Raising rural household income is central to narrowing the rural–urban gap and advancing common prosperity. Using data from the China Family Panel Studies (CFPS), this study examines the impact of digital skills, a key for human capital, on rural Chinese households’ income and uses a fixed-effects model and the instrumental variable method to address endogeneity. The study finds that digital skills raise total household income, and each additional skill is associated with an increase of CNY 1678. By skill type, online business skills have the largest effect, followed by work–study skills, while entertainment–social skills are negatively associated with income. Heterogeneity analyses indicate larger gains for households with lower educational attainment and lower income, showing that a stronger regional digital environment amplifies these effects. Mechanism tests point to factor reallocation toward the nonfarm sector, via higher probabilities of off-farm employment and entrepreneurship and improved access to formal credit, as the primary pathway. Consistent with these channels, digital skills increase wages and operating income and reduce inequality in these components, as well as benefitting total income, but they have no detectable effect on property or transfer income or their dispersion. These findings point to key implications for boosting rural income growth and reducing inequality, namely strengthening digital skill development and optimizing the digital environment to enhance rural households’ endogenous income-generating capacity.

Open public data is a vital institutional arrangement for overcoming data constraints in corporate low-carbon technological innovation; however, its mechanisms and boundaries remain empirically untested. Using a panel dataset of China’s Shanghai- and Shenzhen-listed A-share firms over the 2007-2023 period, this study employs a difference-in-differences (DID) approach to examine the impact of open public data on corporate low-carbon technological innovation. The results show that open public data has a significant positive effect on corporate low-carbon technological innovation, and the results remain robust across multiple validation tests. Mechanism tests point out that open public data primarily drives corporate low-carbon technological innovation by enhancing government transparency and reducing barriers to factor mobility. The heterogeneity analysis indicates that the positive impact of open public data is more pronounced among firms characterized by higher R&D investment, lower financial constraints, and greater digitalization. Further analysis indicates that open public data also exhibits significant geographic and industry spillover effects, with the geographic spillover following an inverted U-shaped pattern of decay and the industry spillover driven by peer imitation. This paper provides policy references for the development of open public data and the enhancement of corporate low-carbon technological innova-tion.

Open public data is a vital institutional arrangement for overcoming data constraints in corporate low-carbon technological innovation. Using a panel dataset of China’s Shanghai and Shenzhen A-share listed firms over the 2007–2023 period, this study employs a difference-in-differences (DID) approach to examine the impact of open public data on corporate low-carbon technological innovation. The results show that open public data has a significant positive effect on corporate low-carbon technological innovation, and the results remain robust across multiple validation tests. Mechanism tests point out that government transparency negatively moderates the promotional effect of public data openness on corporate low-carbon technological innovation, while barriers to factor mobility positively moderate this effect. The heterogeneity analysis indicates that the positive impact of open public data is more pronounced among firms characterized by higher R&D investment, lower financial constraints, and greater digitalization. Further analysis indicates that open public data also exhibits significant geographic and industry spillover effects, with the geographic spillover following an inverted U-shaped pattern of decay and the industry spillover driven by peer imitation. This study provides evidence on leveraging open public data to stimulate low-carbon innovation and facilitate green economic transformation, offering valuable insights for advancing data-driven sustainable development globally.

This study examines how client ESG performance affects supplier total factor productivity (TFP) from a knowledge spillover perspective, using matched client–supplier–year data for Chinese A-share listed firms from 2010 to 2023. The results show that client ESG significantly improves supplier TFP; specifically, a one-unit increase in client ESG is associated with an average increase of approximately 8.3% in supplier TFP. These results remain robust across a series of robustness tests. Mechanism analysis indicates that client ESG enhances supplier productivity through three knowledge spillover channels: technical assistance, management sharing, and innovation induction. Heterogeneity analysis further shows that this positive effect is more pronounced in long-term cooperative relationships, among clients with stronger market power, for state-owned suppliers, and when clients and suppliers have aligned ownership structures. Further analysis shows that the positive effect of client ESG persists for at least three fiscal years and is more pronounced in industries characterized by lower volatility. These findings suggest that policymakers and firms should strengthen supply chain ESG governance to promote knowledge spillovers and improve productivity.