Climate policy uncertainty and green total factor energy efficiency: Does the green finance matter?

Abstract

This study investigates the impact of climate policy uncertainty (CPU) on green total factor energy efficiency (GTFEE) and examines the moderating role of green finance (GF). Using a panel data analysis framework combined with the super-efficient SBM-DEA model, the study finds that CPU has a significant negative effect on GTFEE, indicating that increased policy uncertainty hinders the improvement of urban energy efficiency. At the same time, GF plays an important moderating role in alleviating the negative impacts of CPU, particularly in environments with higher policy uncertainty, where GF can effectively promote energy efficiency. Additionally, the study discovers that the development of artificial intelligence (AI) industries significantly moderates the relationship between GF and GTFEE. In cities with more advanced AI technologies, AI helps boost energy efficiency. Overall, the findings offer important policy recommendations on how to improve energy efficiency through green finance in uncertain policy environments , with broad applicability, especially in advancing low-carbon economies. • CPU negatively affects GTFEE in urban areas. • GF mitigates the negative impact of CPU on GTFEE. • A U-shaped relationship exists between GF and GTFEE. • AI enhances green finance's impact on energy efficiency in advanced AI cities.