统计与信息论坛

在数字经济时代，数据成为与土地、劳动力、技术和资本并列的第五大关键生产要素，如何发挥数据要素的绿色创新作用成为亟须关注的重要问题。基于资源基础观、交易成本理论、动态能力理论与竞争逃离假说，剖析数据要素市场化对企业绿色创新效率提升的理论机制，并以2012—2022年中国A股上市公司数据为研究样本，通过双重机器学习模型进行实证检验。研究发现：数据要素市场化显著提升了企业绿色创新效率，在经过一系列稳健性检验后该结论依旧成立；机制分析表明，数据要素市场化能通过推进数字化转型和加剧市场竞争两条路径提升企业绿色创新效率；异质性分析发现，数据要素市场化对小规模企业、重污染企业以及东部地区企业的绿色创新效率存在明显的提升作用。研究结论不仅拓展了企业绿色创新效率驱动因素的相关研究，也为政府持续深化数据要素市场化改革提供了政策指向。

In the era of digital economy, data has became the fifth key productive element alongside land, labor, technology, and capital.At the same time, enterprises must continuously explore green innovation models and enhance their green innovation efficiency to achieve high-quality development ultimately.However, tight resource constraints and significant technology gaps hamper improvements in enterprise green innovation capabilities.Consequently, the green innovation efficiency of Chinese enterprises falls substantially short of actual development needs.Therefore, whether data element marketization can enhance the efficiency of green innovation in enterprises has become a critical problem to be sdved urgently.Grounded in the resource-based view, transaction cost theory, dynamic capability theory, and the competition escape hypothesis, the theoretical mechanisms are analyzed, that data element marketization enhances enterprises green innovation efficiency.Utilizing a quasi-natural experiment enabled by data trading platforms and employing panel data from Chinese A-share listed companies from 2012 to 2022,a double machine learning method is constructed to empirically test the impact of data element marketization on the efficiency of green innovation in enterprises.The findings reveal that the data element marketization significantly enhances the efficiency of green innovation in enterprises, a conclusion robust to a series of tests, including instrumental variable estimation, subsample regressions, and model re-specification.Mechanism analysis indicates that the data element marketization promotes the efficiency of green innovation through dual machanisms, advancing digital transformation and intensifying market competition.The data element marketization exerts heterogeneous effects on enterprises' green innovation efficiency.Specifically, enterprises with smaller scales, those in pollution-intensive industries, and those located in the eastern region exhibit stronger responses to data element marketization.Based on the research findings, the study proposes the following recommendations.For enterprises, build data-driven decision-making, accelerate digital transformation, and leverage AI,big data and cloud computing to expand their “technology pool”,so that to enhance data capabilities and digital infrastructure to, further sustainably improving the green innovation efficiency.Governments should cultivate high-quality data trading markets and foster sound competition to encourage strategic enterprise collaboration.Differentiated green innovation policies should prioritize large enterprises, non-heavily polluting industries, and central-western enterprises.Capitalizing on data marketization helps overcome inadequate data supply, poor circulation, and undervaluation, providing momentum for green innovation efficiency.The marginal contributions may lie in the following three aspects.First, by employing the double machine learning method under a nonlinear framework, more variables influencing enterprise green innovation efficiency are considered and controlled.Second this study empirically reveals its, by focusing on innovation efficiency, underlying mechanisms of digital transformation and market competition are revealed.enriching the literature on this topic.Finally, heterogeneity is examined in the facilitative effect of data factor marketization across enterprises of varying size, industry, and region.The conclusions not only extend the research on the driving factors of the efficiency of green innovation in enterprises, but also provide policy guidance for the government to further deepen the market-oriented reform of data elements.