Spatio-temporal Dynamic Evolution and the Factors Impacting Eco-efficiency in Chengdu-Chongqing Economic Circle

doi:10.5814/j.issn.1674-764x.2022.06.004

Abstract

Abstract:

In response to the 14th National Five-year Plan of China and to better explore new strategies for promoting regional coordinated green development, the eco-efficiency values of Chengdu-Chongqing Economic Circle and the corresponding temporal analysis from 2004 to 2018 were assessed in this paper using the super-SBM model and Markov chain. Meanwhile, the spatial analysis of eco-efficiency was conducted by a geographically weighted regression model. Although eco-efficiency has risen at an increasing rate, the economic development of Chengdu-Chongqing Economic Circle was still ecologically ineffective. This means there is an urgent need to improve the efficiency of resource utilization and promote technological innovation. During the study period, the evolution of the eco-efficiency presented as a “π” shape, and was accompanied by the phenomenon of “club convergence”. There was also a strong tendency for eco-efficiency to maintain the original status quo, which indicates that it lacked sufficient momentum for improvement, so it was difficult to achieve a leapfrog transfer. Spatially, the eco-efficiency was distributed from northwest to southeast in a high-low-high manner. The spatial-temporal differences of eco-efficiency narrowed but the effect of agglomeration was relatively weak and there was a polarization trend. Further investigation suggests that the differences in the development level of urbanization, opening, technology, environmental regulation and advancement of industrial structure led to the spatial differences of eco-efficiency. Each city in the Economic Circle should make every effort to improve eco-efficiency accordingly, and thus to promote the green development of the whole region, so as to lay a foundation for driving the green and coordinated development of the central and western regions.

Key words: super SBM model, Markov chain, spatial and temporal disparities, geographically weighted regression

LI Hongli, CHEN Yunping. Spatio-temporal Dynamic Evolution and the Factors Impacting Eco-efficiency in Chengdu-Chongqing Economic Circle[J]. Journal of Resources and Ecology, 2022, 13(6): 986-998.

Figures/Tables 15

References 34

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Grade 1	Grade 2	Definition of indicators
Inputs	Labor force (I₁)	Number of social employees at the end of the year (10⁴ person)
	Capital (I₂)	The perpetual inventory method was used to calculate the capital stock to measure the capital investment, which is: K_i,t= K_i_,_t_-1(1-δ_i_,_t) + I_i_,_t, where K_i,t and K_i,t_-1 represent the stock of capital of city i in period t and t-1,respectively, δ_i_,_t stands for depreciation rate of city i in period t, and I_i_,_t is the total fixed assets investment of city i in period t (10⁸ yuan)
	Energy resource (I₃)	The consumption of energy, which is converted into 10000 tons of standard coal (10⁴ t)
Desirable outputs	GDP (O₁)	GDP of cities at constant prices from 2004 (10⁸ yuan)
Desirable outputs	Greening coverage (O₂)	The greening coverage rate of built-up area (%)
Undesirable outputs	Index of environmental pollution (UO₁)	Comprehensive index of industrial wastewater, waste gas and solid waste based on the entropy method.

Grade 1	Grade 2	Definition of indicators
Inputs	Labor force (I₁)	Number of social employees at the end of the year (10⁴ person)
	Capital (I₂)	The perpetual inventory method was used to calculate the capital stock to measure the capital investment, which is: K_i,t= K_i_,_t_-1(1-δ_i_,_t) + I_i_,_t, where K_i,t and K_i,t_-1 represent the stock of capital of city i in period t and t-1,respectively, δ_i_,_t stands for depreciation rate of city i in period t, and I_i_,_t is the total fixed assets investment of city i in period t (10⁸ yuan)
	Energy resource (I₃)	The consumption of energy, which is converted into 10000 tons of standard coal (10⁴ t)
Desirable outputs	GDP (O₁)	GDP of cities at constant prices from 2004 (10⁸ yuan)
Desirable outputs	Greening coverage (O₂)	The greening coverage rate of built-up area (%)
Undesirable outputs	Index of environmental pollution (UO₁)	Comprehensive index of industrial wastewater, waste gas and solid waste based on the entropy method.

Variables	Indicators	Definition of Indicators
Explained variable	Eco-efficiency	Based on the previous evaluation—EE
Control variables	Industrial structure	Refer to the calculation method of Fu Linghui (Fu, 2010)—IS
	Technological level	Removal rate of sulfur dioxide—Tech
	Urbanization level	Urban population / Local total population—Urban
	Level of opening	Actual utilization of foreign capital /Local GDP—Open
	Environmental regulation	Expenditure for environmental protection/ local fiscal expenditure—RE

Variables	Indicators	Definition of Indicators
Explained variable	Eco-efficiency	Based on the previous evaluation—EE
Control variables	Industrial structure	Refer to the calculation method of Fu Linghui (Fu, 2010)—IS
	Technological level	Removal rate of sulfur dioxide—Tech
	Urbanization level	Urban population / Local total population—Urban
	Level of opening	Actual utilization of foreign capital /Local GDP—Open
	Environmental regulation	Expenditure for environmental protection/ local fiscal expenditure—RE

Outputs/Inputs	Labor force	Capital	Energy resource
GDP	0.881^*** (0.0000)	0.993^*** (0.0000)	0.959^*** (0.0000)
Greening coverage	0.170^*** (0.0085)	0.221^*** (0.0006)	0.250^*** (0.0001)
Index of environmental pollution	-0.785^*** (0.0000)	-0.548^*** (0.0000)	-0.663^*** (0.0000)