index (Diener et al., 2009) and ultimately reflects the analysts’ and policy makers’ subjective opinions on the value of different domains for experienced welfare (Diener et al., 2009).

Second, objective measures capture well the quantifiable part of a concept but often do not include all its relevant and/or qualitative aspects. Income does not always reflect people’s standard of living or whether people are able to make ends meet (Ravallion, 2012). People may have to work two or three jobs to ensure that they have sufficient income, or they may have to commute long distances on a daily basis to access well-paying jobs. Similarly, objective crime levels are not always accurate in capturing the safety in an area (Lorenc et al., 2012) and objective inequality can differ considerably from perceived inequality (Gimpelson & Treisman, 2018). Standards of living are affected by environmental and climate issues, quality of public services, governance, social cohesion, and other difficult to measure quality dimensions of development. SWB measures factor in the effects of these issues on experienced welfare by gauging people’s evaluations, experiences, and expectations (Diener et al. 2009; Jahedi & Mendez, 2014).

Third and particularly related to this research, SWB data can be used to uncover the objective and subjective conditions that underpin experienced welfare using regression analyses and identify the domains that are most important in explaining changes in experienced welfare for specific groups. The main objective and subjective factors underpinning individuals’ SWB have been welldocumented (Helliwell, 2006; Frey, 2010; Layard, 2011; Clark, 2018), but the regressions used in these analyses pose challenges. Systematic differences have been found in how people value different domains of importance to experienced welfare across and within countries (Deaton, 2008; Tiefenbach & Kohlbacher, 2016). In addition, people recalibrate their SWB based on the ‘ideal’ they have for their personal life (‘reference point’). Thus, people’s values and preferences may change over time. Technological advances have accelerated the change in reference norms and in many places around the world they have increased people’s frustration with relative income differences (Graham, 2005).

# _2.2. Drivers of SWB_

Genetic factors and personality traits explain to a large extent differences in SWB between people (Bartels, 2015), but other personal characteristics, including age (Clark, 2019), health (Graham, 2008), income (Clark et al., 2008), marital status (Stutzer & Frey, 2006), social contacts (Helliwell, 2006), and employment status (Winkelmann, 2014), also play a role. In addition, the livability of the environment also matters in that differences in SWB between countries are mostly driven by differences in economic development (37%), the quality of and access to health care services (15%), freedom (11%), and the availability of social support (8%) (Clark, 2018). Although there are cross-country variations in the relative importance of different domains, several papers have shown that the correlates of SWB are quite similar across cultures (Helliwell et al., 2010; Tov & Diener, 2013; Diego-Rosell et al., 2018), with the difference that economic factors appear to be more important in developing countries (Oishi, 2010), while freedom has a stronger correlation with SWB in more affluent and individualistic countries.

In Latin America and the Caribbean, as in other developing regions, economic factors are considered important drivers of SWB (Diego-Rosell et al., 2018), but income perceptions (e.g. formed based on comparisons of one’s income with that of the relevant age- and gender-based reference group) seem to be as important for people’s SWB as absolute income.<sup>10</sup> In Brazil, GoriMaia (2013) finds that neighborhood income is negatively associated with self-reported perceptions of income sufficiency, i.e., families with the same income are less likely to report sufficient income in high-income neighborhoods. Islam et al. (2009) report that the relationship

> 10 See also Macchia et al. (2019) who show that the rank of income is more strongly associated with well-being in more unequal nations.

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