This book examines the evolution of happiness research, considering the famous “Easterlin Paradox,” which found that people’s average life satisfaction didn’t seem to depend on their income. But they question whether happiness research can measure what needs to be measured. Laura Kudrna argues this book is well worth a read for its excellent coverage of much of the happiness literature from large surveys, as well as the interesting arguments put forth about how we should interpret this evidence.
Measuring Happiness: the Economics of Wellbeing. Joachim Weimann, Andreas Knabe and Ronnie Schöb. MIT Press. February 2015.
In Measuring Happiness, three German economists – Joachim Weimann, Andreas Knabe and Ronnie Schob – tackle hard questions about happiness armed with the latest academic evidence. They focus on what large, national surveys say about what makes us happy, and they critically engage with classic findings such as the Easterlin Paradox, the relative income effect, and the relationship of unemployment with happiness. Instead of rehearsing old debates, however, they integrate new research and novel opinions that add fresh insight to longstanding questions in the happiness literature. The authors’ rendering of the academic evidence is accurate and very readable, although at times the work may have benefited from a more psychological perspective. Personality, for example, may not be as stable across the life course as they seem to believe, and separating the effects of determinants like income on happiness from those of personality can’t necessarily be eliminated with the statistical techniques they recommend.
One of the major strengths of the book is its interrogation of the definition of happiness, rightly separating evaluations from experiences, and hedonic or ‘pleasure’-based happiness from eudemonic or ‘purpose’-based happiness. Many people make claims about what makes people happy without actually defining what happiness is in the first place but the authors do not fall into this trap. In fact, Weimann, Knabe and Schob have made a very important contribution to this field with original empirical work revealing that although people who are unemployed are less satisfied with their lives overall, they are not unhappy according to their experiences because they use their free time quite well. This is a fascinating insight worthy of further exploration. For example, although employment status is not associated with experiences of pleasure, it is possible that people who are unemployed could feel as if their experiences are not particularly meaningful and their data do not appear to speak to this. Moreover, since moments of unhappiness feel as if they last longer than moments of happiness, the unemployed could still be less happy than the employed according to their experiences of subjective rather than objective time but again, their data do not appear to address this issue.
Sign in Bhutan. Photo Credit: International Rivers. CC-BY-NC-SA.
It is always interesting when academics are freed from the rigid requirements of academic journals to interpret the implications of research findings. To this end, the authors argue that because unemployment is not closely associated with experiences of pleasure, experiential measures of happiness are not a good guide for evaluating the effects of social conditions – and that instead, we should look to evaluative measures of happiness. But it does not seem logical to allow differences in the determinants of different sorts of happiness to inform which type of happiness measure is best. The best measure of happiness is surely one that best reflects how well our lives are going, and whether or not what we think should be associated with that measure actually is cannot – by itself – speak to the value of that measure. Psychological research shows that we are not very good at predicting what makes us happy because we fail to accurately predict what we will and will not adapt to. Thus we should assess the value of different sorts of happiness measures for policy not according to our sometimes flawed judgments of what we think should affect them, but rather according to how well the measures capture what they should – happiness.
There is much more covered in the book, including about what conclusions can be drawn from research into the relative income effect, concerns about how people interpret happiness scales, and a fascinating – though technical – tour of the history of happiness research tucked into an Appendix. The book is well worth a read for its excellent coverage of much of the happiness literature from large surveys, as well as the interesting arguments put forth about how we should interpret this evidence. Hopefully it will inspire further critical discussions about whether these are the best interpretations and how we can best learn from happiness research.
Laura Kudrna is a Doctoral Candidate in Social Policy at the London School of Economics. Her PhD investigates the effects of socio-economic status on wellbeing in the English Longitudinal Study of Ageing and the American Time Use Surveys. She is also a researcher at LSE’s Behavioural Research Lab, conducting experiments on prosocial behaviour, status and wellbeing.