Assessment of electricity productivity in china: Regional differences and convergence

被引：0
作者：
Xie P. [1 ]
Zhai Y. [1 ]
Yang F. [1 ,2 ]
Mu Z. [3 ]
Wang C. [4 ]
机构：
[1] College of Economics and Management, Shanghai University of Electric Power, Shanghai
[2] Zhejiang Electric Transmission and Transformation Engineering Co., Ltd, Hangzhou
[3] State Grid Jiangsu Marketing Service Center (Metrology Center), Nanjing
[4] Beijing Electric Power Transmission and Transformation Co., Ltd, Beijing
来源：
Energy Engineering: Journal of the Association of Energy Engineering | 2021年 / 118卷 / 05期
基金：
中国国家自然科学基金;
关键词：
Convergence; Electricity productivity; Regional differences; Spatial Durbin model;
D O I：
10.32604/EE.2021.014970
中图分类号：
学科分类号：
摘要：
Electricity productivity is regarded as a major assessment indicator in the design of energy saving policies, given that China has entered a “New Normal” of economic development. In fact, enhancing electricity productivity in an all-round way, as is one of the binding indicators for energy and environmental issues, means that non-growth target of total electric energy consumption in the economic development is feasible. The Gini coefficient, Theil index, and Mean log deviation are utilized to measure regional differences in China’s electricity productivity from 1997 to 2016 in five regions, and conditional β convergence is empirically analyzed with the spatial Durbin model. The results show that: (1) China’s electricity productivity is improving, while the overall feature is that the eastern area has a higher efficiency than the western area. (2) The difference in electricity productivity is the smallest in the northeast and the largest in the northwest. Interregional difference plays an important role and is the main cause for the differences. (3) The electricity productivity in China exhibits β convergence, except for the northwest. The positive driving factor is urbanization level (0.0485%), and the negative driving factor is FDI (–0.0104%). Moreover, the urbanization rate (0.0669%), foreign direct investment (0.0960%), and the industrial structure (–0.0769%) have a spatial spillover effect on improving regional electricity productivity. Based on this conclusion, the study provides some recommendations for saving energy policy design in China’s power industry. © 2021, Tech Science Press. All rights reserved.
引用
收藏
页码：1353 / 1374
页数：21
相关论文
共 53 条
  • [1] China statistics yearbook 2001–2017, (2017)
  • [2] Zhou K., Yang S., Shao Z., Energy Internet: The business perspective, Applied Energy, 178, 23, pp. 212-222, (2016)
  • [3] Dong F., Yu B., Pan Y., Examining the synergistic effect of CO2 emissions on PM2.5 emissions reduction: Evidence from China, Journal of Cleaner Production, 223, 7, pp. 759-771, (2019)
  • [4] Chen W., Zhou K. L., Yang S. L., Evaluation of China’s electricity productivity under environmental constraints: A DEA cross efficiency model based on game relationship, Journal of Cleaner Production, 164, 2, pp. 38-44, (2017)
  • [5] Yao L., Chang Y., Energy security in China: A quantitative analysis and policy implications, Energy Policy, 67, 6, pp. 595-604, (2014)
  • [6] Yuan R., Jaao F. D., Rodrigues B. P., Impact of non-fossil electricity on the carbon emissions embodied in China’s exports, Journal of Cleaner Production, 192, 5, pp. 582-596, (2018)
  • [7] Chen X., Wang C., Zhang Y., Pu Y., The simultaneous convergence of energy intensity and economy in China, Journal of Industrial Engineering Management, 30, 3, pp. 216-223, (2016)
  • [8] Jenkins S., Getting to zero carbon emissions in the electric power sector, Energy Joule, 2, pp. 1-12, (2018)
  • [9] Xie P., Gao S., Sun F., An analysis of the decoupling relationship between CO2 emission in power industry and GDP in China based on LMDI method, Journal of Cleaner Production, 211, 8, pp. 598-606, (2019)
  • [10] Xie P., Yang F., Mu Z., Gao S., Influencing factors of the decoupling relationship between CO2 emission and economic development in China’s power industry, Energy, 209, pp. 1-9, (2020)
123456