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中南大学学报(社会科学版)
ZHONGNAN DAXUE XUEBAO(SHEHUI KEXUE BAN)

2024年11月第30卷第6期
   
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文章编号:1672-3104(2024)06-0104-15
 
人工智能对实体经济融资效率的影响研究:理论机制与实证检验
 
陈劲1, 2,彭刚东1,韩卫冬3,张吉森4
 
(1. 清华大学经济管理学院,北京,100084;
2. 清华大学技术创新研究中心,北京,100084;
3. 重庆市税务局,重庆,401121;
4. 中国人民银行湖北省分行神农架林区营业管理部,湖北神农架,442400)
 
摘  要: 实体企业的融资效率是衡量实体经济发展质量的关键指标,对企业经营具有深远影响。从融资成本、融资收益和融资风险三个方面构建融资效率评估指标,选取2000—2022年中国上市公司的数据,探讨了人工智能对实体经济融资效率的影响及其作用机制。研究发现,人工智能显著提升了实体企业的融资效率,即便在采用工具变量2SLS、动态面板-系统GMM等方法控制内生性问题后,这一结果依然保持稳健。机制分析表明,人工智能能够通过降低资金供需双方的信息不对称、缓解企业融资约束以及加剧企业间的竞争,提高实体经济的融资效率。异质性分析表明,人工智能对东部地区实体企业融资效率的影响较为显著,而对西部、中部及东北地区实体企业融资效率的影响则不明显;根据企业所有制属性进一步分组研究发现,人工智能对实体企业融资效率的影响均显著为正,但对民营企业的作用效果相对较弱。
 
关键词: 人工智能;实体经济;融资效率;信息不对称
 
 
The impact of artificial intelligence on the financing efficiency of the real economy: Theoretical mechanism and empirical test
 
CHEN Jin1, 2, PENG Gangdong1, HAN Weidong3, ZHANG Jisen4
 
(1. School of Economics and Management, Tsinghua University, Beijing 100084, China;
2. Research Center for Technological Innovation, Tsinghua University, Beijing 100084, China;
3.Chongqing Taxation Bureau, Chongqing 401121, China;
4. Shennongjia Forest District Business Management Department, Hubei Province Branch, People's Bank of China, Shennongjia 442400, China)
 
Abstract: The financing efficiency of physical enterprises is a key indicator for measuring the quality of real economic development and has a profound impact on business operations. By constructing an evaluation index for financing efficiency from such three aspects as financing costs, financing benefits, and financing risks, and by selecting data from Chinese listed companies from 2000 to 2022, this paper explores the impact of artificial intelligence on the financing efficiency of the real economy and its mechanism of action. The study finds that artificial intelligence significantly enhances the financing efficiency of physical enterprises, and this result remains robust even after controlling for endogeneity issues using instrumental variable 2SLS and dynamic panel-system GMM methods. Mechanism analysis indicates that artificial intelligence can improve the financing efficiency of the real economy by reducing information asymmetry between capital providers and capital demanders, alleviating corporate financing constraints, and intensifying competition among enterprises. Heterogeneity analysis shows that the impact of artificial intelligence on the financing efficiency of physical enterprises in the eastern region is more significant, while its impact on the financing efficiency of physical enterprises in the central, western, and northeastern regions is not apparent. Further subgroup analysis based on enterprise ownership attributes reveals that the impact of artificial intelligence on the financing efficiency of physical enterprises is significantly positive, while its effect on private enterprises is relatively weaker.
 
Key words: artificial intelligence; real economy; financing efficiency; information asymmetry
 
 
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