Abstract: Currently, data elements have become a key factor driving industrial development. This paper systematically reviews relevant literature on data elements driving industrial development, deeply analyzes the connotation and characteristics of data elements, and interprets the mechanism framework of data elements driving industrial development from three levels: micro-enterprise entities, meso-industrial structure, and macroeconomic environment. It summarizes two mainstream methods for measuring the intensity of the industrial development effect driven by data elements: the econometric model method and the general equilibrium method, and focuses on organizing the statistical measurement practices of data elements involved in the econometric model method. In addition, based on the quasi-natural experiment research on data elements driving industrial development, this paper summarizes institutional arrangements that help exert the industrial empowerment effect of data elements around the agglomeration, circulation, and supply of data elements. In response to the shortcomings of existing research, such as the lack of standards for statistical measurement of data elements, fragmented theoretical systems, and unclear distinction between technical and institutional effects, this paper proposes directions for further expansion of research in the future.

Key words: Data Elements, Industrial Development, Theoretical Mechanism, Effect Measurement

摘要： 本文系统梳理数据要素驱动产业发展的相关文献,深度剖析数据要素的内涵特征,从微观企业主体、中观产业结构和宏观经济环境三个层面解读数据要素驱动产业发展的机制框架,总结测度数据要素驱动产业发展效应强度的两种主流方法——计量模型法和一般均衡法,并重点整理计量模型法中涉及的数据要素统计测度实践。此外,基于数据要素驱动产业发展的准自然实验研究,围绕数据要素的集聚、流通和供给归纳了数据要素产业赋能效应发挥作用的制度安排。针对现有研究存在的数据要素统计测度缺乏标准、理论体系分散、技术效应与制度效应未明确区分等不足,本文提出了未来进一步拓展研究的主要方向。

关键词: 数据要素, 产业发展, 理论机制, 效应测度