The impact assessment of low-carbon city pilot policy on urban green innovation: A batch-time heterogeneity perspective

• Published in: Applied energy Vol. 377; p. 124489
• Main Authors: Liu, Kui, Huang, Tao, Xia, Zheyi, Xia, Xingneng, Wu, Rongrong
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.01.2025
• Subjects: Green innovation; Heterogeneous causal inference; Low-carbon city; Spatial competition; The batch-time heterogeneity; Urban characterization; Urban characterization; The batch-time heterogeneity; Spatial competition; Low-carbon city; Green innovation; Heterogeneous causal inference
• ISSN: 0306-2619
• DOI: 10.1016/j.apenergy.2024.124489

The Chinese government is actively implementing the Low Carbon City Pilot (LCCP) policy nationwide to fulfill its commitment to carbon peaking and carbon neutrality. One of the main objectives of the LCCP policy is to enhance green innovation in cities, and many publications have assessed its effectiveness. While previous studies have considered differences in city characteristics, they have not adequately analyzed the varying effects of LCCP policy on different batches of pilot cities. To address this gap, this study utilized a cutting-edge heterogeneity causal inference approach to evaluate the heterogeneity of LCCP policy effects across different batches. The findings indicate that the LCCP policy significantly promoted urban green innovation and green substantive innovation. However, its impact on green symbolic innovation was not statistically significant. Among the different batches of pilot cities, the second batch was most strongly affected by the LCCP policy, followed by the third batch. Further analysis reveals that the initial group of pilot cities, with their varying innovation capabilities, carbon emission levels, and government intervention, along with the negative spatial competition among the cities, resulted in a less effective implementation of the LCCP policy compared to the second and third batches. This study contributes to a more accurate assessment of the effectiveness of the LCCP policy by highlighting the heterogeneity across different batches. We recommend that cities committed to low-carbon growth through green innovation customize the design and implementation of their low-carbon policies and establish broader networks of city-to-city cooperation. •A heterogeneous causal inference method is used to estimate the effects of LCCP.•LCCP significantly contributes to urban green innovation.•The effects of LCCP on urban green innovation are batch-time heterogeneous.•The second batch of cities is the most affected, and the first batch the least.•Urban characteristics and spatial competition led to the batch-time heterogeneity.