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Provincial Carbon Emissions Efficiency and Its Influencing Factors in China

Shi Wang (), Hua Wang (), Li Zhang () and Jun Dang ()
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Shi Wang: School of Economics and Finance, Xi’an International Studies University, Xi’an 710128, China
Hua Wang: School of Foreign Studies, Xi’an Jiaotong University, Xi’an 710049, China
Li Zhang: School of Journalism and New Media, Xi’an Jiaotong University, Xi’an 710049, China
Jun Dang: School of Economics and Finance, Xi’an International Studies University, Xi’an 710128, China

Sustainability, 2019, vol. 11, issue 8, 1-21

Abstract: We calculated provincial carbon emissions efficiency and related influencing factors in China with the purpose of providing a reference for other developing countries to develop a green economy. Using panel data covering the period from 2004–2016 from 30 provinces in China, we calculated the carbon emission performance (CEP) and the technology gap ratio of carbon emission (TGR) with the data envelopment analysis (DEA) method and the meta-frontier model separately to analyze provincial carbon emissions efficiency in China. No matter which indicator was employed, we found that distinct differences exist in the eastern, the central, and the western regions of China, and the eastern region has the highest carbon emission performance, followed by the central and the western regions. Then, the panel data Tobit regression model was employed to analyze the influencing factors of carbon emissions efficiency, and we found that scale economy, industrial structure, degree of opening up, foreign direct investment (FDI), energy intensity, government interference, ownership structure, and capital-labor ratio have different impacts on the carbon emission efficiency in different regions of China, which indicates different policies should be implemented in different regions.

Keywords: carbon emissions efficiency; carbon emissions performance (CEP); technology gap ratio of carbon emissions (TGR); meta-frontier data envelopment analysis (DEA) model (search for similar items in EconPapers)
JEL-codes: Q Q0 Q2 Q3 Q5 Q56 O13 (search for similar items in EconPapers)
Date: 2019
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