Impact of policies on wind power innovation at different income levels: Regional differences in China based on dynamic panel estimation

Based on the expanded two-factor learning curve and adopting dynamic panel methods, we explored the driving effects of policies and policy interaction on wind power technology innovation (TIW) at different developmental levels using panel data for the period 2006–2017 in 29 provinces in China. To reveal regional heterogeneity, we classified the 29 Chinese provinces into two regions based on the 2017 per capita gross domestic product. The results indicated that public research and development policy plays the most significant role in driving TIW for all samples. We only confirmed the positive interaction effect of policies for middle-income provinces (Region 2). Additionally, the learning-by-doing effect for TIW in China was identified, though the magnitude of that effect was much smaller than that of the learning-by-searching effect. Finally, the regional differences in the impacts of different policy instruments provide new insights for future policy design to effectively promote TIW.