Liu Xiao-Meng, Zhang Ying-Quan
Business School, Jinling Institute of Technology, Nanjing, Jiangsu, 211169, People's Republic of China.
Business School, Nanjing Forestry University, Nanjing, Jiangsu, 210037, People's Republic of China.
Environ Sci Pollut Res Int. 2023 Apr;30(20):57882-57897. doi: 10.1007/s11356-023-26579-0. Epub 2023 Mar 27.
The intelligent city pilot policy is a major measure in China to promote urban development from factor driven and investment driven to innovation driven. Intelligent city construction can effectively coordinate specialized production factors and information sharing mechanism, promote digital information technology innovation, promote smart industry cluster, and expand ecological scenarios of clean industry application, so as to reduce carbon emissions. This paper reveals the internal mechanism of intelligent city construction to promote carbon emission reduction. Based on the quasi-natural experiments carried out in three batches of pilot construction of intelligent cities since 2012, the difference-in-difference model (DID) is used to identify its impact on urban carbon emissions. The research results show that the pilot construction of intelligent cities is conducive to reducing carbon emissions, which is still robust under multiple scenarios such as placebo test and endogenous test. Heterogeneity analysis shows that the pilot policies have a more significant carbon emission reduction effect on the Beijing-Tianjin-Hebei urban agglomeration, non-resource-based cities, and non-old industrial bases. After further quantitative analysis of 917 pilot policy texts based on Simhash algorithm, Jieba word segmentation, and word frequency statistics, it is found that intelligent industry policies reduce carbon emissions by driving data elements agglomeration and optimizing industrial structure, while intelligent government and intelligent people's livelihood policies improve energy efficiency and reduce carbon emissions through green technological innovation. Counterfactual tests using machine learning algorithms show that the later the pilot batch, the better the sustainable carbon emission reduction effect of intelligent city pilot policies.
智慧城市试点政策是中国推动城市发展从要素驱动和投资驱动向创新驱动转变的一项重大举措。智慧城市建设能够有效统筹专业化生产要素与信息共享机制，推动数字信息技术创新，促进智慧产业集群发展，拓展清洁产业应用的生态场景，从而实现碳减排。本文揭示了智慧城市建设促进碳减排的内在机制。基于2012年以来三批智慧城市试点建设所开展的准自然实验，运用双重差分模型（DID）识别其对城市碳排放的影响。研究结果表明，智慧城市试点建设有利于降低碳排放，在安慰剂检验和内生性检验等多种情景下依然稳健。异质性分析表明，试点政策对京津冀城市群、非资源型城市和非老工业基地的碳减排效果更为显著。在基于Simhash算法、结巴分词和词频统计对917份试点政策文本进行进一步定量分析后发现，智能产业政策通过驱动数据要素集聚和优化产业结构来降低碳排放，而智能政府和智能民生政策则通过绿色技术创新提高能源效率并减少碳排放。使用机器学习算法进行的反事实检验表明，试点批次越靠后，智慧城市试点政策的可持续碳减排效果越好。
