Dynamic changes and convergence of China's regional green productivity: A dynamic spatial econometric analysis

Abstract

Low-carbon economic development is at the heart of the post-pandemic green recovery scheme worldwide. It requires economic recovery without compromising on the environment, implying a critical role that green productivity plays in achieving the carbon neutrality goal. Green productivity measures the quality of economic growth with consideration for energy consumption and environmental pollution. This study employs the slacks-based measure directional distance function (SBM-DDF) approach and the Malmquist-Luenberger (ML) index to calculate green productivity and its components of 30 provinces in China between 2001 and 2018. Using a spatial panel data model, we empirically analyzed the conditional β-convergence of China's green productivity. We found that overall, since 2001, China's green productivity has demonstrated a continuous upward trend. When taking into account spatial factors, China's green productivity demonstrates a significant conditional β-convergence. In terms of regional effects, the results indicate that the green productivity of the eastern and western regions demonstrates club convergence, implying a more balanced green economic development. Moreover, the convergence rate of China's green productivity increases with the addition of environmental regulation variable, and so the corresponding convergence time decreases. It indicates that environmental regulations help to facilitate the convergence of China's green productivity, narrowing the gap between the regional green economic development. The findings provide guideline for achieving a low-carbon development and carbon neutrality from a regional green productivity perspective.