Understanding the overall difference, distribution dynamics and convergence trends of green innovation efficiency in China’s eight urban agglomerations

Abstract

Based on adopting the global super-efficiency slacks-based measure (GSSBM) model to calculate green innovation efficiency (GIE), this paper systematically investigates GIE’s overall difference, distribution dynamics and convergence trends in eight national urban agglomerations (UAs) of China from 2004 to2018 by combining the methods of Dagum Gini Coefficient (DGC), Kernel Density Estimation (KDE), Variation Coefficient (VC), fixed-effect model (FEM) and spatial Durbin model (SDM). The results show that: (1) the average GIE of eight UAs was 0.632 during 2004–2018, which is generally low and has substantial potential for improvement, and seven of them achieved positive growth with an annual average growth rate of 2.70%. (2) The overall difference of GIE within eight UAs was significant with the inter-UA difference as the main contributor. (3) The distribution curves of GIE in eight UAs were distinct in terms of location, form, ductility and polarization trend. (4) Besides five UAs presenting significant σ convergence characteristics, all eight UAs displayed significant absolute or conditional β convergence trends with different speeds and cycles. The findings of this paper can provide important insights on the promotion of green innovation-driven development for UAs in China.

Keywords

• Green innovation efficiency
• Urban agglomeration
• Overall difference
• Distribution dynamic
• Convergence trend