大数据、技术进步与经济增长——大数据作为生产要素的一个内生增长理论

Big Data,Technical Progress and Economic Growth:An Endogenous Growth Theory Introducing Data as Production Factors

本文旨在揭示大数据对经济增长的内生影响,以大数据作为生产要素拓展了内生增长理论。一是将大数据作为新型生产要素从物质资本中剥离,在“创造性破坏”理论框架下将大数据内生化引入生产函数,构建了多部门熊彼特质量阶梯模型,理论演绎大数据促进中间品质量阶梯提升高度的“乘数作用”和引起“研发模式转型”。二是理论刻画了大数据驱动技术进步与经济增长的路径与机制,并进行数值模拟检验。研究表明:大数据与其他生产要素存在“融合成本”,导致“研发模式转型”抑制短期经济产出;在长期,大数据通过“乘数作用”提升中间品质量水平和促进技术进步,持续推动经济增长;大数据的“乘数作用”随其“应用程度”提高而放大;同时,在中国要素收入分配偏向资本情景下,大数据将发挥更大的经济增长效应。本文拓展了大数据影响经济增长的内生增长理论,为大数据发展提供理论支撑。

Big data is spearheading a new round of technological revolution,which in turn is leading,driving and transforming economic growth patterns.It is important to examine how big data will influence technological progress and economic growth and to specify its mechanisms.This paper investigates the path and mechanism of big data driving technological progress and economic growth.We expand the endogenous growth theory that technological progress driven by big data affects economic growth,providing theoretical support for the way big data is currently developing.Based on the theory of creative destruction,we construct a big data-economic growth model.Firstly,by taking big data as an independent factor of production and introducing it into the endogenous growth model,we illustrate the multiplier effect and application degree of big data.Secondly,we describe how big data drive R&D patterns in technological development,as well as big data’s multiplier effect on the enhancement of quality ladder of intermediate goods.Thirdly,we specify the mechanisms through which big data drive technological progress and influence economic growth,and compare the difference in economic growth before and after the application of big data.Finally,to verify the theoretical assumptions,we make a numerical simulation to analyze the impact of big data on economic growth based on the empirical data.This paper puts forward four propositions,which explain the underlying mechanisms through which big data influence technological progress and economic growth.First,in the long run,big data has a multiplier effect on the enhancement of quality ladder of intermediate goods by infiltrating production and R&D enterprises.Second,in the short run,since R&D enterprises need time to make complementary investments and adapt to the new R&D mode,so that they can transform their production R&D mode,which leads to the lag of technological progress,fluctuation effect and economic depression.Third,the higher the application degree of big data,the larger multiplier effect of big data on economic growth.Fourth,compared with developed countries,China’s economy will grow faster as a result of big data because it has a higher level of capital income distribution.This paper contributes to the literature in three ways.First,by taking big data as an independent productive factor and introducing it into the endogenous growth model,we explain the multiplier effect of big data on the enhancement of quality ladder of intermediate goods.Second,this paper provides a theoretical explanation of the application degree and the multiplier effect of big data,describing these as dynamic processes.Third,we also theoretically explain the transformation of R&D patterns driven by big data.Our paper captures the essential characteristics of big data’s fluctuation effects on technological progress and economic growth.Fourth,this paper expands the endogenous economic growth theory through a big data economic growth model,which reveals the mechanisms through which big data influence economic growth.This paper has three policy implications.First,the government should encourage market players to carry out data collection in accordance with the law.It should also promote the construction of a data resources standard system,improve data quality and data management,and establish a global public data use system.Second,the government should promote data trading by building data banks,fostering and strengthening data trading platforms.It should conduct top-level design on data asset evaluation and trading rules,and promote to establish data asset value evaluation indicators and trading system.Third,the government should establish global and national data resource archives and data asset management systems.It should also build a flexible and effective data market governance system that is compatible with the healthy development of the data market.In future studies,we will explore ways to establish a data market access management system that combines a positive guidance list with a negative prohibition list and certification and rating by third-party institutions.This paper also has some limitations.Most notably,we assume that non-competitive data is a shared factor of production among enterprises,whereas it is not the case in reality.Changes in ownership and sharing parameters may influence the multiplier effect and effectiveness of economic growth,and relaxing those assumptions could be an interesting topic for future research.