当代财经 ›› 2024, Vol. 0 ›› Issue (4): 141-152.

• 现代会计 • 上一篇    下一篇

人工智能与企业金融资产配置——来自国家人工智能创新应用先导区的经验证据

冯婉昕   

  1. 上海财经大学 会计学院,上海 200433
  • 收稿日期:2023-09-11 修回日期:2024-01-04 出版日期:2024-04-15 发布日期:2024-04-25
  • 作者简介:冯婉昕,上海财经大学博士研究生,主要从事中国情景下的企业经济行为研究,联系方式15326104217@163.com。
  • 基金资助:
    国家自然科学基金面上项目“国有企业与经济社会可持续发展——基于供应链溢出效应的视角”(72272095); 上海市教育发展基金会和上海市教育委员会“曙光计划”项目“关系性交易、嵌入式承销商与企业债券发行”(20SG35); 上海财经大学研究生创新基金项目“线上销售模式是否会影响上市公司的审计费用?”(CXJJ-2022-303)

Artificial Intelligence and Corporate Financial Asset Allocation: Empirical Evidences from the National AI Innovation and Application Pioneer Zone

FENG Wan-xin   

  1. Shanghai University of Finance and Economics, Shanghai 200433, China
  • Received:2023-09-11 Revised:2024-01-04 Online:2024-04-15 Published:2024-04-25

摘要: 当前,人工智能是我国制造业智能化转型和实体经济发展的重要驱动力。以2011—2021年中国A股制造业上市公司为样本,利用多期DID 模型实证检验了国家人工智能创新应用先导区政策对先导区内制造业企业金融资产配置的影响及其影响机制。研究发现,国家人工智能创新应用先导区政策显著降低了先导区内制造业企业的金融资产配置水平。机制分析发现,国家人工智能创新应用先导区政策提高了制造业企业的全要素生产率和缓解了企业的融资约束,从而抑制了制造业企业的金融资产配置水平。异质性分析发现,当企业人力资本质量较高或资产专用性较低时,国家人工智能创新应用先导区政策对制造业企业金融资产配置的抑制效应更强。经济后果分析发现,国家人工智能先导区政策可增加制造业企业的研发投入。为此,先导区要进一步搭建人工智能创新应用场景,非先导区地区要积极学习先导区的有益经验。

关键词: 人工智能, 金融资产配置, 制造业企业

Abstract: Currently, artificial intelligence (AI) serves as an important driving force for the intelligent transformation of China’s manufacturing industry and the development of the real economy. Taking China’s A-share listed manufacturing companies from 2011 to 2021 as samples, this paper empirically examines the influence of the national AI innovation application pilot zone policy on the financial asset allocation of the manufacturing enterprises within the pilot zones, as well as its underlying mechanisms, by employing a multi-period Difference-in-Differences (DID) model. The results reveal that the national AI innovation pilot zone policy has significantly reduced the level of the financial asset allocation among the manufacturing enterprises within the pilot zones. The mechanism analysis indicates that the policy of the national AI innovation pilot zone has enhanced the total factor productivity of the manufacturing enterprises and alleviated their financial constraints, thereby suppressing the financial asset allocation level of these enterprises. The heterogeneity analysis reveals that the inhibitory effect of the national AI innovation pilot zone policy on the financial asset allocation in the manufacturing sector is stronger when the human capital of enterprises is of higher quality or when asset specificity is lower. The economic consequences analysis reveals that the policy has the potential to increase R&D investments in manufacturing enterprises. Therefore, the pilot zones should further build innovative application scenarios for artificial intelligence, and the non pilot zones should actively learn from the beneficial experiences of the pilot zones.

Key words: artificial intelligence, financial asset allocation, manufacturing companies

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