Institutional Deregulation,Digital Governance Ecosystem and New Quality Productive Forces:A Quasi-Natural Experiment for the Establishment of Big Data Management Organizations under the Double Machine Learning Model
The new quality productive forces are defined by the reliance on the superposition and iteration of data elements.This represents the original driving force behind the maintenance of high-quality economic and social development.Never-theless,at this juncture,the advancement of novel,new quality productive forces in China is still constrained by institu-tional impediments,including the absence of a well-defined property rights system,a suboptimal distribution apparatus,and inadequate incentives,particularly a deficient database system and an imperfect data governance apparatus.The insuf-ficient development of economic,educational,scientific and technological,and human resources is regarded as the primary factor contributing to the stagnation in the advancement of new quality productive forces.Some studies have proposed that the development of new quality productive forces should be reinforced through the establishment of a modernized industrial system,the advancement of scientific and educational endeavors,the advancement of scientific and technological innova-tion and the cultivation of scientific talent.However,a limitation of these studies is that they do not address the institu-tional constraints that impede the leapfrogging of new quality productive forces,particularly the lack of empirical evidence on whether effective institutional arrangements for data can facilitate the development of new quality productive forces.By establishing effective institutional frameworks,big data management organizations have been instrumental in re-moving obstacles,enhancing aggregation,and facilitating circulation.As a result,they have contributed to the develop-ment of a robust digital governance ecosystem,enabling the realization of data's full potential.This may prove to be a piv-otal factor in facilitating new quality productive forces gains centered on data-driven.Accordingly,this paper considers the establishment of provincial big data management agencies as a prototypical instance of data institutional deregulation.It examines the intrinsic links and pathways of action of institutional deregulation,the digital governance ecosystem,and new quality productive forces from the perspective of institutional change,utilizing provincial panel data from 2010 to 2022 and a double machine learning model.The findings indicate that the establishment of the big data management organizations,which represents institutional deregulation,has been effective in promoting the development of new quality productive forces.A mechanism analysis in-dicates that the establishment of big data management organizations can facilitate the creation of a favorable digital govern-ance ecosystem and accelerate the development of new quality productive forces through the exploitation of institutional ad-vantages.Specifically,the establishment of management organizations optimizes the digital policy environment,the digital economic environment,and the digital social environment,thereby contributing to the development of new quality produc-tive forces.Further analysis indicates that the impact of institutional deregulation on new quality productive forces varies across contexts.In regions exhibiting high government efficiency,high human capital,and high levels of information tech-nology,the effect is particularly pronounced.This paper contributes threefold to the literature.Firstly,it introduces a novel research perspective.From the van-tage point of institutional change,the institutional deregulation experiment of establishing a big data management organi-zation reveals that institutional deregulation exerts an upgrading influence on the advancement of new quality productive forces.This not only serves to embed the theoretical interpretation of the institutional change perspective for new quality productive forces,but also provides empirical evidence from China to deepen the institutional theory in the era of digital in-telligence.Secondly,this paper presents a novel chain-building path of"institutional deregulation-digital governance eco-system-new quality productive forces,"which can further elucidate the mechanism that is currently opaque between insti-tutional deregulation and the development of new quality productive forces.Thirdly,it methodologically employs double machine learning to address model issues in complex analyses.It can effectively circumvent the issues of model misspecifi-cation and the curse of dimensionality that may be encountered by traditional models in the intricate cascade of the topics of new quality productive forces,enhancing conclusion accuracy.The study's findings offer a theoretical interpretation of the institutional change perspective for new quality productive forces and provide a practical basis for policy formulation to pro-mote the development of new quality productive forces through institutional paths and governance systems.
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万方数据
