Efficient allocation of CO 2 emissions in China: a zero sum gains data envelopment model

Zhang, Miao; Geng, Yong; Sheng, Jichuan

doi:10.1016/j.jclepro.2015.07.035

Cited by 131 publications

(43 citation statements)

References 32 publications

(36 reference statements)

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“…Similar to Li [27], we use the perpetual inventory method to estimate the capital indicators. Combine with the average investment of fixed assets in "12·5" period and the depreciation rate (10.96%), which was calculated by Miao et al [10] to calculate the provincial capital in "13·5" period. The calculation of energy consumption and GDP indicators is based on the above set of four scenarios.…”

Section: Variables and Datamentioning

confidence: 99%

“…However, a large number of studies have indicated that due to great differences in economic scale, resource endowment, industrial structure and energy consumption structure of China's different provinces, there are great differences in carbon intensity among China's provinces [6][7][8][9]. Miao et al [10] found that setting the same emission reduction target may cause the low efficiency of each province. Therefore, it is necessary to allocate the provincial CO 2 emission reduction target according to the actual situation of provincial carbon intensity.…”

Section: Introductionmentioning

confidence: 99%

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Efficiency Allocation of Provincial Carbon Reduction Target in China’s “13·5” Period: Based on Zero-Sum-Gains SBM Model

2017

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Firstly, we introduce the "Zero Sum Gains" game theory into the SBM (Slacks-based Measure) model, and establish the ZSG-SBM model. Then, set up 4 development scenarios for the China's economic system in "13·5" (The Chinese government formulates a Five-Year Planning for national economic and social development every five years, "13·5" means 2016 to 2020.) period through two dimensions as economic growth and energy consumption structure, and make the efficient allocation in provincial level of carbon reduction target by using the above ZSG-SBM model based on the China's overall carbon reduction constraint (18%) which is set in "13·5" planning. Finally, we analyze the provincial development path of low-carbon economy by comparing the economic development status with the allocated result of carbon reduction target. Results show that: After the ZSG-SBM model being applied to the efficiency allocation of carbon emission, the input and output indicators of the 30 provinces realize the effective allocation, and the carbon emission efficiency reaches the efficiency frontier. The equity-oriented administrative allocation scheme of government will bring about efficiency loss in a certain degree, and the efficiency allocation scheme, based on the ZSG-SBM model, fits better with the long-term development requirement of low-carbon economy. On the basis of carbon intensity constraint, the re-constraint of energy intensity will force the provinces to optimize their energy consumption structure, thereby enhancing the overall carbon emission efficiency of China. Sixteen provinces' allocation results of carbon reduction target are above China's average (18%) in "13·5" period, all the provinces should select appropriate development path of low-carbon economy according to the status of their resource endowment, economic level, industrial structure and energy consumption structure.

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Section: Variables and Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Efficiency Allocation of Provincial Carbon Reduction Target in China’s “13·5” Period: Based on Zero-Sum-Gains SBM Model

2017

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“…Pang et al [21] studied the reallocation of carbon emission allowance with regard to all the countries participating in the Kyoto Protocol. Wang et al [22] investigated the regional allocation of CO 2 emissions allowance among Chinese provinces, whereas Miao et al [23] investigated the efficient allocation of CO 2 emissions in China.…”

Section: Carbon Allowance Allocation Based On Efficiencymentioning

confidence: 99%

“…Miao et al [23] researched CO2 emissions allowances among provinces in 2010 in China but did not research CO2 emissions allowances among provinces in 2020 in China. References [24][25][26][27][28][29][30][31][32][33][34][35][36] did not use the ZSG-DEA model and/or did not research the CO2 emissions allowance among provinces in China.…”

Section: Deap2mentioning

confidence: 99%

Forecasting the Allocative Efficiency of Carbon Emission Allowance Financial Assets in China at the Provincial Level in 2020

Zeng

Wang

et al. 2016

Energies

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Abstract:As the result of climate change and deteriorating global environmental quality, nations are under pressure to reduce their emissions of greenhouse gases per unit of GDP. China has announced that it is aiming not only to reduce carbon emission per unit of GDP, but also to consume increased amounts of non-fossil energy. The carbon emission allowance is a new type of financial asset in each Chinese province and city that also affects individual firms. This paper attempts to examine the allocative efficiency of carbon emission reduction and non-fossil energy consumption by employing a zero sum gains data envelopment analysis (ZSG-DEA) model, given the premise of fixed CO 2 emissions as well as non-fossil energy consumption. In making its forecasts, the paper optimizes allocative efficiency in 2020 using 2010 economic and carbon emission data from 30 provinces and cities across China as its baseline. An efficient allocation scheme is achieved for all the provinces and cities using the ZSG-DEA model through five iterative calculations.

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“…Moreover, Wang et al allocated CO 2 emission allowances among China's provinces by 2020 by modifying the model published by Gomes and Lins into a "zero-sum game" evaluation model that considers slack effects [17]. Miao and Sheng treat CO 2 as an undesirable output variable, using a non-radial ZSG-DEA model to allocate CO 2 emissions between different Chinese provinces [18]. Lozano et al analyzed data on pulp and paper enterprises in Sweden using the DEA method in order to explore efficient allocation of CO 2 emissions [19].…”

mentioning

confidence: 99%

Allocative Efficiency of Carbon Emission Allowances among Sectors in China

Chen¹,

He²,

Wang³

2018

Pol. J. Environ. Stud.

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Efficient allocation of CO 2 emissions in China: a zero sum gains data envelopment model

Cited by 131 publications

References 32 publications

Efficiency Allocation of Provincial Carbon Reduction Target in China’s “13·5” Period: Based on Zero-Sum-Gains SBM Model

Efficiency Allocation of Provincial Carbon Reduction Target in China’s “13·5” Period: Based on Zero-Sum-Gains SBM Model

Forecasting the Allocative Efficiency of Carbon Emission Allowance Financial Assets in China at the Provincial Level in 2020

Allocative Efficiency of Carbon Emission Allowances among Sectors in China

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