Modelling well-being to aid in social–ecological transitions

Achieving a good life for all within planetary boundaries requires understanding what contributes to human flourishing, yet most macroeconomic models treat GDP as an end goal despite its poor correlation with well-being in high-income societies. Here we investigate key determinants of human well-being that are readily measurable and useful in advancing integrated assessment models (IAMs). We first compile and harmonize global survey data (World Values Survey, Gallup World Poll, Global Flourishing Study) to identify how socioeconomic, biophysical, and cultural markers codetermine human well-being. We then compare survey data to time use data from the Human Chronome Project and an array of material factors using advanced statistical methods (e.g. fixed-effects panel regression) and machine learning (e.g. random forests). We reveal robust patterns that challenge assumptions about relationships between material consumption and life satisfaction. We also interrogate the relationship between self-reported or subjective well-being and more normative understandings of the good life, including societal characteristics like whether wealth is fairly distributed (using inequality metrics e.g. Gini coefficient) or whether citizens have influence over collective decision-making (using e.g. “political voice” metrics from Raworth’s Doughnut). These findings are used to propose new empirically-derived well-being indices for use in macroeconomic models. Models incorporating these metrics provide a powerful tool for policymakers to target well-being outcomes directly, rather than relying on imprecise proxies like GDP. It is our hope that the next generation of IAMs—or environment–society-economy models, more broadly—incorporate these insights to help guide just transitions within and between countries.