A Comparative Review of Methods to Create a Composite Index for Sustainable and Inclusive Wellbeing
Societal goals need to shift from over-reliance on gross domestic product (GDP) to broader aspects of sustainable and inclusive wellbeing (SIW). However, defining SIW and eventually measuring it with a single number is problematic because it involves many subjective and objective contributors that combine in complex, non-linear ways. Conventional approaches either use linear weighted averages or reduce SIW to subjective wellbeing alone. Neither is sufficient. This paper reviews aggregation methods for SIW against nine conditions derived from needs theory and strong sustainability: limited substitutability, penalisation of imbalances, non-linear transformations, respect for environmental ceilings, respect for lower limits, a formative measurement model, no correlation requirement, distributional sensitivity, cross-border spillovers, and intertemporal aggregation. We compare 13 methods, from simple arithmetic means to penalty-based indices, outranking multicriteria, data envelopment analysis, and insights from ecology, neuroscience, and machine learning. Our illustrative example shows that aggregation choices change significantly country rankings. Compensatory methods create similar rankings. No single method satisfies all nine conditions. We conclude that a future SIW composite indicator will require combining methods across levels: non-linear normalisation, non-compensatory aggregation, and measurement-level choices for inclusiveness and spillovers. This paper provides a step towards the headline aggregated indicator advocated by the UN High-Level Expert Group on Beyond GDP.