The Assessment of Carbon Performance under the Region-Sector Perspective based on the Nonparametric Estimation: A Case Study of the Northern Province in China

Xian’En Wang, Shimeng Wang, Xipan Wang, Wenbo Li, Junnian Song, Haiyan Duan and Shuo Wang
Additional contact information
Xian’En Wang: School of New Energy and Environment, Jilin University, Qianjin Street 2699, Changchun 130012, China
Shimeng Wang: School of New Energy and Environment, Jilin University, Qianjin Street 2699, Changchun 130012, China
Xipan Wang: School of New Energy and Environment, Jilin University, Qianjin Street 2699, Changchun 130012, China
Wenbo Li: School of New Energy and Environment, Jilin University, Qianjin Street 2699, Changchun 130012, China
Junnian Song: School of New Energy and Environment, Jilin University, Qianjin Street 2699, Changchun 130012, China
Haiyan Duan: School of New Energy and Environment, Jilin University, Qianjin Street 2699, Changchun 130012, China
Shuo Wang: School of New Energy and Environment, Jilin University, Qianjin Street 2699, Changchun 130012, China

Sustainability, 2019, vol. 11, issue 21, 1-23

Abstract: China is the largest emitter of carbon dioxide (CO 2 ) in the world, and the Chinese government has accordingly proposed a series of measures to achieve a low-carbon economy. Due to the low carbon emission performance (CEP) and the high industry portion of the northern provinces in China, evaluating the CEPs of industrial sectors in northern China is necessary. By considering the different CEP assessments in regional and industrial research, a dual-perspective assessment of CEP was presented to narrow the gap between the regional and industrial perspectives. The dual model of slack-based measure (SBM) and data envelopment analysis (DEA) was combined with the global Malmquist–Luenberger index (GMLI) proposed to measure the static CEP and the dynamic change of the CEP of six provinces in northern China from 2006–15 for the regional and industrial perspectives, respectively. A comparison of the results under the different perspectives proved the irrationality of our evaluation under the sole perspective. For example, for Jilin Province, the CEPs of Mining and Processing of Nonmetal and Other Ores (Sector 4) ranked in the top 30% in the regional perspective. However, in the industrial level, the CEPs of Mining and Processing of Nonmetal and Other Ores (Sector 4) ranked lower. The CEPs of the Production and Supply of Electric Power and Heat Power (Sector 20) of Heilongjiang Province ranked in the bottom 30% in a regional perspective but ranked first at the industrial level. We also found the advantage sectors in the CEP under the region–sector dual perspective. For example, for Jilin Province, the Processing of Petroleum, Coking, and Processing of Nuclear Fuel (Sector 10) and the manufacture of Transport Equipment (Sector 16) were the advantageous sectors. The dual-perspective assessment aimed to evaluate the CEP under diverse views. It also provided a more reliable path to reduce CO 2 emissions for managers and regulators.

Keywords: dual-perspective; regional assessment; industrial evaluation; SBM (slack-based measure) model; GMLI (global Malmquist–Luenberger index); the northern province of China (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.mdpi.com/2071-1050/11/21/6031/pdf (application/pdf)
https://www.mdpi.com/2071-1050/11/21/6031/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:11:y:2019:i:21:p:6031-:d:281784

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().