Estimating the determinants and spatial effects of electricity intensity in China

• Main Authors: Ruijun Duan, Tao Shen, Chunming Li, Naseem Fatima, Muhammad Khalid Anser
• Format: Article
• Language: English
• Published: Elsevier 2021-05-01
• Series: Energy Strategy Reviews
• Subjects: Electricity intensity; Determinants; Spatial autocorrelation; Spatial durbin model; China
• Online Access: http://www.sciencedirect.com/science/article/pii/S2211467X21000377

Due to the continuous growth of China's electricity demand, the efficiency of electricity consumption has drawn great attention. Based on 31 provincial panel data in China from 2004 to 2018, this study uses the spatial autocorrelation test and spatial econometric methods to quantitatively identify the spatial distribution characteristics and the dominating driving factors of the electricity intensity. The results show that China's electricity intensity presents significant spatial dependence and clustering characteristics under different spatial weights, and the agglomeration types in backward areas and developed areas are mainly HH and LL clusters, respectively. According to the results of spatial Durbin model, urbanization have significant effects on reducing electricity intensity within a province, and industrialization, foreign direct investment (FDI) and financial development have the opposite impacts, while the direct effect of trade openness is not significant. Considering the spatial spillover effect, urbanization and financial development are found to significantly reduce electricity intensity in the surrounding provinces, and industrialization has the opposite impact, while the spatial spillover effects of FDI and trade openness are not significant. These conclusions offer some fruitful evidence for differential localized policy making related to reduction in electricity intensity.