More on the Easterlin Paradox: A Response to Wolfers

Justin Wolfers’ column titled “Debunking the Easterlin Paradox, Again” dismisses Richard Easterlin’s work as just plain wrong. I argue here, as I have elsewhere, that where you come out on the Easterlin paradox depends on the happiness question (and therefore the definition of happiness) that you use, as well as the sample of countries and the period of time.

Richard Easterlin finds no clear country-by-country relationship between average per capita GDP and life satisfaction (among wealthy countries), despite a clear relationship between income and happiness at the individual level within countries. Easterlin also found – and continues to find, based on methods different from Wolfers’ – an absence of a relationship between life satisfaction and long-term changes in GDP per capita.

Different well-being questions measure different dimensions of “happiness”, and, in turn, they correlate differently with income (something they themselves show at the end of their last paper, and admit that the relationship between income and well-being is complex). The best possible life question – which Justin Wolfers and Betsey Stevenson primarily use in the first work, and also in the second – asks respondents to compare their life today to the best possible life they can imagine for themselves. This introduces a relative component, and, not surprisingly, the question correlates most closely with income of all of the available subjective well-being questions. Life satisfaction, which they use in the second work, also correlates with income more than open-ended happiness, life purpose or affect questions, but not as closely as the best possible life question.

Wolfers and Stevenson used the most recent and extensive sample of countries available from the Gallup World Poll, and, as the measure of “happiness”, the best possible life question therein, and challenged the Easterlin paradox. In more recent work, with Stevenson and Dan Sacks (2010), referenced in this blog, the authors look at the relationship between life satisfaction and economic growth, based on the World Values survey and GDP levels and the best possible life question, based on the Gallup World Poll. They isolate a clear relationship between life satisfaction and GDP levels, and their statistical analysis is spot on.

Recent studies by Kahneman and Deaton (2010), and Diener and colleagues (2010), for example, find that happiness in a life evaluation sense (as measured by the best possible life question) correlates much more closely with income than does happiness in a life experience sense (as measured by affect or more open ended happiness questions). This holds within the United States (Kahneman and Deaton) and across countries (Diener et al.).

My own work on Latin America, with Soumya Chattopadhyay and Mario Picon, tested various questions against each other and finds a similar difference in correlation, with affect and life purpose questions having the least correlation with income and the best possible life question the most. My work on happiness in Afghanistan found that Afghans were happier than the world average (on par with Latin Americans) as measured by an open ended happiness question, and 20 percent more likely to smile in a day than Cubans. Yet they scored much lower than the world average on the best possible life question. This is not a surprise. While naturally cheerful and able to make the best of their lot, the Afghans also know that the best possible life is outside Afghanistan.

Thus the conclusions that one draws on whether there is an Easterlin paradox or not in part rest on the definition of happiness, and therefore the question that is used as the basis of analysis. Wolfers and co-authors find a clear relationship between GDP levels and life satisfaction and best possible life – clearly important dimensions of well-being. Yet in the same paper they find much less clear relationships when they use happiness, affect and life purpose questions.  

There is also the question of the sample of countries, and whether one is examining cross section or time series data. The most recent debate with Easterlin is about the trends over time rather than cross-sectional patterns. Dropping the transition economies, as Easterlin does, may be a mistake, as Wolfers contends. But it is also important to recognize the extent to which including a large sample of countries that experienced unprecedented economic collapse and associated drops in happiness alters the slope in the cross-country income-happiness relationship (making it steeper). Wolfers also criticizes Easterlin for relying on financial satisfaction data for his Latin American time series sample (because there is not enough life satisfaction data); financial satisfaction correlates closely, but not perfectly, with life satisfaction. Easterlin’s technique allows for the inclusion of a much larger sample of middle income developing countries, a sample of countries that one can imagine is very important to the growth and happiness debate. Wolfers and co-authors use far fewer Latin American countries because comparable life satisfaction data is limited. Either approach is plausible and, as with all work with limited data, is not perfect. But I would not go as far as calling one or the other “plain wrong”.

Finally, there is the simpler question of giving credit where credit is due. We would not be having this debate, nor would we have a host of analysis on well-being beyond what is measured by income, had Easterlin not triggered our thinking on this with his original study of happiness and income over three decades ago (and his patient and thoughtful mentoring of many economists since then). In the big picture of things, Easterlin had the idea.