当代财经 ›› 2026, Vol. 0 ›› Issue (4): 46-60.

• 理论经济·经济增长专题 • 上一篇    下一篇

数据要素对技术创新与产业结构变迁的影响

王弟海a, b, 党燕宇a, b, 徐弘毅a   

  1. 复旦大学 a.经济学院 b.六次产业研究院,上海 200433
  • 收稿日期:2025-11-01 修回日期:2025-12-31 发布日期:2026-04-24
  • 作者简介:王弟海,复旦大学教授,博士生导师,经济学博士,主要从事宏观经济学、收入分配、健康经济学、产业结构变迁和经济增长研究;党燕宇,复旦大学博士研究生,主要从事产业结构变迁和经济增长研究;徐弘毅(通信作者),复旦大学博士研究生,主要从事产业结构变迁和经济增长研究,联系方式20110680012@fudan.edu.cn。
  • 基金资助:
    国家自然科学基金面上项目“经济结构如何影响经济增长:理论机制和经验事实”(72073031); 国家自然科学基金创新研究群体项目“中国经济发展规律与治理机制研究”(72121002)

The Impact of Data Elements on Technological Innovation and Industrial Structure Transformation

Wang Di-hai, Dang Yan-yu, Xu Hong-yi   

  1. Fudan University, Shanghai 200433, China
  • Received:2025-11-01 Revised:2025-12-31 Published:2026-04-24

摘要: 从数据的非竞争性特征视角,基于数据能促进横向技术创新的内生产业结构变迁的理论模型研究表明,数据要素会通过直接的数据创新效应和数据成本效应,以及间接的市场规模效应影响部门技术创新。数据创新效应加强了数据创新弹性更高部门的创新激励,而数据成本效应则削弱了该部门的创新激励,这两种机制共同影响了数据对技术创新的贡献率。数据创新贡献率更高部门的技术进步速度快于数据创新贡献率低的部门,由于两部门产品并非替代品,相对价格效应使得要素流向数据创新贡献率更低的部门。在数据产权由消费者所有的情况下,数据隐私成本会限制数据的交易量,并由此制约数据对技术创新和经济增长的贡献。上述结论意味着政府应当加强数据隐私管理、完善数据产权结构设计并提高公共数据共享建设水平,以便于对已有数据进行深度开发利用。

关键词: 数据要素, 技术创新, 产业结构变迁, 经济增长

Abstract: From the perspective of the non-rivalrous nature of data, and based on the theoretical models of data’s ability to promote horizontal technological innovation in endogenous industrial structural transformation, this paper conducts a study. The findings demonstrate that data factors will influence sectoral technological innovation through direct data innovation effects and data cost effects, as well as indirect market size effects. The data innovation effect strengthens innovation incentives in sectors with higher data innovation elasticity, while the data cost effect weakens these incentives. These two mechanisms jointly determine the contribution rate of data to technological innovation. Departments with higher data innovation contribution rates experience faster technological progress than those with lower rates. Since the products of the two departments are not substitutes, the relative price effect drives factors toward departments with lower data innovation contribution rates. When data ownership is held by consumers, data privacy costs will restrict data transactions, thereby limiting data’s contribution to technological innovation and economic growth. The above conclusion implies that the government should strengthen data privacy management, improve the design of data ownership structures, and enhance the level of public data sharing to facilitate in-depth development and utilization of the existing data.

Key words: data element, technological innovation, industrial structural transformation, economic growth

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