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A Study of Total-Factor Energy Efficiency for Regional Sustainable Development in China: An Application of Bootstrapped DEA and Clustering Approach

Yang Li (), An-Chi Liu (), Shu-Mei Wang (), Yiting Zhan (), Jingran Chen () and Hsiao-Fen Hsiao ()
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Yang Li: Department of International Trade, Takming University of Science and Technology, Taipei 11451, Taiwan
An-Chi Liu: College of Business Administration, Fujian Business University, Fuzhou 350016, China
Shu-Mei Wang: Department of Bio-Industry Communication and Development, National Taiwan University, Taipei 10617, Taiwan
Yiting Zhan: New Huadu Business School, Minjiang University, Fuzhou 350108, China
Jingran Chen: New Huadu Business School, Minjiang University, Fuzhou 350108, China
Hsiao-Fen Hsiao: New Huadu Business School, Minjiang University, Fuzhou 350108, China

Energies, 2022, vol. 15, issue 9, 1-13

Abstract: Total-factor energy efficiency (TFEE) is widely used to measure energy efficiency under the data envelopment analysis (DEA) framework, but the efficiencies obtained from DEA are structurally biased upward, and thus TFEE tends to overestimate energy efficiency. This research thus applies the bootstrapped DEA approach to correct the bias of TFEE. Using a dataset consisting of 30 provinces of China in the period 2016–2019, the bootstrapped-based test supports technology with variable returns to scale. The biased-corrected TFEE also indicates that energy consumption on average can be scaled down by 42.36%, rather than the biased value of 19.4%. The bootstrapped clustering partitions provinces into three groups: Cluster 1, with Guizhou as the representative medoid, includes half of the superior coastal provinces in terms of actual energy consumption and TFEE and half of the competitive inland provinces, whereas Cluster 3 outperforms Cluster 2 in terms of TFEE, but the actual energy consumption is higher, with Shandong and Hebei as the representative medoids, respectively. Lastly, empirical results imply that the northeast and central regions need more government attention and resources to practice sustainable development and improve TFEE.

Keywords: regional sustainable development; China; DEA; total-factor energy efficiency; bootstrapped clustering approach (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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