Data Elements Allocation and Corporate Green Innovation: Causal Inference Based on the Staggered DID Model

Against the dual strategic backdrop of the digital economy and green low-carbon development, data, as an emerging production factor, has an unclear yet critical impact of its market-oriented allocation on corporate green innovation, which deserves in-depth and systematic exploration. Taking the panel data of China's A-share listed companies from 2009 to 2023 as the research sample, this paper regards the establishment of data trading platforms as a quasi-natural experiment, and adopts the staggered Difference-in-Differences (DID) model to empirically examine the causal effect and underlying transmission mechanisms of data elements allocation on corporate green innovation. Empirical evidence reveals that deploying data elements plays a key role in improving corporate green innovation outcomes. Further mechanism analysis reveals that data elements allocation empowers corporate green innovation through three validated channels: alleviating corporate financing constraints, optimizing the human capital structure, and facilitating cross-subject collaborative innovation. These conclusions not only supplement micro-level empirical evidence for the synergy between digital economy development and green transformation, but also provide targeted policy implications for advancing the market-oriented reform of data factors and high-quality green development of enterprises.