Green and low-carbon industrial transformation is an important support for realizing the goal of"dual carbon"and high-quality economic development.Based on the panel data of 30 provinces in China from 2002 to 2020,this paper uses the super efficiency Epsilon-based Measure(EBM)model and Global Malmquist-lunberge(GML)index to measure the industrial green and low-carbon transformation index and explore its spatial-temporal evolution characteristics.From the perspective of space,the spatial agglomeration characteristics of the industrial green and low-carbon transformation index are significant,and the geographical contiguity has a significantly positive impact on the industrial green and low-carbon transformation.Fur-thermore,this paper uses the spatial β convergence model to evaluate the convergence trend of industrial green and low-car-bon transformation index.The empirical results show that the spatial absolute β convergence and spatial conditional β conver-gence of China's industrial green and low-carbon transformation index are significant.
关键词
工业绿色低碳转型指数/绿色全要素生产率/时空演变特征/空间相关性
Key words
industrial green and low-carbon transformation index/green total factor productivity/spatio-temporal evolution characteristics/spatial correlation
维普
万方数据