The energy-sustainability nexus: A probabilistic approach to policy prioritization

This study aims to identify and rank the key factors driving sustainability within the Future of Growth framework, emphasizing the role of energy-related dynamics. Given the urgency of transitioning to greener economies, this research explores how various sustainability drivers interact, offering policymakers data-driven insights into the most impactful areas for fostering environmental and economic resilience. The study utilizes data from the World Economic Forum's Future of Growth Report 2024, encompassing 107 countries. A Bayesian Belief Network (BBN) model is employed to analyze the interdependencies among 14 key sustainability variables, including renewable energy consumption, investment in renewable energy, green patents, energy efficiency regulations, fossil-fuel subsidies, and environmental technology trade, among others. The analysis reveals that renewable energy consumption, investment in renewable energy, and environmental technology trade serve as critical accelerators of sustainability. Conversely, low performance in fossil-fuel subsidies and greenhouse gas emissions poses serious threats. The study also highlights the interconnected effects of sustainability drivers, emphasizing the need for integrated policy responses. By incorporating a probabilistic approach to sustainability assessment, this study advances the literature on energy transition and environmental policy modeling. The findings provide a data-driven roadmap for policymakers, helping prioritize actions that yield the highest sustainability gains. The Bayesian modeling framework offers a structured way to assess trade-offs, ensuring that policy interventions effectively target the most influential sustainability levers.