constraints exist. Also, they do not fully eliminate some degree of arbitrariness (for example, on the number of indicators, functional forms, or aggregation of indicators per components). However, they allow for monitoring, profiling, benchmarking, and analytical functions in a systematic way. They also allow for multiple robustness checks that confirm that our key results are not predetermined by these choices.

Our empirical exploration highlights three main results. First, a given country’s social sustainability is positively correlated with per capita income levels and negatively correlated with poverty headcounts and income inequality. This is also true for each of the four components of social sustainability. Second, these associations are not equally strong. Process legitimacy and social inclusion tend to be more strongly associated with higher income and lower levels of poverty and inequality, the opposite being true for resilience and social cohesion. Third, results are generally robust to the choice and number of social indicators, different functional forms, and alternative developmental outcomes.

Both the global database and the analysis can be further expanded and improved. The global database would benefit from including a previous time period (and future ones) to enable longterm monitoring. Further variables need to be explored to increase the number of countries for which social sustainability indices can be constructed. Currently, only 40 countries have information for every resilience indicator, compared with 139 that have data for every process legitimacy indicator, something which has implications for the precision of each dimension. More analysis is also needed to understand how the variation of social indicators across vulnerability groups within a country affects our results. In addition, both the global database and analysis are conducted at national levels. Scholars working on social sustainability in the future will hopefully be able to draw on data sets from more countries with data representative at the subnational and even city level. This will allow for an enhanced within- and between-country monitoring of social sustainability. More analysis is also needed to understand the interactions between different components of social sustainability. For example, we know relatively little about the systematic association between social cohesion and resilience or the extent to which process legitimacy is stronger in contexts with high levels of social inclusion. Providing insights on these interactions, their strength and their dynamics is fundamental for policy design that effectively considers synergies between social dimensions. Finally, future analyses might draw out not only correlations but also causal relationships between the different dimensions of social sustainability and various developmental incomes. For this, a more econometrically sound analysis based on temporal and panel data series of countries is required, which would need in turn to draw from a global database spanning several decades.

Despite these limitations, our analysis underlines several important policy messages. One, empirical evidence supports the claim that social sustainability has a concrete importance, because it is associated with reduced poverty, greater equality, and increased GDP per capita. While this only meets a narrow definition of development, and one that needs further substantiation and explanation, it systematically shows a foundational link between social sustainability and basic developmental outcomes. Two, it is not only desirable but also possible to reduce poverty and inequality while increasing social sustainability. This is the case because all social sustainability dimensions move in the same direction when it comes to poverty and inequality reduction (as well as other development outcomes such as human capital and human 24