Mapping the landscape: a survey on the evolution and similarities among alternative well-being indicators

The limitations of GDP as a measure of societal well-being have led to a proliferation of “Beyond GDP” indicators, yet systematic comparisons remain scarce. This paper addresses this gap by combining text-mining techniques with empirical analysis to examine similarities and differences among major international well-being indices. Particular attention is given to the treatment of inequality, highlighting its marginal integration and the shortcomings of relying solely on the Gini index. Using Cosine and Jaccard similarity measures, we identify conceptual overlaps, redundancies, and the distinctiveness of environmental indicators such as the Ecological Footprint and the Environmental Performance Index. Empirical validation shows moderate alignment between textual similarity and statistical co-movement, supported by a novel application of spatially stratified heterogeneity analysis, which reveals strong regional structuring of socio-economic, but not environmental, indicators. These findings offer a comprehensive mapping of the well-being indicator landscape and practical guidance for selecting complementary, inequality-sensitive and regionally appropriate metrics for policy and research. • Text-mining and empirical analysis uncover conceptual and statistical similarities among global well-being indicators. • Environmental indicators (EF and EPI) show unique profiles, highlighting their complementarity to socio-economic indices. • Moderate alignment is found between text-based similarities and empirical co-movement of indicators. • SSH analysis reveals strong regional patterns in socio-economic indicators, absent in environmental ones. • One-third of indices include inequality, often via Gini index, calling for richer, context-sensitive metrics.