The sustainable and efficient use of water resources has gained wide social concern, and the key point is to investigate the virtual water trade of the water-scarcity region and optimize water resources allocation. In this paper, we apply a multi-regional input-output model to analyze patterns and the spillover risks of the interprovincial virtual water trade in the Yellow River Economic Belt, China. The results show that: (1) The agriculture and supply sector as well as electricity and hot water production own the largest total water use coefficient, being high-risk water use sectors in the Yellow River Economic Belt. These two sectors also play a major role in the inflow and outflow of virtual water; (2) The overall situation of the Yellow River Economic Belt is virtual water inflow, but the pattern of virtual water trade between eastern and western provinces is quite different. Shandong, Henan, Shaanxi, and Inner Mongolia belong to the virtual water net inflow area, while the virtual water net outflow regions are concentrated in Shanxi, Gansu, Xinjiang, Ningxia, and Qinghai; (3) Due to higher water resource stress, Shandong and Shanxi suffer a higher cumulative risk through virtual water trade. Also, Shandong, Henan, and Inner Mongolia have a higher spillover risk to other provinces in the Yellow River Economic Belt.

Virtual water trade is widely considered as a potential method to solve local water shortage and unequal distribution. However, limited research investigated water-saving efficiency and water inequality of inter-provincial virtual water trade. In this study, we sought to explore this issue within China based on the 2015 input-output data. A multi-regional input-output model and a modified input-output model were used to estimate the virtual water trade and its impact on water-saving and water inequality. Our results suggest that: (1) The total virtual water flow across the country is 200.03 × 10⁹ m³, which accounts for 32.77% of water withdrawal. The agriculture sector contributes the highest proportion (73.99%) to virtual water flow. (2) Virtual water trade could decrease water withdrawal by 446.08 × 10⁹ m³ compared with withdrawal under no-trade situation at a national level, and 22 provinces could gain benefits through inter-provincial trade with a positive water-saving efficiency index. (3) Virtual water trade also causes water inequality, which exacerbates water scarcity of exported provinces, especially in northwest provinces. (4) There is a conflict between water conservation and water inequality, but different provinces show significant heterogeneity.

County entrepreneurial activities play a vital role in fostering rural industrial prosperity, advancing digital village development, and improving residents’ welfare. This study empirically investigated the impact and mechanisms through which digital village construction influences county entrepreneurial activity, utilizing the Digital Village Index (2020) from the Institute for New Rural Development at Peking University, along with economic data from 2267 counties. The findings are as follows: (1) Digital village construction significantly enhances county entrepreneurial activity, with results robustly validated through endogeneity tests and robustness checks. (2) Key components of digital village construction, including rural digital infrastructure, rural economic digitization, rural governance digitization, and rural life digitization, all positively influence entrepreneurial activity, with rural economic digitization exerting the most substantial effect. (3) The primary channels through which digital village construction fosters entrepreneurial activity include the promotion of e-commerce, facilitation of non-farm employment, and encouragement of technological innovation. (4) The entrepreneurial benefits of digital village construction are more pronounced in counties located in the central and eastern regions, particularly those within the Yangtze River Economic Belt, as compared to counties in the western region and non-Yangtze River Economic Belt. (5) The impact of digital village construction on entrepreneurial activity is conditional, with stronger effects observed in counties with higher baseline entrepreneurial activity.