sense of the poverty head-count ratio. This is much less the case for social well-being indicators based on complex mathematical formulas, like the welfare indices proposed by Atkinson (1970).

Second, we focus on construction methods that are relatively simple to implement and explain. A successful method typically yields a good balance between conceptual validity and simplicity of implementation.<sup>22</sup> Also, the trade-offs that the indicator makes across dimensions should not appear as “black box” to policy makers. Aggregating the outcomes in different dimensions through utility function representing individual preferences may be conceptually satisfactory. However, it seems challenging to transparently explain the implicit trade-offs under which a given achievement vector is deemed “equivalent” to some monetary value in a reference situation (Boarini et al., 2022). With such aggregation, the policy maker has no direct way of checking whether the implicit trade-offs make sense to her.<sup>23</sup> For this reason, we mostly focus on aggregation methods based on weights.

Third, we focus on opportunities with the potential to be applied in the near future. We exclude avenues whose implementation would require data coming from new recurrent surveys. The data feeding the well-being indicator must come from available surveys. Note that this does not necessarily exclude opportunities that requires a one-off dedicated survey, say to fix the values of weights. We also exclude new data sources like bioindicators or cheaper data sources like remote sensing because we believe more work is necessary to firmly establish their relationship with determinants of well-being.

# **3.2 not based on dichotomous variables**

In this section, we consider two solutions to waste less data from variables that are already taken into account.

Both the global MPI and the World Bank’s MPM are based on the Alkire-Foster (AF) methodology to identify the multidimensionally poor (Alkire and Foster, 2011a).<sup>24</sup> In a nutshell, the AF methodology starts from a list of dichotomous deprivation variables sij ∈ {0, 1} where 1 means that i is deprived in variable j and 0 means i is not deprived. The AF methodology identifies individual i as (multidimensionally) poor when the weighted individuals. The latter gives full priority to individuals at the bottom of the well-being distribution. From a normative perspective, ignoring entirely the progress taking place above the poverty line is not satisfactory. However, from a pragmatic perspective, a poverty line allows constructing an easy-tocommunicate distribution-sensitive social well-being indicator: the poverty head-count ratio.

> 22For instance, in the monetary approach, the deflation methods based on demand-system à la Deaton and Muellbauer (1980) are rarely used in practice. Instead, simpler deflation methods based on price indices are routinely used in spite of being less conceptually satisfactory. Arguably, one key reason is the difficulty and the experience required to successfully implement the former methods.

> 23Relatedly, many parameters entering the definition of standard social well-being indicators have no intuitive meaning attached to their values, even for practitioners. This is arguably the case of coefficients of risk aversion or elasticities of inter-temporal substitution.

> 24See Appendix 6.1 for a succinct definition of both of these global multidimensional poverty measures.

16