Can the backward endowments of rural areas support digital village construction to attain the expected results? If the answer is yes, what are the mechanisms involved? Answering these questions is related to common prosperity. Counties are China’s frontline commanders, and the urban–rural income gap is a suitable entry point for observing the urban–rural digital divide; however, there is limited research assessing the effectiveness of digital village construction from the perspective of the urban–rural income gap at the county level. In addition, counties lifted out of poverty, as counties with worse initial endowments and as counties that should be most concerned with common wealth, are more typical for examining the effectiveness of digital rural construction; however, there are few studies on counties lifted out of poverty. Based on cross-sectional data from 865 counties in China in 2020, this study empirically analyzes the impact of digital village construction on the urban–rural income gap using an OLS model. This study also conducts mechanism tests and poverty benefit tests in addition to heterogeneity and robustness tests. The findings indicate that the development of digital villages lowers the income difference between urban and rural areas, and that the shift in the industrial structure is a key driver of this effect. Different construction dimensions have varying degrees of impact, with digital infrastructure and the digitalization of the economy having the most significant impact, the digitalization of countryside governance coming second, and the digitalization of countryside life having the most negligible impact. The impact is more pronounced in the central-eastern region of China and counties that have just been lifted out of poverty than in the western region and counties that have never been in poverty. The government will benefit greatly from this study’s understanding of the main themes, areas, and scope of digital rural construction, which will help to expand and further integrate the outcomes of reducing poverty and fostering shared prosperity.

China’s carbon emissions trading policy represents a significant institutional innovation designed to advance the country’s economic and social development towards sustainability and low-carbon growth. This study investigates the effects of China’s carbon emissions trading policy by employing the difference-in-differences model and spatial Durbin model, using provincial panel data spanning from 2005 to 2020. We find that the carbon emissions trading policy can inhibit per capita carbon emissions in the pilot areas. This work is primarily driven by green technological innovation and the upgrade of industrial structure. Furthermore, the carbon emissions trading policy exhibits a positive spatial spillover effect, inhibits per capita carbon emissions in the areas adjacent to the pilot through demonstration effect and competition effect, and does not cause carbon leakage. These findings reveal the policy’s effectiveness in emissions reduction, and may be useful reference for promoting sustainable economic and social development. This is of great practical significance for exploring how to optimize environmental governance measures, avoid carbon leakage, and achieve balance and fairness in responsibilities in achieving low-carbon sustainable development. Our study proposes policy recommendations for synergizing the national trading market in China.

The fragmented nature of Chinese households’ forestland hinders the realization of economies of scale in forestry production. Understanding the role of forestry service outsourcing organizations in mitigating this fragmentation provides a critical foundation for the exploration of pathways to scaled forestry management. Based on tracking data from 500 households across 10 counties in Fujian Province between 2013 and 2018, this study examines an unbalanced panel containing six periods and 2780 valid observations. It constructs a panel Logit model to examine the influence of forestry service outsourcing organizations on the likelihood of forestland transfer by households, and it employs a panel Tobit model to analyze the relationship between these organizations and the scale of forestland transferred. To capture potential heterogeneity, the analysis incorporates households’ part-time status and the forestland terrain conditions. The results indicate that the duration of establishment of county-level forestry project teams and forestry companies in households’ regions significantly reduces the tendency of households to lease out their forestland, especially for those in plain and hilly regions and part-time forestry producers. Furthermore, the longer the establishment history of township-level forestry project teams, the more inclined households are to retain their family forestland management rights. Our study demonstrates that, when specialized forestry service outsourcing organizations emerge in the market, households are less likely to lease out their forestland, thereby retaining management rights, avoiding the risk of forestland loss, and reducing forestland abandonment. As forestry service outsourcing organizations continue to develop and expand—with improvements in service levels and production efficiency—forestry production is gradually transitioning toward a new stage of service-oriented scale operations.