Pathways to Sustainable Wellbeing: A Bayesian Approach to Decent Living Within Planetary Boundaries

2026-07-22

As the world faces escalating environmental crises driven by human economic activity, research on planetary boundaries highlights critical ecological limits necessary to sustain human life. High-income countries primarily drive the overshoot of these boundaries, yet conventional economic models continue to promote perpetual growth, hindering key ecological goals like reducing resource use and achieving rapid decarbonization. Ecological economics suggests shifting from growth-centric approaches to post-growth strategies that prioritize reducing unnecessary production and consumption. While concerns exist about potential social consequences to post-growth pathways, evidence in post-growth literature indicates that both social and ecological objectives can be met simultaneously. This project aims to advance this research by modeling the relationship between resource use and human wellbeing, identify optimal conditions for decent living within planetary boundaries across diverse contexts, quantify the probability of achieving wellbeing under different policy scenarios, and influence policy debates around degrowth. The model will utilize Bayesian probabilistic methods due to their ability to integrate both qualitative and quantitative data, to capture complex interdependencies among the social and biophysical indicators of wellbeing, make causal inferences, and ultimately provide insights for decisionmakers. Meeting the project objectives will involve developing a comprehensive Bayesian Belief Network (BBN) model as a framework to quantify the likelihood of achieving decent living standards under various scenarios while accounting for uncertainties and diverse regional contexts. This research will take an interdisciplinary approach to gain new insights that will inform policy decisions that prioritize human wellbeing, supporting post-growth economies that align environmental and social objectives globally.

Spain

2026-01-01