Analysis of regional energy economic efficiency and its influencing factors: A case study of Yangtze river urban agglomeration. (October 2020)

• Record Type: Journal Article
• Authors: Zhong, Zhaoqiang; Peng, Benhong; Xu, Lu; Andrews, Awuah; Elahi, Ehsan
• Is Part Of: Sustainable energy technologies and assessments. Volume 41(2021)
• Publication Date: 2020-10
• Subjects: Energy economic efficiency -- Slack-based model -- Moran index -- Tobit regression model; Renewable energy sources -- Periodicals; Energy development -- Technological innovations -- Periodicals; Electric power production -- Periodicals; Energy storage -- Periodicals; 333.79
• DOI: 10.1016/j.seta.2020.100784
• Languages: English
• ISSNs: 2213-1388

Abstract

Abstract: The current economic development is based on high input and high consumption, which is contrary to the current green development concept. Improving energy economic efficiency is a powerful way to balance economic development and energy consumption. This paper focuses on estimation of energy economic efficiency of Yangtze River Urban Agglomeration (YRUA). The Slack-Based Model (SBM) was used to estimate the energy economic efficiency of each city by using data from 2008 to 2017. Moreover, in order to better explore the constraints of energy economic efficiency improvement, the energy economic efficiency is decomposed into pure technical efficiency and scale efficiency. Combined with Moran index, the spatial distribution characteristics of energy efficiency in urban agglomeration are studied. The Tobit regression model was used to analysis on influencing factors of the energy economic efficiency. The results showed that the energy economic efficiency of the YRUA first declined and then increased overall. Particularly, the economic efficiency of Suzhou and Wuxi has been in the effective state of the evaluation unit, while the energy efficiency of Yangzhou, Taizhou and Zhenjiang is relatively low. From the perspective of its decomposition index, scale efficiency is the main factor restricting the efficiency of energy economy. On the one hand, the energy economic efficiency of urban agglomeration has a certain spatial aggregation, and its spatial distribution is positively correlated. On the other hand, the effect of technological progress on energy economic efficiency is not significant. The industrial structure is negatively correlated with the energy economic efficiency. Therefore, the industrial structure, economic development level and urbanization level can be promoted to improve energy economic efficiency.