| Summary/Abstract |
Understanding the convergence patterns of energy intensity and the drivers leading to the club convergence are of great significance for local governments to implement targeted policies to improve energy efficiency. With this in mind, we begin with the collection of energy consumption data of 193 Chinese cities at prefecture level or above, then we adopt the log t-test and clustering algorithm to investigate convergence characteristics of energy intensity. Besides, the Ordered Probit model is adopted to investigate the drivers that affect the formulation of convergent club. We identify four convergent clubs among total 193 cities, and these clubs show great differences in energy intensity. Marketization degree, population density, foreign direct investment, resource endowment, and industrial structure are recognized as the drivers of the formation of convergence clubs. This paper adds more evidence to understand the energy intensity gap, we propose that upgrading the industrial structure, exerting economic assemble advantage, enhancing the level of opening up, and improving the marketization level are favorable measures to reduce energy intensity.
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