Biased allocation of emission reduction target constraints and urban green competitiveness

The biased allocation of emission reduction target constraints quantifies emission reduction responsibilities and reflects differences in pollutant reductions both across and within cities. This approach represents a systematic innovation aims to enhance China’s green competitiveness and facilitate its economic transformation through localized and precise policymaking. Using panel data from 275 Chinese cities spanning 2000–2022, this study applies the difference-in-differences method to estimate the impact of biased allocation of emission reduction target constraints on urban green competitiveness. The findings indicate that such constraints—whether based on chemical oxygen demand or sulfur dioxide targets—significantly improve urban green competitiveness, with both pollutant-specific constraints producing comparable effects. Furthermore, these constraints exhibit significant spatial spillover effects within a 200-km geographical radius. Heterogeneity analysis reveals stronger policy impacts in resource-based cities, eastern regions, and cities designated as key areas for pollution prevention and control. Mechanism analysis demonstrates that the constraints enhance green competitiveness primarily by fostering green technological innovation and optimizing industrial structures. These conclusions provide a practical foundation for addressing China’s enduring conflict between environmental protection and economic development.