A brief history of measuring happiness
There are long-standing doubts (in economics) that happiness either can be or needs to be measured. According to Layard (2003): In the eighteenth century Bentham and others proposed that the object of public policy should be to maximise the sum of happiness in society. So economics evolved as the study of utility or happiness, which was assumed to be in principle measurable and comparable across people. It was also assumed that the marginal utility of income was higher for poor people than for rich people, so that income ought to be redistributed unless the efficiency cost was too high. All these assumptions were challenged by Lionel Robbins in his famous book on the Nature and Significance of Economic Science published in 1932. Robbins argued correctly that, if you wanted to predict a person’s behaviour, you need only assume he has a stable set of preferences. His level of happiness need not be measurable nor need it be compared with other people. Moreover economics was, as Robbins put it, about “the relationship between given ends and scarce means”, and how the “ends” or preferences came to be formed was outside the scope of the discipline. New momentum Interest in measuring happiness has returned in recent decades (see figure 1) [1]. This seems to be caused by the Easterlin paradox, the (contested) finding that while richer people are more satisfied with their lives than poor people, an increase in average wealth does not raise average life satisfaction;
The idea governments should measure SWB and use it to guide policy has started to take root. In 2013 the OECD issued guidelines recommending its member-nations collect SWB data:Paragraph. Zur Bearbeitung hier klicken. There is now widespread acknowledgement that measuring subjective well-being is an essential part of measuring quality of life alongside other social and economic dimensions [...] The Guidelines also outline why measures of subjective well-being are relevant for monitoring and policy making. The UK’s Office of National Statistics have been collecting data on subjective well-being (SWB) (see previous post in this series) since 2012 and currently polls 158,000 people a year. (Readers unfamiliar with SWB measures may find their FAQs helpful.)
Now, some scholars who argue we shouldn’t use SWB measures, such as Fleurbaey, Schokkaert and Dencanq (2009), nevertheless accept such measures are meaningful: With the mass of data accumulated on happiness and satisfaction and the development of their econometric exploitation, subjective utility seems more measurable than ever. There now seem to be good reasons to trust the existence of sufficient regularity in human psychology, so that interpersonal comparisons appear feasible in principle.These new developments have triggered a revival of welfarism as well. If utility can be measured after all, why not take it as the metric of social welfare? Several authors have taken this line (Kahneman et al. 2004b, Layard 2005). However, none of the recent developments in the field of measurement directly undermine the arguments that were raised against welfarism in the philosophical debates of the previous decades. The fact that something becomes easier to measure does not give any new normative reason to rely on it. This article has noted that there is a growing consensus happiness can be meaningfully measured, but hasn’t given an explanation for why we might think this. That’s what we cover in the next post in this series.
Endnotes
[1] OECD (2013, p20) notes “during the 1990s there was an average of less than five articles on happiness or related subjects each year in the journals covered by the Econlit database. By 2008 this had risen to over fifty each year” [2] E.g. Thinking, Fast and Slow by Kahneman (2011) [3] E.g. see the Sen-Fitoussi-Stiglitz report: Commission on the Measurement of Economic and Social Progress (2009) |