Spatial Convergence of Carbon Productivity: Theoretical Analysis and Chinese Experience

Abstract

Based on the neoclassical framework, we propose the convergence hypothesis of carbon productivity under sustainable growth and prove the different effects of knowledge spillover and technology diffusion on convergence. The convergence hypothesis is tested using China’s provincial spatial dynamic panel data from 1995 to 2019. The results show that China’s provincial carbon productivity has conditional convergence and club convergence characteristics. The convergence speed of dynamic panel regression estimation is greater than that of cross-sectional regression. The convergence rate of dynamic spatial panel regression estimation is faster depending on the spatial spillover difference between the two technologies. In the early stage, the provincial spatial dependence of China’s carbon productivity is mainly knowledge spillover, and the convergence rate is lower than that of the closed economy. Over the past decade, the spatial spillover, dominated by low-carbon technology diffusion, has become the dominant force. The convergence rate is significantly faster than that of a non-spatial-dependent economy. In addition, the mechanism test found that the development of energy efficiency dominates the spatial transfer of technology, so the overall convergence of carbon productivity in China mainly comes from the apparent convergence of energy efficiency in provinces and cities. Our conclusion provides a new reference for the emission reduction actions of countries worldwide because the spatial knowledge spillover carried by capital flows is not conducive to the pursuit of carbon productivity in less developed regions. On the contrary, the dissemination and diffusion of low-carbon technologies can significantly reduce carbon equivalent input in the production process, accelerating the pursuit of developing countries or regions.

Spatial Differences and Influential Factors of Urban Carbon Emissions in China under the Target of Carbon Neutrality

“…The consumption of fossil energy is the primary source of CEs in Chinese cities. Drawing on previous studies [ 44 , 45 ], we used the consumption data of 15 energy resources from 264 cities at the prefecture level to calculate the CEs. The data on energy consumption by cities were derived from the statistical yearbook of each city ( , accessed on 17 January 2022), which Chinese government departments provide with authority and credibility.…”

The Spatial Differentiation and Driving Forces of Ecological Welfare Performance in the Yangtze River Economic Belt

“…Third, some scholars have investigated the evolution of resource allocation efficiency, green total factor productivity and carbon emission rate from the perspective of spatial convergence [ 40 , 41 , 42 ], but few scholars use spatial convergence models to study the differences in EWP. By constructing a spatial panel Durbin convergence model, this study proposes and verifies the difference in the convergence rate of the EWP and the main influencing factors in the upstream, midstream and downstream of the YREB.…”

“…Further, most of these methods are considered static models as they are incapable of revealing temporal trends of the associations between EWP and causal factors. The spatial convergence model (SCM) is used on the basis of spatial angles for investigating the differentiated causes of the associations among different regions and their convergence trends [ 40 , 41 , 42 ]. Therefore, this research builds a spatial Durbin convergence model which incorporates the spatial impacts.…”