, the two poorest countries in the sample,
15 We estimate a well-being-income gradient that is about half that estimated by Deaton because we have standardized our estimates
through the use of ordered probits, whereas Deaton is estimating the relationship between the raw life satisfaction score and log
income. Putting both on a similar scale yields similar estimates. Appendix A compares our ordered probit approach with other
possible cardinalizations of subjective well-being.
16 The contrast in Figure 5 probably overstates this divergence, as it plots the data for the 1999-2004 wave of the World Values
Survey, whereas Table 1 shows that earlier waves yielded a clearer happiness-GDP link.