Climate Policy Uncertainty and Renewable Energy Consumption: Multiple Insights from Digitization, Energy, and Innovation-Oriented Governance

This study applies the rolling window Granger causality method to explore the dynamic causal nexus between China’s renewable energy consumption (REC) and climate policy uncertainty (CPU). From the perspectives of digitalization, energy development and technological innovation, empirical outcomes confirm that CPU exerts time-varying instead of static causal effects and steadily boosts REC expansion. There exists evident asymmetry in the reverse feedback of REC on CPU. Thriving renewable energy development reduces policy uncertainty by validating energy transition feasibility, while traditional energy interest-oriented policy revisions tend to heighten CPU. This study further verifies pronounced temporal heterogeneity in their causal interactions, providing fresh evidence for understanding the linkage between policy uncertainty and green growth. It finally proposes differentiated strategies involving short-term energy structure optimization and long-term climate institutional design to advance stable and resilient energy transition.