# **1. Introduction**

Widely used measures of subjective welfare ask survey respondents to rate their “economic welfare,” “satisfaction with life” or “happiness” on an ordinal scale. These measures have found innumerable applications in the psychological and social sciences and have recently become popular in economics.<sup>2</sup> However, different people may well have different ideas about what it means to be “rich” or “poor,” or “satisfied” or not with one’s life, leading them to interpret survey questions on subjective welfare differently.<sup>3</sup> For example, the Young Lives Project (2009) reports the comment of a six-year old in rural Vietnam, named Duy, as saying that “We are nearly rich as we have a new cupboard, but we haven’t got a washing machine.” Duy clearly has a different idea of what it means to be “rich” than those in Vietnam more familiar with the living conditions of the truly rich. Survey respondents can be expected to interpret subjective questions relative to their personal frame-of-reference, which will depend on latent aspects of their own knowledge and experience.

Two important applications of subjective welfare data illustrate why this matters. The first is their application in the interpersonal comparisons of welfare required for poverty measurement. Measures of “subjective poverty” are becoming common.<sup>4</sup> These measures tell us what proportion of survey respondents place themselves on the bottom rung (or possibly second lowest rung) of a welfare ladder from “poor” to “rich.” But if the rungs of the welfare ladder are not understood the same way by different respondents it is unclear what meaning can be attached to such measures.

The second application relates to the many studies of the covariates of subjective welfare.<sup>5</sup> In now standard practice, a linear or ordered probit (OP) regression is run of the survey

> 2 The relevant economics literature is reviewed by Frey and Stutzer (2002), Di Tella and MacCulloch (2006) and Dolan et al. (2008). The psychological literature on subjective welfare is reviewed in Diener et al. (1999) and Furnham and Argyle (1998). An alternative approach is to ask what level of income is needed to attain a given position on a ladder, such as not being “poor.” This is the “Leyden method” devised by van Praag (1968). While we do not use this type of data here, the same concerns about bias arise in the Leyden method.

> 3 While this paper focuses on heterogeneity in scales, there are other concerns with survey design. For example, Conti and Pudney (2011) find that minor re-designs in questions on satisfaction of life/work led to large changes in answers, particularly for women, finding that distortions in responses influence findings with respect to correlates of women’s job satisfaction. For an overview of the concerns about inferring welfare effects from subjective data see Ravallion (2012).

> 4 Examples include Mangahas (1995), Ravallion and Lokshin (2002), Carletto and Zezza (2006), and Posel and Rogan (2013). 5

Examples include van de Stadt et al. (1985), Clark and Oswald (1994, 1996), Kapteyn et al. (1998), Oswald (1997), Winkelmann and Winkelmann (1998), Pradhan and Ravallion (2000), McBride (2001), Ravallion and 2