Digital village construction is the key to future rural development in China. This study has empirically examined the impact of digital village construction on county-level economic growth in China, utilizing non-balanced panel data from 16 provinces and 622 counties for the years from 2018 to 2021. The study also investigated the underlying mechanisms and conducted heterogeneity and robustness tests using various analytical methods, including instrumental variables and the difference-in-differences (DID) approach. The findings reveal that digital village construction significantly enhances county-level economic growth, with a more pronounced effect observed in southern regions, eastern regions, and non-agricultural counties. The primary mechanism through which digital village construction drives economic growth at the county level is by promoting entrepreneurship. This study not only points out the key to digital village construction in China, but also enriches the theoretical research on digital village construction for economic growth. However, due to data limitations and the short time span of digital village construction, the results of the study are correct only for the period 2018–2021 in China. As digital village construction continues to progress, its impact on economic growth is likely to be even greater.

Guiding and encouraging farmers to adopt low-carbon agricultural technologies is highly significant for reducing greenhouse gas emissions, mitigating climate change, and achieving agricultural production development and food security. This study used survey data from 1843 grain farmers in 14 provinces of China to empirically analyze the impact of non-farm employment experience and risk preferences on grain farmers’ low-carbon agricultural technology (LCAT) adoption. The results show that for grain farmers: (1) non-farm employment experience significantly promoted the adopting of LCAT. The probability of adopting LCAT by those with non-farm experience is 23.5% higher than those without. (2) Non-farm employment experience reinforced their risk preferences and promoted the adoption of LCAT. The adoption probability of LCAT of those with high-risk preferences was 6.1% higher than those with low-risk preferences. (3) The impact of non-farm employment experience on adopting LCAT was more significant for those with high education and training. Non-farm employment experience outside the province and employment experience in the tertiary sector while working outside significantly affect grain farmers’ LCAT adoption.

Aging is an important trend in the global demographic, with rural population aging becoming a significant challenge due to its faster pace and profound implications. Although the most significant impact of the aging agricultural labor force occurs in agricultural production and land use, little is known about their relationship. Based on the 2010–2018 data from the Chinese Family Panel Studies, this study uses the panel probit model to analyze the impact of the aging agricultural labor force on land transfer and tests its influence mechanism from the aspects of health effect and pension insurance effect. The results show the following: (1) there is an inverted U-shaped relationship between the aging of the agricultural labor force and land rent-in—with the deepening of the aging of the agricultural labor force, the aging of the agricultural labor force shifts from promoting land rent-in to inhibiting it; (2) there is a U-shaped relationship between the aging of the agricultural labor force and land rent-out—with the deepening of the aging of the agricultural labor force, the aging of the agricultural labor force shifts from inhibiting land rent-out to promoting it; and (3) the impact of the aging agricultural labor force on land rent-in and rent-out is significantly affected by farmers’ health levels, however pension insurance does not play a significant moderating role. Therefore, the government should strengthen the land transfer market and improve the level of pension insurance for the elderly rural agricultural labor force.

Under the dual challenges of global downward economic pressure and the COVID-19 pandemic, studying the impact of local government fiscal pressure on public health is a meaningful endeavor. First, this paper analyzes the impact of local government fiscal pressure on public health and clarifies its impact mechanisms. Second, by utilizing panel data of 31 Chinese provinces from 2000 to 2020, two-way fixed-effects and mediating-effects models are developed to identify the effects and impact mechanisms of local government fiscal pressure on public health. The results show that local government fiscal pressure can be detrimental to public health through three main mechanisms: reducing public health fiscal expenditures, hindering industrial structure upgrading, and exacerbating environmental pollution. Heterogeneity analysis finds that the negative effects of local government fiscal pressure on public health mainly exist in Central and Western China. Accordingly, three policy implications are proposed: optimizing the fiscal system, accelerating industrial upgrading, and improving the appraisal system of local officers.

Cost sharing and cost shifting mechanisms are of vital importance in a prospective payment system. This paper employed the difference-in-differences method to estimate the impacts of a per diem system with inverted-U-shape rates on medical costs and the length of stay based on data from a health insurance institution. The supply side cost sharing mechanism worked so that the new payment system significantly reduced medical costs by 17.59 percent while the average length of stay varied little. After further analyzing the mechanism, we found that heterogeneous effects emerged mainly due to the special rates design. The reform decreased the cases that incurred relatively high medical costs and lengths of stay. However, cost shifting existed so that physicians could be motivated to provide unnecessary services to the patients who should have been discharged before the average length of stay. Therefore, payment rates in the per diem system require a sophisticated design to constrain its distortion to medical service provision even though medical expenditures were successfully contained.

Classification-based forest management (CFM) is generally regarded as an important political means of achieving sustainable forest development. However, in the upsurge of publicly managed forest devolution, the impact of CFM policies on forestland restoration remains uncertain and needs to be explored. This study contributes to the scant literature on this topic in China, where CFM has long been implemented based on the ecological welfare forestland (EWF) certification program. We use provincial data from China to examine the relationship between EWF-certified areas and forest restoration. Based on inter-provincial panel data from the third to the ninth consecutive forest resource inventories in China (1984–2018), we use a dynamic spatial autoregressive model to analyze the impact of forest classification management on forest restoration. The results show that, contrary to appearances, increasing EWF-certified areas promotes forest restoration. However, after controlling for other possible influencing factors, increasing EWF-certified areas plays a minimal role in promoting forest restoration and regrowth by inhibiting investment in forest management and even has a negative impact on forest restoration in the southern collective forest area.