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

Yutian Zhao, Yanjie Wang and Chuang Li

International Journal of Manpower, 2026, vol. 47, issue 2, 389-402

Abstract: PurposeThis study examines how the development of a formal data factor market affects the labor income share at the firm level.Design/methodology/approachWe 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.FindingsThe 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/valueThis 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.

Keywords: Data factor market construction; Firm labor income share; Staggered difference-in-differences; Quasi-natural experimental (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:eme:ijmpps:ijm-10-2025-0919

DOI: 10.1108/IJM-10-2025-0919

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