Reducing energy mismatch in Chinese cities: Can low carbon transition work?

Abstract

As central objectives in China's urban high-quality development, facilitating the socioeconomic low-carbon transition (LCT) and optimizing energy allocation efficiency constitute dual imperatives for sustainable growth. This study integrates the dynamic spatial Durbin model (DSDM) with panel threshold regression analysis to systematically investigate the spatial spillover and nonlinear threshold effects of LCT on energy mismatch by using a balanced panel dataset from Chinese cities. Our multiscale analysis yields three pivotal findings: (1) LCT not only significantly reduces energy mismatch but also generates notable spatial spillover effects. (2) In resource-based cities, centrally administered municipalities, eastern Hu Line regions, and northern China cities, LCT significantly reduces energy mismatch locally while generating positive spatial spillover effects. Energy mismatch also exhibits significant spatial spillover and temporal lag effects. (3) Threshold effect analysis reveals dual threshold characteristics, with industrial structure optimization (ISO) and industrial structure upgrading (ISU) displaying significant nonlinear relationships between LCT and energy mismatch. Only by reaching a certain threshold can LCT significantly reduce energy mismatch. These findings contribute to the energy economics literature by establishing a spatiotemporal analytical framework for improving energy efficiency, while providing empirical insights for differentiated policy design across city clusters.