This article examines the influence of social capital on the sustainable livelihood ability of rural households who are out of poverty, in order to promote the sustainable development of their livelihood. Based on the survey data of 371 out-of-poverty households in rural Jiangxi, we analyzed the relationship between social capital and households’ sustainable livelihood ability using “Ordinary Least Square (OLS) + robust standard error” regression models and quantile regression models. Households’ social capital was measured from the following three dimensions: social network, social participation, and social trust. The benchmark regression models showed that social capital index, social network, and social participation all had a significant positive effect on the sustainable livelihood ability of out-of-poverty households. However, the impact of social trust on sustainable livelihood ability was not significant. In addition, the quantile regression analysis results showed that social capital index, social network, social participation, and social trust all contributed the most to households with a low sustainable livelihood ability. Therefore, it is suggested to improve the social capital accumulation of out-of-poverty households from multiple dimensions, so as to enhance the sustainable livelihood ability of households and consolidate poverty-alleviation achievements.

As the direct subject of collective forestland tenure reform, increasing farmers’ income is an important goal of collective forestland tenure reform and the key to sustainable management of forest resources. Based on the survey data of 1276 rural households in 18 counties in 9 provinces, we construct a theoretical analysis framework of the impact of collective forestland tenure reform on household income from the perspective of rural household differentiation and elucidate the mechanism of the effect of collective forestland tenure reform on household income in the context of the rural household differentiation. The results of the empirical analysis show that, firstly, the collective forestland tenure reform significantly increases the total income, forestry income, and off-farm income of rural households, but the effect of income increase differs significantly among different groups of rural households with different income levels, showing the characteristic of “benefitting the rich more than the poor”. Secondly, as rural household differentiation deepens, there is a moderating effect of rural household differentiation in the income-raising effect of collective forestland tenure reform, i.e., collective forestland tenure reform has a stronger marginal effect on the forestry income of shallowly differentiated rural households and a weaker marginal effect on their off-farm income compared to deeply differentiated rural households. Finally, the income increase effect of collective forestland tenure reform shows significant situational dependence in both forestland operation scale and human capital endowment. The income-raising effect of collective forestland tenure reform is stronger for forestry income of large operation scale farmers, while it is stronger for off-farm income of small operation scale farmers; the income-raising effect of collective forestland tenure reform is stronger for farmers with high quantity and quality human capital endowment than for farmers with low quantity and quality human capital endowment. Therefore, this paper attempts to provide a policy adjustment idea to deepen the policies related to collective forestland tenure reform by starting from the farmer differentiation side.

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.

We analyze the impact of smartphone usage on multidimensional poverty reduction. Utilizing the A-F approach, we compute a multidimensional poverty index based on five dimensions: education, health, income, living standard, and labor force. This index categorizes multidimensional poverty into three levels: Vulnerable Multidimensional Poverty Index (VMPI), General Multidimensional Poverty Index (GMPI), and Extreme Multidimensional Poverty Index (EMPI), following MPI criteria. Furthermore, we investigate the mediating role of social capital in the smartphone-multidimensional poverty relationship through a mediating effects analysis. We used the survey data of 382 sample out-of-poverty rural households in Jiangxi, China, in 2020. Our results indicated that: (1) Education (37.80%), labor force (29.7%), and health (20.40%) were identified as the primary contributors to multidimensional poverty. (2) Increasing deprivation categories correlated with declining multidimensional poverty index, following an inverted U-shaped pattern. (3) Smartphone usage significantly reduced VMPI (57.6%), GMPI (52.6%), and EMPI (5%). (4) Social capital fully mediated EMPI reduction through smartphones (91.67%), and partially mediated VMPI (14.09%) and GMPI (20.84%) reduction. These insights inform targeted policy formulation for rural multidimensional poverty reduction.

This study analyzes the influence mechanism of migration on farmers' forestland transfer behavior by using instrumental variable‐Probit and instrumental variable‐Tobit models based on survey data of 505 households in 50 villages in 10 sample counties in Jiangxi Province. The results show that the farmers' willingness to transfer forestland is generally not high, but there is a great difference in the influence of intra‐county migration and outside‐of‐county migration on the transfer behavior of farmers. Outside‐of‐county migration promotes the renting out of forestland and inhibits renting it in, whereas intra‐county migration does not affect either. In addition, households' human capital, forestland resource endowments, policy systems, and locational environment factors all have different degrees of influence on farmers' transfer behavior. According to the analysis, improving rural laborers' job skills through training can deepen the reform of collective forestland. Recommendations for Resource Managers This study uses econometric models to reflect the influence of intra‐county migration and outside‐of‐county migration on households' forestland transfer and provides a foundation for the sustainable development of forestland. The factors affecting the renting in or out of forestland strongly differ according to intra‐ and outside‐of‐county migration. Outside‐of‐county migration promotes the renting out of forestland and inhibits renting it in, whereas intra‐county migration does not affect either. To encourage forestland transfer and achieve sustainable forest development, managers should concentrate on improving the rural laborers' job skills through training, continuing the reform of collective forestland, and coordinating the relationship between farmers and forestland.