A panel empirical modeling on the driving factors of provincial electricity consumption in China

Abstract

This study aims to explore the relationships between electricity consumption and per capita GDP, urbanization rate, and the proportion of tertiary industry in China during 2005-2018. The results demonstrate that electricity consumption and its determinants are cointegrated. Then fully modified ordinary least square (FMOLS) and fixed effect with varying coefficients and intercept techniques are used to explore the relationships. The empirical results show that all three factors positively affect electricity consumption, per capita GDP has exerted positive impacts on electricity consumption in the 28 provinces, urbanization rate also contributes a positive influence on electricity consumption in 29 provinces, while the positive effect of the proportion of tertiary industry emerges only in 10 provinces. Meanwhile, the urbanization rate makes the most considerable contribution to electricity consumption, while the proportion of the tertiary industry is the least essential determinant. The panel causality results reveal that per capita GDP and urbanization rate cause electricity consumption in the short run and per capita GDP and electricity consumption Granger cause each other in the long run. Finally, we propose policy implications including enhancing the security and reliability of power supply and optimizing the structure of electricity consumption in different industries in China.

Keywords: China; Driving factors; Panel data model; Provincial electricity consumption.