Given the prevalence of part-time farming behaviors in rural households, studying the impact of part-time farming behaviors on grain output is of great practical significance. Using a panel dataset of 5629 Chinese national rural fixed observation point data from 2009 to 2015, this paper used the Propensity Score Matching-Difference in Differences method (PSM-DID) to examine the impact and dynamic effect of rural household’s part-time farming behavior on grain output. In addition, the paper also aims to explore the mechanism of how part-time farming affects grain output by running an OLS in an intermediary effect model. We analyzed the data from two aspects: the effect of rural households’ part-time farming decisions on grain output and the relationship between the income from rural households’ part-time farming and grain output. After accounting for the control variables, the results showed a significant positive correlation between rural households’ part-time farming behavior and grain output, with an influence coefficient of 0.304 tons increase in total grain output. While rural households’ part-time farming behavior inhibited grain output over the short term, it ultimately promoted grain output in the long run. The promotion effect increased with the duration of the rural households’ part-time farming. Moreover, the degree of part-time farming and its impact on grain output are mediated by agricultural labor inputs and agricultural technology inputs. Hence, differences in the employment times of rural households’ part-time farming can lead to varying results in grain output. To improve the efficiency of grain output, this study recommends that the government implement policies that promote orderly rural households’ part-time farming behavior.

Although absolute poverty has been eliminated in rural China, multidimensional poverty has an unstoppable impact on the self-rated health of rural households through multiple dimensions. This study constructed a moderated mediation model with multidimensional poverty as the independent variable to explore the impact on rural households’ self-rated health, social capital as a mediating variable, and family care as a moderating variable. We used the survey data of 382 sample out-of-poverty rural households in Jiangxi, China, in 2020. Our results indicated that multidimensional poverty had a detrimental impact on the self-rated health and social capital of rural households, both of which were significant at the 1% level (β = −0.751, t = −4.775, and β = −0.197, t = −7.08). A test of the mediating effect of social capital using the mediation model found the mediating effect accounting for 84.95% of the entire effect of multidimensional poverty on rural households’ self-rated health. Further, the interaction term between family care and multidimensional poverty and its beneficial effect on social capital as well as the interaction term between family care and social capital and its negative effect on rural household’ self-rated health are both statistically significant at the 1% level (β = 0.558, t = −5.221 and β = −2.100, t = −3.304). It is revealed that multidimensional poverty affects rural households’ self-rated health through social capital and that family care moderates the mediating pathway. Family care exacerbates the negative effect of multidimensional poverty on rural households’ self-rated health and weakens the beneficial effect of social capital on rural households’ self-rated health. The lower (higher) the level of family care, the more significant the positive (negative) effect of social capital on rural households’ health. Therefore, rural households should prioritize building social capital and shifting the responsibility for family care. First, through enhancing housing infrastructure and establishing cultural and educational initiatives, households can improve their viability. Second, increasing engagement in group activities will enhance social networks and boost interpersonal connections. Finally, to lessen the stress on family caregivers, building socialized care services can cover the gap in family care.

With the full penetration of the Internet, the Internet has had a great impact on the production and life of rural residents. The article takes a rural residents’ group as its research object to explore the impact mechanism. Leveraging data from the Chinese Family Panel Studies (CFPS) in 2016, we employ a multivariate ordered logit model as an empirical approach to delve into the various dimensions of Internet usage. By examining different facets of Internet utilization, we aim to assess the effects of these distinct uses on the well-being of rural residents. Furthermore, we investigate the mediating role of social capital in understanding the collective well-being of this demographic. The findings of this study are as follows: (1) The utilization of the Internet yields a positive impact on the well-being of rural residents. (2) Social networks exhibit a significant positive influence on the well-being of rural residents; social solidarity demonstrates a significant negative impact on the well-being of rural residents. Additionally, social trust is found to have a significant negative effect on the well-being of rural residents. (3) Regarding mobile phone access, we identify a positive and significant effect on the well-being of rural residents when mediated by social networks and social trust. In contrast, social mutual aid does not exhibit a significant mediating effect. Among the patterns of mobile phone usage, social network and social mutual aid within the realm of social capital emerge as intermediate variables that affect the well-being of rural residents through Internet usage. However, it is worth noting that social trust does not have a significant effect in this regard. These results contribute to our understanding of how Internet usage and social capital interact to shape the well-being of rural communities.

Recognizing the effect of the digital economy on residents’ health can transform technological dividends into health and well-being and provide the basis for the construction of a “health-oriented” digital society development path. This paper explores the direct impact of the digital economy on residents’ health and its mechanism by constructing a digital economic development index and combining data from the China Family Panel Studies (CFPS). The digital economy has a health-improving effect. At the individual level, the mechanism is to accumulate social capital and improve the quality of employment, whereas at the regional level, the mechanism is to promote the equalization of basic public services and improve the quality of the environment. The effectiveness of government governance plays a beneficial moderating role in this mechanism. The heterogeneity analysis shows that the digital economy had a more significant effect on the central, western, rural, and economically underdeveloped cities, as well as on males and the low-health group. Further analysis reveals that the digital economy increases intergenerational health mobility and helps alleviate health inequalities. This paper not only enriches the study of health determinants but also provides a reference for collaboration between global digitalization and health governance.

This study uses field survey data from 382 families in the year 2020 in Jiangxi province, China, to explore the effects of land lease and labor migration, a well-known occurrence in China, on rural households’ multidimensional poverty status. We used the A-F method to measure the household’s multidimensional poverty in terms of health, education, income, living standard, and social relations. The Bootstrap Test approach, which worked well with our data, was used to build our mediating effect models while taking into account the influence mechanisms of land leasing and multidimensional poverty. According to our findings, 76.70% of sample homes experience multidimensional poverty at the threshold of 0.33. The reduction of multidimensional poverty is significantly aided by both leasing in and leasing out land. Land lease out and land lease in, however, have asymmetrical effects on multidimensional poverty alleviation, with the proportion of land lease out being 1.147 without control variables and the proportion of land lease in being 0.969 without control variables. Land lease in and lease out have positive effects on the multifaceted alleviation of poverty due to the mediating effect of labor migration. For policymakers to develop and put into action more relevant policies to help multidimensional poverty alleviation, our analysis offers critical insights.