A three-level meta-frontier directional distance function approach for carbon emission efficiency analysis in China: convexity versus non-convexity

Abstract

Achieving carbon peaking and carbon neutrality goals is a fundamental requirement for advancing high-quality development in China. Carbon emission efficiency (CEE) indicates the proportion of optimal emissions to actual emissions in the production system, providing a basis for reasonable carbon emission reductions. To facilitate the realisation of China's goals, this paper analyses CEE and the carbon emission reduction potential in China from 2001 to 2020. Considering the heterogeneity of both regions and industries, this paper proposes a three-hierarchy meta-frontier directional distance function (DDF) method to measure CEE under convex and non-convex assumptions of production possibility set (PPS). The empirical results show that the assumption of convex or non-convex axiom on the innermost PPS has a great impact on efficiency distribution, and the distribution of technology gap rate (TGR) is more affected by the selection of convex or non-convex assumption compared with the distribution of CEE. Currently, China's carbon emission efficiency remains low, mostly due to management inefficiency. The primary industry has more advanced emission reduction technologies than the other two industries. The eastern region has a large potential for carbon emission reduction because of its high carbon emission base, despite its high efficiency.

KEYWORDS:

• Data envelopment analysis
• meta-frontier
• non-convexity
• carbon emission efficiency
• carbon peaking and carbon neutrality

Acknowledgments

We thank Professor Kristiaan Kerstens for his feedback and suggestions. The views expressed in this paper are those of the authors and do not necessarily reflect the views of any individual or organisation. All errors are our own.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data that support the findings of this study are available upon request.

Notes

1 https://www.gov.cn/xinwen/2023-02/28/content_5743623.htm

2 The division of provinces under the National Bureau of Statistics of China is as follows (excluding Hong Kong, Macao, and Taiwan): The eastern region includes eleven provinces including Hebei, Beijing, Tianjin, Liaoning, Shandong, Jiangsu, Zhejiang, Fujian, Guangdong, Shanghai, and Hainan; The central region includes eight provinces including Heilongjiang, Jilin, Shanxi, Anhui, Henan, Hubei, Hunan, and Jiangxi; The western region includes twelve provinces in Guangxi, Shaanxi, Gansu, Xinjiang, Ningxia, Qinghai, Sichuan, Chongqing, Yunnan, Guizhou, Inner Mongolia, and Tibet.

3 In Sections 4 and 5, three industries are simplified as industry I, industry II, and industry III for the sake of brevity.

4 The data is available at the following link: http://english.mee.gov.cn/Resources/Reports/soe/SOEE2019/202204/P020220407417638702591.pdf.

Additional information

Funding

This research was funded by National Natural Science Foundation of China under grant numbers   72071067, 72188101, 71871081, 42271293, 72271080, 72271079, and 72371115, and by the Fundamental Research Funds for the Central Universities under grant numbers JS2022ZSPY0024, PA2023GDGP0110, JS2021ZSPY0022, and JZ2021HGQA0207.

Notes on contributors

Ya Chen

Ya Chen is a professor in the School of Economics at the Hefei University of Technology. He has published more than 30 articles, such as European Journal of Operational Research, Transportation Research Part E, Omega, Annals of Operations Research, and Resources, Conservation & Recycling, among others. His current research interests include efficiency and productivity analysis, low-carbon transition and green development, blockchain and FinTech, etc. His research has been supported by the National Natural Science Foundation of China, the Natural Science Foundation of Anhui Province, and the Fundamental Research Funds for the Central Universities, etc.

Yongbin Pan

Yongbin Pan is a master student in the School of Economics at the Hefei University of Technology. He has published articles in Structural Change and Economic Dynamics and Socio-Economic Planning Sciences. His current research interests include data envelopment analysis, energy efficiency, and carbon reduction analysis.

Tao Ding

Tao Ding is an associate professor in the School of Economics at the Hefei University of Technology. He has published more than 30 articles, such as Omega, Annals of Operations Research, and Computers & Industrial Engineering, among others. His current research interests include efficiency and productivity analysis, low-carbon transition and green development, etc. His research has been supported by the National Natural Science Foundation of China, the Natural Science Foundation of Anhui Province, and the Fundamental Research Funds for the Central Universities, etc.

Huaqing Wu

Huaqing Wu is a professor in the School of Economics at the Hefei University of Technology. He has published more than 80 articles in peer-reviewed journals, such as European Journal of Operational Research, Omega, Annals of Operations Research, Mathematical and Computer Modelling, Tourism Economics, Resources, Conservation & Recycling, and Energy Policy, among others. His current research interests include technical efficiency and total factor productivity, industrial organisation efficiency and policy evaluation, economic governance and high-quality development, etc. His research has been supported by the National Natural Science Foundation of China and the Major Project of the National Social Science Foundation of China, etc.

Guangwei Deng

Guangwei Deng is an assistant professor in the department of public administration at the Hefei University of Technology. He received a Ph.D. degree in business management from the Hefei University of Technology in 2020. His research interests include performance evaluation and health care resource allocation.