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<p>As the global economy transitions toward sustainable development, Green New Quality Productive Forces (GNQPF) have emerged as a&#xa0;critical strategic paradigm. Simultaneously, data elements have become transformative factors of production characterized by non-rivalry and near-zero marginal transmission costs. However, whether and how the marketization of data elements empowers GNQPF remains insufficiently explored. Utilizing the establishment of China’s National Big Data Comprehensive Experimental Zones as a&#xa0;quasi-natural experiment, this study employs a&#xa0;Spatial Durbin Difference-in-Differences (SDM-DID) model to identify the causal and spatial effects of data elements on GNQPF based on a&#xa0;panel dataset of 280 cities from 2007 to 2024. The results robustly demonstrate that the marketization of data elements directly accelerates local GNQPF and generates powerful positive spatial spillovers to neighboring cities. Crucially, a&#xa0;spatial mediation analysis reveals that data elements act as an informational solvent to correct traditional Environmental Resource Misallocation (ERM), which serves as a&#xa0;vital transmission channel. Furthermore, heterogeneity analysis indicates a&#xa0;profound Matthew Effect, where the empowerment is significantly stronger in eastern regions and cities with superior digital infrastructure. This study provides vital micro-theoretical mechanisms and novel methodological insights for policymakers aiming to leverage digital transitions to achieve regional green growth.</p>

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Data Elements, Spatial Spillovers, and Green New Quality Productive Forces: a Spatial Difference-in-Differences Approach from China

  • 期刊论文

  • 发表日期：

    2026年7月30日

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  • Jingdong Huang

摘要

As the global economy transitions toward sustainable development, Green New Quality Productive Forces (GNQPF) have emerged as a critical strategic paradigm. Simultaneously, data elements have become transformative factors of production characterized by non-rivalry and near-zero marginal transmission costs. However, whether and how the marketization of data elements empowers GNQPF remains insufficiently explored. Utilizing the establishment of China’s National Big Data Comprehensive Experimental Zones as a quasi-natural experiment, this study employs a Spatial Durbin Difference-in-Differences (SDM-DID) model to identify the causal and spatial effects of data elements on GNQPF based on a panel dataset of 280 cities from 2007 to 2024. The results robustly demonstrate that the marketization of data elements directly accelerates local GNQPF and generates powerful positive spatial spillovers to neighboring cities. Crucially, a spatial mediation analysis reveals that data elements act as an informational solvent to correct traditional Environmental Resource Misallocation (ERM), which serves as a vital transmission channel. Furthermore, heterogeneity analysis indicates a profound Matthew Effect, where the empowerment is significantly stronger in eastern regions and cities with superior digital infrastructure. This study provides vital micro-theoretical mechanisms and novel methodological insights for policymakers aiming to leverage digital transitions to achieve regional green growth.