This study examines how digital development dynamically reshapes employment in China using provincial panel data (30 provinces, 2012-2022) and System GMM estimation. We construct a comprehensive digital development index spanning infrastructure, industrialization, industry digitalization, and innovation to address endogeneity and capture dynamic adjustments. Results suggest that digital development is positively associated with employment in the current year, followed by a partial negative adjustment in the subsequent year. This aggregate pattern conceals substantial heterogeneity: highly educated workers experience job restructuring with minimal net change, while less educated workers gain employment primarily through digital infrastructure expansion. Across income groups, job growth concentrates in high-income regions, with employment shifting toward secondary and tertiary sectors. Institutional factors also matter. The moderating association of human capital is insignificant, while that of government education spending is significantly negative. These patterns tend to be consistent with a possible misalignment between educational outputs and the skill demands of the digital labor market. These findings highlight that digital development’s employment associations depend heavily on regional economic conditions, worker skill levels, and institutional quality, suggesting targeted policy interventions are essential for inclusive digital transformation.
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Xiao et al. (2026) studied this question.
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