The evolution and determinants of Chinese inter-provincial green development efficiency: an MCSE-DEA-Tobit-based perspective

Yang, Lin; Ma, Zaitian; Yin, Jie; Li, Yiming; Lv, Haodong

doi:10.1007/s11356-023-25894-w

Cited by 9 publications

(5 citation statements)

References 46 publications

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“…The remaining three provinces (Gansu, Ningxia, and Qinghai) have a lower level of CEE than other provinces located in Western China. This may be due to their relatively backward economic development level, production technology, and limited capital investment [76], resulting in low CEE levels. 0.713 in 2019.…”

Section: Calculation Results Of Ceementioning

confidence: 99%

What Are the Impacts of Urbanisation on Carbon Emissions Efficiency? Evidence from Western China

Yang,

Liang,

Yao

et al. 2023

Land

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The contributions of this research are making the theoretical analysis of the impact mechanism of urbanisation on carbon emissions efficiency (CEE), and then empirically analysing the effects of urbanisation on CEE in Western China from 2010 to 2019 by applying the epsilon-based measure model with undesirable outputs and the Tobit model. Major findings are: (1) The mean CEE of the 11 western provinces show a trend of declining and then increasing over those 10 years, demonstrating U-shaped change characteristics. (2) The CEE of Guangxi has the most significant decrease, while the CEE of Chongqing showed only a small fluctuation; the CEE of Guizhou has the characteristic that first it rises, then descends, then rises again; the CEEs of Inner Mongolia and Yunnan have been in the production frontier surface from 2010 to 2015, and presents the trend of declining, then increasing after 2015. The CEEs of the other six western provinces present a trend of declining, then increasing. (3) Chongqing, Sichuan, Inner Mongolia, and Yunnan have a high level of CEE, followed by Shaanxi, Xinjiang, Guangxi, and Guizhou, with an intermediate level of CEE, and Gansu, Ningxia, and Qinghai, with the lowest level of CEE. (4) The effects of urbanisation on CEE in Western China present a U-shaped relationship, meaning that the process of influence was first inhibition, then stimulation. At present, the process of urbanisation shows negative impacts on the CEE, while the tipping point has not yet arrived. The western provinces of China should follow the path of high-quality urbanisation to quickly shift the impact of urbanisation on CEE to the right side of the U-shaped curve.

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Section: Calculation Results Of Ceementioning

confidence: 99%

What Are the Impacts of Urbanisation on Carbon Emissions Efficiency? Evidence from Western China

Yang,

Liang,

Yao

et al. 2023

Land

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“…The productivity of green total factor aims to reflect the resource and environmental losses in a regional development through the consideration of resource and environmental costs. It is an effective measurement indicator for regional green development and is widely used in the field of regional green development evaluation (Tian and Feng 2023, Yang et al 2023a, Yu 2023). In the selection of efficiency measurement indicators, scholars pay more attention to the input indicators such as human resources, capital, energy and technological innovation, together with the output indicators such as economic benefits, social benefits and environmental damage.…”

Section: Literature Reviewmentioning

confidence: 99%

Research on green development measurement and regional differences in the China's Yellow River Basin based on the ecological function orientation

Ma,

Dong,

Yao

et al. 2024

Environ. Res. Commun.

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The ecological protection and high-quality development of the Yellow River Basin have become a national strategy. This study takes 57 cities in the Yellow River Basin as research samples, employs the green total factor productivity (GTFP) to characterizes the level of green development, introduces an improved mixed distance (MEBM) Windows model and an algorithm containing the background differences to measure the level of green development, and further uses the Dagum Gini coefficient to analyze the regional differences. It shows that the level of green development of Yellow River Basin exhibits a downward trend during the study period when the ecological function orientation (EFO) is not considered, however, the downward trend is significantly narrowed when the EFO is considered, and 91.23% of the sample rankings is changed. According to these results, the study samples are divided into three types: the controlled development zones, the moderate development zones, and the transition development zones. The inter-regional differences are the main factors that causes the regional differences in the green development of Yellow River Basin. Based on the results, we propose the relevant policy recommendations that can provide a decision-making basis for promoting the ecological protection and high-quality development in the Yellow River Basin according to the local conditions.

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“…① Environmental regulation level (Er i,t ): Referring to Li and Tao (2012) and Yang (2015), the level of environmental regulation is measured by the actual investment in environmental pollution control in each province. ② Energy consumption structure (Ec i,t ): Considering that energy consumption has a direct impact on carbon emissions (Chen and Li, 2021), this paper measures the energy consumption structure of the service industry by the ratio of the energy consumption and CO 2 emissions of the service industry in each province, referring to the index construction method of Liu (2015).…”

Section: Control Variablesmentioning

confidence: 99%

Research on the impact of technical progress on the carbon productivity in China’s service industry

Zhen-qiu

Huang

et al. 2023

Front. Environ. Sci.

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The energy consumption and carbon emission of the service industry should not be ignored. In order to achieve green and low-carbon development, improving the carbon productivity of the service industry is an extremely important method, and technical progress is a key path to improving the carbon productivity of the service industry. This paper decomposes the technical progress of China’s service industry into technical progress of non-energy factors and technical progress of energy factor, and analyzes the impact and action mechanism of these two technical progress on the carbon productivity of China’s service industry respectively from the theoretical and empirical perspectives. The main conclusions of this paper are as follows: From 2003 to 2019, technical progress had a significant positive impact on the carbon productivity of China’s service industry. The influence coefficients of technical progress of non-energy factors and technical progress of energy factor are 0.285 and 0.306. In terms of the type of technical progress, the technical progress of energy factor has a greater impact. The technical progress of non-energy factors and energy factor have a significant promoting effect on the improvement of carbon productivity of service industry in all regions of China. In Eastern, central and Western China, the influence coefficients of the former are 0.318, 0.289 and 0.266, and the influence coefficients of the latter are 0.352, 0.296 and 0.273. The mechanism test finds that the technical progress of non-energy factors and energy factor directly affect the carbon productivity of China’s service industry on the one hand, and indirectly affect the carbon productivity of China’s service industry through the production efficiency and energy use efficiency of the service industry on the other hand.

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The evolution and determinants of Chinese inter-provincial green development efficiency: an MCSE-DEA-Tobit-based perspective

Cited by 9 publications

References 46 publications

What Are the Impacts of Urbanisation on Carbon Emissions Efficiency? Evidence from Western China

What Are the Impacts of Urbanisation on Carbon Emissions Efficiency? Evidence from Western China

Research on green development measurement and regional differences in the China's Yellow River Basin based on the ecological function orientation

Research on the impact of technical progress on the carbon productivity in China’s service industry

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