首页|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

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

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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.
Artificial Intelligence and Corporate Financial Asset Allocation:Empirical Evidences from the National AI Innovation and Application Pioneer Zone
Currently,artificial intelligence(AI)serves as an important driving force for the intelli-gent transformation of China's manufacturing industry and the development of the real economy.Tak-ing China's A-share listed manufacturing companies from 2011 to 2021 as samples,this paper em-pirically examines the influence of the national AI innovation application pilot zone policy on the fi-nancial asset allocation of the manufacturing enterprises within the pilot zones,as well as its underly-ing mechanisms,by employing a multi-period Difference-in-Differences(DID)model.The results re-veal that the national AI innovation pilot zone policy has significantly reduced the level of the finan-cial asset allocation among the manufacturing enterprises within the pilot zones.The mechanism anal-ysis 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 suppress-ing 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.

artificial intelligencefinancial asset allocationmanufacturing companies

冯婉昕

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上海财经大学会计学院,上海 200433

人工智能 金融资产配置 制造业企业

国家自然科学基金面上项目上海市教育发展基金会和上海市教育委员会"曙光计划"项目上海财经大学研究生创新基金项目

7227209520SG35CXJJ-2022-303

2024

当代财经
江西财经大学

当代财经

CSTPCDCSSCICHSSCD北大核心
影响因子:1.539
ISSN:1005-0892
年,卷(期):2024.(4)
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