前沿经济理论视野下的数据要素研究进展

数字经济蓬勃发展,数据要素逐渐成为学术和政策讨论的重要议题。数据要素在要素特性、市场化机制、经济价值等方面相对传统生产要素有较大差异,对其研究亟待创新建模思路。经济学理论已经积累不少相关文献。文章着眼于数据要素的特性、市场化机制和经济价值,系统梳理了国内外相关文献,从前沿经济理论文献对数据要素的建模思路入手,进行了全面的总结和分析。首先,从隐私外部性和要素报酬两个角度入手梳理了前沿文献对于数据要素特性的探讨;其次,从数据要素的产权归属和交易机制设计两个层面梳理数据要素市场化相关文献;再次,总结文献中关于数据要素的经济价值和实证评估的研究;最后,列举应用前沿理论研究数据要素的方法创新方向,展望应用经济学理论研究中国数据要素实际问题的潜在思路。文章可为数据要素市场化的理论和政策研究提供一定的理论参考。

Overview of Current Studies on Data Factor

With the fast growth of digital economy, the role data factor played in economy has become the focus of theoretical and practical studies. Data factor is different from traditional production factors in terms of characteristics of the factor, marketization mechanisms and economic value. Studies on data factor rely on innovations in economic modelling. This paper reviews literature on data factor in terms of its characteristics, marketization mechanisms and economic value. We first discuss privacy externality and factor return of the data factor. By listing literature on relevant topics, we find that researchers generally agreed that data factor exhibits privacy externality. There is no consensus on whether data factor shows increasing or decreasing marginal returns. But microeconomic modeling strongly agree that data factor shows increasing returns to scale because of fixed cost on the supply side, network effect on the demand side, and "learning by doing" effect. Macro-economic modelling, by introducing non-rivalry of data, also shows that data factor has increasing returns to scale. But increasing privacy cost may prevent data factor from showing increasing returns to scale. Then, we review literature on the ownership of data factor. By assigning ownership of data factor to consumers or to the firm, the government may achieve different social welfare levels under different settings like incomplete contract, non-rivalry of data, and "creative destruction" effect. We also discuss trading mechanisms of data factor. Scholars have introduced trading mechanisms with the enlightenment from literature on information design, information acquisition, and market design. We introduce relevant literature from the perspective of two-sided data trading mechanisms, the effect of market structure on data trading mechanisms, the effectiveness of direct data selling of consumers, and firms' data transfers. Literature shows that data intermediaries can utilize different mechanisms in data trading, that market structure strongly affect the efficiency of data trading, that consumers' direct selling of data may be not efficient because of the existence of privacy externality, and that firms make trade-off between the disclosure of sensitive information and benefit of data sharing. Then, we discuss studies on the economic value of data factor and relevant empirical results. Data factor can be used to improve the design of consumer products, to improve asset assignment in financial markets, and to train AI algorithms. All these effects can boost economic growth. By using EU's GDPR as a natural experiment, current studies have estimated the economic value of data factor. Lastly, we discuss future studies of practical issues of data factor in china. We show that information design, mechanism design, and behavioral economics are of particular interests in studying data factor. We also provide important areas in studying data factor in China, including the measurement of data factor and the estimation of its effect on TFP, design of optimal digital tax, data privacy protection, and data factor's effect on the anti-trust issues of digital platforms. The present study provides reference for the research of data factor and digital economy in China.