Gil Hersch (Virginia Tech) - There are a variety of measures that are considered by their proponents to be good ways of operationalizing well-being. These include the traditional economic measures, such as Gross Domestic Product (GDP) per capita, Subjective Well-Being (SWB) measures, such as questionnaires about how one evaluates her life as a whole, as well as capabilities-based measures such as the OECD’s Better Life Index (BLI). But how does one decide which measure is a better operationalization of well-being? Advocates of different measures provide only a cursory account of why their chosen measure is an appropriate operationalization of well-being. I argue that this is a significant gap in the literature, which once addressed, will enable a much more reasoned way of choosing between different measures of well-being. The problem faced in the well-being literature can be described as similar to what Chang (2004) calls the “problem of nomic measurement,” which arises when we want to measure a quantity X that is not directly observable. We infer it from another quantity Y, which is directly observable, but we have no way of establishing empirically what the law that governs the relationship between Y and X is. In the context of well-being, proposed measures of well-being can be thought of as quantity Y whereas well-being itself can be thought of as quantity X. The question then is how to figure out if there is a function f, and what it is, without being able to measure quantity X directly. If we are ever to decide which of the different measures Y is a better operationalization of well-being X, we need to look at how the proponents of the different measures account for the link between well-being and the measure they champion. What we need from those advocating for various measures as measures of well-being as a whole is that they provide fully fleshed out accounts of why their chosen measure is indeed a measure of well-being. It would then be possible to seriously examine the merits of each measure as an operationalization of well-being. Without such positive accounts, all we are left with are negative arguments against different measures. While negative arguments are helpful in guiding us as to which measures seem to be poor operationalizations, in light of the variety of ways one can defend multiple measures as operationalizations of well-being, the process of elimination is a long one. Looking at the assumptions that support different accounts, we can judge the relative plausibility of these accounts. This is a comparative exercise. It is only meaningful to reject an account in favor of a given measure as an operationalization of well-being when a more plausible account is at hand.
