The interactions of rare earth minerals with renewable energy production alongside artificial intelligence and geopolitical risk

This research examines the unexplored aspects of the asymmetric and symmetric relationship between rare earth minerals and renewable energy production considering AI (artificial intelligence) and geopolitical risk. Analyzing data from 1991 to 2020, the study focuses on seven rare earth mineral-rich countries, offering a unique perspective on this understudied dimension. We applied advanced econometric approaches, including the cross-sectional non-linear autoregressive distributed lag (CS-NARDL) for asymmetric computation, the cross-sectional autoregressive distributed lag (CS-ARDL) for symmetric computation, and the autoregressive distributed lag-error correction model (ARDL-ECM) for cross-country computation. The results reveal that rare earth minerals contribute to a consistent, positive, and substantial effect on the renewable energy production in positive shocks and symmetric connectedness. Meanwhile, negative disruptions in rare earth minerals lead to a decline in renewable energy production. However, AI plays a significant role in facilitating and improving renewable energy production. While, geopolitical hazards significantly impede the advancement of renewable energy. As per country-specific computation, rare earth minerals and AI have a positive and significant impact on the development of renewable energy in almost all countries. Our research provides factual evidence highlighting rare earth elements' crucial significance in renewable energy and their broader role in shaping future sustainable paths.