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数据要素成为中国经济增长新动能的机制探析

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本文重点关注数据资本影响中国经济增长的内在机制.本文提出数据采样模型,将数据作为有意识生产积累的结果,而不是副产品引入增长模型,引入内部数据和外部数据之间的替代性以考察数据非竞争性的作用,理论分析发现内外部数据互补性程度会影响数据对增长贡献的大小,数据影响增长存在通过促进创新和直接作用于生产部门这两个基本渠道.利用省际数据资本存量和面板模型的实证结果表明,同数据采集、数据清洗和存储阶段积累的数据资本相比,数据加工阶段所积累的数据资本对经济增长的贡献更大.特别是利用空间面板模型发现,数据资本在现实中的溢出效应很小甚至为负,数据资本非竞争性的特点可能没有理论预言的那么强,甚至产生一定的"虹吸"效应.数据资本既可直接作用于生产活动,也可通过创新活动间接作用于生产,但是通过促进创新发挥的作用远弱于前者.因此,若要数据真正成为未来中国经济增长的新动能,迫切需要通过加强数据要素市场建设促进数据的流通、汇聚和分享,并充分发挥数据对研发与创新的促进作用.
Analysis on Mechanism of Data as a New Growth Engine for China
In the new stage of China's economy development,identifying new drivers of economic growth is crucial for sustaining long-term development goals.From the perspective of production factors,traditional inputs(e.g.,capital,labor,and human capital)appear to have diminishing potential to support future growth.Amid the rapid expansion of the digital economy,data has emerged as a pivotal production factor,underscoring the importance of measuring its value and contri-bution to economic growth.Data has transitioned from a by-product of economic activities into a strategic asset that is actively collected,pro-cessed,or even generated specifically for economic ends.Exploring data capital's contribution to economic growth re-quires a clear understanding of the data value chain.This value chain is structured in three stages.The first stage involves data collection,where raw information from various economic scenarios is systematically recorded.In the second stage,data undergoes cleaning and storage processes,which remove redundancies,standardize formats,and enhance quality,producing refined data.The third stage involves applying algorithms to refined data,facilitating value extraction and mak-ing it usable across production contexts;we refer to this final output as data capital.At this stage,data attains productive utility and can thus be considered a production factor.Data companies,therefore,trade data as a production input within data markets,supplying product companies that le-verage data to improve efficiency.Through this process,product companies generate significant amounts of information from production activities,and when goods reach consumers,consumption data further enriches this ecosystem.While in-formation naturally arises from various economic activities,it becomes data only after data companies invest resources in its collection and recording.Each new cycle of economic activity yields additional information,which data companies capture as raw data,thereby catalyzing ongoing data production along the value chain.In each economic cycle,data capi-tal grows iteratively,accumulating as a stock of data capital.Newly generated data in each cycle represents the formation of data capital,while the cumulative total forms its stock.Based on such data market framework,this paper examines how the accumulation of data capital impacts China's economic growth,leveraging its non-rivalrous characteristics to drive growth through two main channels:direct effects on production sectors and indirect effects on innovation.By analyzing distinct stages in the formation of data capital-data collection,cleaning and storage,and processing-this study constructs a sampling model of data production and de-velops a growth model based on data capital,which is then solved to determine a balanced growth path.Findings indicate that data capital accelerates economic growth,with its impact intensifying as returns to data scale and substitutability be-tween internal and external data improve.These results imply that the growth contribution of data capital is maximized when its non-rivalrous nature is fully utilized.Data capital can directly drive production-sector growth or indirectly sup-port growth by promoting R&D and innovation.Following our economic model,we further explore how data drives growth in China.Specifically,this paper em-ploys estimates of provincial data capital stocks in China,and our empirical results show three key conclusions.First,data capital's contribution to economic growth varies across stages,with data capital formed in the third stage exerting a more substantial impact on growth than that formed in earlier stages.This suggests that China's data value chain currently exhibits a development gap in data processing and analysis.Second,while data is theoretically non-rival and replicable at zero cost,spatial regression indicates limited spillover effects of data capital in China.This finding suggests two issues:an underdeveloped data factor market in China and insufficient interregional data flow.It also raises the possibility that data's cross-regional and cross-sectoral utility may be lower than theoretical expectations suggest.Third,in our economic model,data capital impacts economic growth through two channels:directly influencing production or indirectly foster-ing R&D and innovation.However,empirical evidence shows that the indirect channel is notably weaker than the direct one,indicating that data capital's potential in innovation activities remains largely untapped.In sum,while data capital has already contributed to accelerating China's economic growth and shows promise as a new driver of future growth,its current impact remains constrained.The fundamental advantage of data's non-rivalrous nature,along with its essential role in fostering R&D and innovation,has yet to be fully observed.

Data CapitalEconomic GrowthSpillover EffectsData Complementarity

刘涛雄、张亚迪、戎珂、周迪

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清华大学社会科学学院经济学研究所,邮政编码:100084

北京交通大学经济管理学院,邮政编码:100044

同济大学经济与管理学院,邮政编码:200092

数据资本 经济增长 外溢效应 数据互补性

2024

经济研究
中国社会科学院经济研究所

经济研究

CSTPCDCSSCICHSSCD北大核心
影响因子:4.821
ISSN:0577-9154
年,卷(期):2024.59(10)