Data factor market construction and firm labor income share: a quasi-natural experimental analysis based on China's data trading platforms

Purpose This study examines how the development of a formal data factor market affects the labor income share at the firm level. Design/methodology/approach We employ a staggered difference-in-differences design, leveraging China's phased rollout of official data trading platforms as a quasi-natural experiment. The analysis uses panel data from A-share listed companies spanning 2012 to 2023. Findings The establishment of data trading platforms significantly raises the labor income share. This effect operates through three channels: digital transformation, increased innovation, and workforce restructuring. It is attenuated by ownership concentration but amplified by human-capital investment. The positive impact is more pronounced in non-state-owned firms, labor-intensive firms, and regions with better-developed digital infrastructure and factor markets. Originality/value This study provides novel causal evidence on how institutionalizing data markets shapes distributional outcomes, shifting the focus from technological diffusion to market design. It systematically identifies key transmission channels and boundary conditions, and documents heterogeneous benefits across firm types and regions, offering a nuanced understanding of data-driven growth.