制度松绑、数字治理生态与新质生产力——双重机器学习下大数据管理机构设立的准自然实验  

Institutional Deregulation, Digital Governance Ecosystem and New QualityProductive Forces: A Quasi-Natural Experiment for the Establishment ofBig Data Management Organizations under the Double Machine Learning Model

作　　者：魏万青[1,2,3] 叶秋志 陈永洲 Wei Wanqing;Ye Qiuzhi;Chen Yongzhou(School of Public Administration,Guangxi University,Nanning 530004,China;School of Social Development,East China Normal University,Shanghai 200241,China;Regional Social Governance Innovation Research Center,Guangxi University,Nanning 530004,China)

机构地区：[1]广西大学公共管理学院,广西南宁530004 [2]华东师范大学社会发展学院,上海200241 [3]广西大学区域社会治理创新研究中心,广西南宁530004

出　　处：《科技进步与对策》2025年第1期10-20,共11页Science & Technology Progress and Policy

基　　金：国家社会科学基金后期资助重点项目(22FSHA003);广西教育厅高校人文社科重点研究基地重大项目(JDZD202203);广西研究生教育创新计划项目(YCBZ2024030)。

摘　　要：数据具有边际报酬递增乘数效应,是打造新质生产力的新增长极。通过数据制度松绑将赋能新质生产力,助力高质量发展与中国式现代化。借助双重机器学习模型,选取2010—2022年省级面板数据,探讨大数据管理机构设立对新质生产力的影响,考察制度松绑、数字治理生态与新质生产力的内在联系与建链路径。研究发现:①以大数据管理机构设立为代表的制度松绑能有效促进新质生产力发展。大数据管理机构的设立推动数字政策环境、数字经济环境与数字社会环境优化,从而作用于新质生产力发展;②进一步分析发现,制度松绑带来的驱动效应受到异质性因素干扰,其中在高政府效率、高人力资本、高信息化水平地区的作用效果更强。研究结论为新质生产力嵌入制度变迁视角提供理论解读,为通过制度路径和治理体系推动新质生产力发展提供现实依据。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.Nevertheless,at this juncture,the advancement of novel,new quality productive forces in China is still constrained by institutional 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 insufficient 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 innovation and the cultivation of scientific talent.However,a limitation of these studies is that they do not address the institutional 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 removing obstacles,enhancing aggregation,and facilitating circulation.As a result,they have contributed to the development of a robust digital governance ecosystem,enabling the realization of data's full potential.This may prove to be a pivotal 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

关 键 词：制度松绑 数字治理生态 新质生产力 大数据管理机构 双重机器学习 

分 类 号：F014.1[经济管理—政治经济学]