Data Elements Marketization and Corporate Investment Efficiency: Causal Inference via Double Machine Learning - Yeteng Ma; Zhuo Li; Li He (Systems)
Amid the rapid development of the digital economy, data elements—emerging as a new type of production factor—are gradually becoming a key resource for enhancing corporate efficiency and promoting high-quality development. The marketization of data elements is also steadily progressing and playing an increasingly important role. Based on data from Chinese A-share listed companies spanning 2007 to 2023, this study systematically evaluates the impact of data element marketization on corporate investment efficiency using a Double Machine Learning approach. The findings reveal that data element marketization significantly improves investment efficiency. Mechanism analysis further demonstrates that such improvement is primarily driven by reduced information dispersion, enhanced risk-bearing capacity, and improved operational efficiency. Heterogeneity analysis indicates that these effects are more pronounced for firms in high-tech industries, high growth potential firms, enterprises located in regions with strong digital infrastructure, and firms experiencing overinvestment problems. This study provides empirical evidence on how the marketization of data elements in China enhances economic outcomes, improving corporate investment decisions, which could serve as a reference for other countries undergoing digital transformation.