Big Data Factor Agglomeration,Technological Capability Gaps and Regional Disparities in Productivity
After more than four decades of rapid growth under reform and opening,the economic growth dependent on traditional factor inputs has gradually slowed,and the Chinese economy now faces structural challenges,including a lack of new growth drivers and unbalanced regional development.With the rapid advancement of digital technologies,big data,as a fundamental and decisive new factor in digital economy production,increasingly enhances total factor productivity(TFP),offering a potential solution to the growth constraints of traditional factor inputs.In this context,big data is expanding rapidly and clustering within specific regions.Consequently,the productivity-enhancing effects of big data agglomeration are anticipated to serve as a catalyst for fostering high-quality regional economic growth and coordinated regional development.However,the regional disparities in TFP within China are widening,indicating a clear deviation between policy intentions and regional outcomes,highlighting a need for an in-depth investigation into the underlying causes of this disparity.Based on this,this paper constructs county-level indicators to assess regional productivity disparities and technological capability gaps,aiming to explore the economic relationships among big data factor agglomeration,technological capability gaps,and regional TFP disparity.This paper finds that big data factor agglomeration significantly intensifies the productivity disparity between agglomerated and frontier regions.This disparity arises from the unrealized productivity-enhancing potential of big data,which is constrained by gaps in data acquisition and application capabilities.In other words,technological capability gaps inhibit big data's productivity-enhancing effects.Additionally,spatial separation in big data storage and utilization further amplifies these regional productivity disparities through spatial effects.These findings validate this paper's proposition that"the agglomeration effect of big data is not an automatic outcome of classical'input-output'dynamics but requires a foundation of essential technological capabilities".The potential contributions of this paper are as follows.Firstly,it analyzes the technical prerequisites for the big data factor to achieve productivity-enhancing effects from the standpoint of technological capabilities,offering insights into why big data factor agglomeration may widen regional productivity disparity.Secondly,based on the theory of appropriate technological progress,it establishes a theoretical framework and transmission mechanism that illustrates how big data factor agglomeration,technological capability gaps,and spatial amplification effects shape regional productivity disparities.Thirdly,this paper calculates TFP at the county level across China from 2011 to 2021 and develops technological capability indicators using data from national business registrations,matching these with county-level data,thereby providing a useful reference for macro-level research.Lastly,presenting novel findings on big data factor agglomeration and regional productivity disparities,this paper contributes fresh empirical evidence for productivity convergence and coordinated regional development in the digital economy era.It offers a reference framework for policy decisions aimed at maximizing the economic multiplier and productivity-enabling effects of the big data factor to drive high-quality growth.
big data factortechnological capability gapsTFPagglomerationregional disparities
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