Data elements marketization and the development of New Quality Productive Forces: Causal inference based on double machine learning

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Received date: 2024-05-23

  Revised date: 2024-06-30

  Online published: 2024-08-22

Abstract

On the basis of constructing a theoretical framework that data factor marketization empowers the development of regional new-quality productivity, and quasi-natural experiments based on the establishment of a data public trading platform, panel data of 284 prefecture-level cities are selected from 2011-2021, and its mechanism of action and regulation is analyzed based on the dual machine learning method. The results show that the construction of data factor marketization effectively empowers the development of regional new quality productivity. In terms of heterogeneity, data factor marketization significantly promotes the development of new-quality productivity in high science and education levels and first- and second-tier cities, while it has no significant driving effect in low science and education levels and cities below the third tier. In terms of the mechanism of action, data factor marketization drives the level of new quality productivity through the mechanisms of guiding market integration, optimizing factor allocation, and reconstructing innovation paradigms. In terms of the regulating mechanism, data factor marketization stimulates the data factor multiplier effect through channels such as industrial upgrading and transformation, digital talent gathering and foreign capital utilization level. Policy recommendations are then put forward to fully release the value of data factors and provide strong support for accelerating the formation of new quality productivity.

Cite this article

LU Yang, WANG Yu-bao . Data elements marketization and the development of New Quality Productive Forces: Causal inference based on double machine learning[J]. Urban Problems, 2024 , 348(7) : 80 -90 . DOI: 10.13239/j.bjsshkxy.cswt.240707

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