Journal
JOURNAL OF CLEANER PRODUCTION
Volume 259, Issue -, Pages -Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2020.120902
Keywords
Data envelopment analysis (DEA); LMDI; Scale economy; Regional heterogeneity
Categories
Funding
- Ministry of Education of China [10JBG013]
- Shanghai Tongji Gao Tingyao Environmental Science & Technology Development Foundation (STGEF)
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The industrial sector is a pillar for China's economy, improving the energy productivity is of great significance to mitigate the discrepancy between energy use and energy supply, as well as the economic development and environmental friendliness. This paper extended the previous decomposition method by introducing six new components: energy/output-oriented regional efficiency, energy/output-oriented scale economy, energy/output-oriented pure technical efficiency. These new factors can uncover the impacts of regional balance development, scale economy optimization, and resource allocation efficiency change on energy productivity. The main research results indicate that during the 2000-2016 period: (1) industrial energy productivity yield progressively increased, and the discrepancies of energy productivity in different regions were obvious: eastern region represented the best energy productivity performance, followed by the central and western regions. (2) Technological progress in both energy-saving and production were two principal contributors to energy productivity growth. Overall, the pure technical efficiency also promoted energy productivity, suggesting that resource allocation efficiencies were performed well in both the energy market and the output market. (3) By contrast, both the energy and output-oriented scale economy effect failed to promote energy productivity growth. Besides, the energy-oriented and output-oriented regional efficiency had opposite impacts on energy productivity: the former one had the inhibiting effects while the last one had the promoting effects. Finally, several relevant suggestions for policymakers were provided. (C) 2020 Elsevier Ltd. All rights reserved.
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