Agglomeration Level and Its Influencing Factors of the Power Industry: A Spatial Econometric Analysis Based on Interprovincial Panel in China

Abstract

ABSTRACT The agglomeration of the power industry can not only improve industrial production efficiency but also promote energy structure adjustment, which is of great significance for improving national energy security and environmental protection levels. This paper is based on panel data from 30 provinces in China from 2001 to 2021, using the improved location entropy method to measure the agglomeration level of the power industry. The spatial Durbin model (SDM) is used to empirically test the influencing factors and spatial effects of the agglomeration level of the power industry. Research has found that (1) there is a significant spatial correlation in the agglomeration level of China's power industry, and the agglomeration level of the power industry in a region is influenced by neighboring regions; (2) the industrial structure, economies of scale, and power consumption of this region have a significant positive spatial effect on the level of power industry agglomeration, while the population of this region and factors such as the industrial structure, economies of scale, and power consumption of adjacent regions have a significant negative spatial effect on power industry agglomeration. Based on empirical results, relevant suggestions have been proposed to improve the agglomeration level of China's power industry. Based on empirical results, relevant suggestions have been proposed to improve the agglomeration level of China's power industry.

Keywords

• improve location entropy
• influencing factors
• power industry agglomeration
• provincial panel
• spatial Durbin model