Nicole Hassoun (Binghamton University) - How should we measure welfare? Doing so is important for many reasons. Policy makers have recently turned towards various measures and indicators of well-being in addition to purely economic measures, such as GDP per capita. The hope is that these indicators will help a variety of actors evaluate progress in ensuring that everyone lives good lives. Scientists have responded with a variety of new metrics from the Human Development Index, Genuine Progress Indicator, and Sustainable Economic Development Assessment to the measures employed in the Organization for Economic Cooperation and Development Framework for measuring well-being and progress and the World Happiness Report (International Panel on Social Progress, 2016; Helliwell, Layard, & Sachs, 2013). But which, if any, of these metrics should we use and for what purpose? This paper has three aims. First, to defend what some have called the “vending machine” approach to measuring well-being. It suggests that we should attempt to measure what we think matters. We can judge the success of the measure by seeing whether it approximates the correct theory well enough for a given purpose. Second, this paper aims to provide some useful guidance for actually creating measures by, for instance, distinguishing some of the main choices that researchers must make when constructing different kinds of measures. In doing so, I will establish that the process of trying to implement a theory can benefit not only the resulting measures but the theory as well. That is, we can improve the theory in the process. I will argue that determining the best measure is ultimately an empirical question, which depends on the purpose of the inquiry and the need for accuracy amongst other things. Third, to make the case that it is useful to have a well-worked out theory of well-being before attempting to measure it, this paper points out that if we lack such a theory, we may not only use the wrong measures for the wrong purposes, but we may use poor proxies as well. Moreover, we may fail to actually measure an interesting phenomenon. This paper makes these points by reflecting on how insufficient attention to theory has caused problems for scientists developing and employing measures of life quality and many other things in the past (Brey 2012; Alexandrova 2017).
