Kun Zhang , Zi-Xuan Kou , Pei-Hua Zhu , Xiang-Yan Qian , Yun-Ze Yang
{"title":"How does AI affect urban carbon emissions? Quasi-experimental evidence from China's AI innovation and development pilot zones","authors":"Kun Zhang , Zi-Xuan Kou , Pei-Hua Zhu , Xiang-Yan Qian , Yun-Ze Yang","doi":"10.1016/j.eap.2024.12.013","DOIUrl":null,"url":null,"abstract":"<div><div>Artificial intelligence (AI) is gradually becoming an important engine for empowering urban economies, driving the low-carbon growth of cities. To promote the deep integration of AI with economic and social expansion, China has proposed building national new-generation AI innovation and development pilot zones (AIPZ) in cities. However, the impact of AIPZ construction on low-carbon development remains unclear. Using panel data from 276 cities in China from 2015 to 2022, we employed a difference-in-differences method to assess the impact of the AIPZ policy on urban carbon emissions (UCE). First, as verified by multiple robustness tests, the AIPZ policy effectively reduced UCE, with an average reduction of 3.4 %. Second, the policy helped lower urban pollutant emissions and achieved a synergistic effect of carbon and pollution reduction. Third, according to the mechanism analysis, the AIPZ policy promoted carbon reduction by optimizing the government spending structure and improving consumers’ online lifestyles. Additionally, the economic effect analysis revealed that the AIPZ policy reduced UCE by optimizing industrial structure, enhancing energy efficiency, and promoting technological innovation. Therefore, this study verifies the positive role of AI in reducing UCE and provides policy support for leveraging AI to promote green and low-carbon urban development.</div></div>","PeriodicalId":54200,"journal":{"name":"Economic Analysis and Policy","volume":"85 ","pages":"Pages 426-447"},"PeriodicalIF":7.9000,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Economic Analysis and Policy","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0313592624003515","RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0
Abstract
Artificial intelligence (AI) is gradually becoming an important engine for empowering urban economies, driving the low-carbon growth of cities. To promote the deep integration of AI with economic and social expansion, China has proposed building national new-generation AI innovation and development pilot zones (AIPZ) in cities. However, the impact of AIPZ construction on low-carbon development remains unclear. Using panel data from 276 cities in China from 2015 to 2022, we employed a difference-in-differences method to assess the impact of the AIPZ policy on urban carbon emissions (UCE). First, as verified by multiple robustness tests, the AIPZ policy effectively reduced UCE, with an average reduction of 3.4 %. Second, the policy helped lower urban pollutant emissions and achieved a synergistic effect of carbon and pollution reduction. Third, according to the mechanism analysis, the AIPZ policy promoted carbon reduction by optimizing the government spending structure and improving consumers’ online lifestyles. Additionally, the economic effect analysis revealed that the AIPZ policy reduced UCE by optimizing industrial structure, enhancing energy efficiency, and promoting technological innovation. Therefore, this study verifies the positive role of AI in reducing UCE and provides policy support for leveraging AI to promote green and low-carbon urban development.
期刊介绍:
Economic Analysis and Policy (established 1970) publishes articles from all branches of economics with a particular focus on research, theoretical and applied, which has strong policy relevance. The journal also publishes survey articles and empirical replications on key policy issues. Authors are expected to highlight the main insights in a non-technical introduction and in the conclusion.