Spatial Non-Equilibrium and Its Solidification Effect of China’s Per Capita Transportation Carbon Emissions
Caiquan Bai 1  
,   Ying Kang 2  
,   Ximei Wang 3  
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The Center for Economic Research, Shandong University, Ji’nan 250100, China
School of Economics, Central University of Finance and Economics, Beijing 102206, China
Department of Mathematics, KTH Royal Institute of Technology, SE-100 44, Stockholm, Sweden
Caiquan Bai   

Shandong University, China
Submission date: 2020-02-26
Final revision date: 2020-05-11
Acceptance date: 2020-05-14
Online publication date: 2020-10-16
It is of great significance to understand the spatial non-equilibrium and the solidification degree of transportation carbon emissions, so that differentiated measures can be taken to reduce transportation carbon emissions. Based on China’s provincial data from 2005 to 2015, this article uses the Dagum Gini coefficient to decompose the spatial non-equilibrium of per capita transportation carbon emissions from static viewpoint. The results indicate that the overall spatial non-equilibrium shows a significant downward trend; the intensity of transvariation has had an increased contribution rate year by year since 2008, and replaces the inter-regional differences as the main source of the overall spatial nonequilibrium. Next, Kernel density estimation is employed to analyze the evolution laws of spatial non-equilibrium from dynamic viewpoint. The results show that the per capita transportation carbon emissions in the eastern region are successively higher than those at the national level, and in other regions. Meanwhile, some provinces are concentrated at a low level, while others at a high level. Finally, Markov chains approach is applied to identify the solidification effect of the spatial non-equilibrium. The results indicate that the effect is obvious and the state transitions occur only between adjacent types. Moreover, the solidification effects of the provinces with higher per capita transportation carbon emissions are stronger than those provinces with a lower level.