The digital economy is an important engine for promoting green economic development, and the integration of the digital and real economies can accelerate the transformation of the real economy. In order to explore the multifaceted influence of digital economy on forestry green total factor productivity and its specific presentation form, based on the panel data of 277 cities in China from 2013 to 2019, this paper first used the super SBM model to measure the level of forestry green total factor productivity and adopted the entropy method to measure the level of the digital economy in each region. Secondly, the influence and mechanism of the digital economy on green total factor productivity in forestry were explored by using fixed-effect and intermediate-effect models, and the heterogeneity of the digital economy on forestry green total factor productivity was analyzed based on different regional classification methods. Finally, the spatial spillover effect of the digital economy was explored in depth by the spatial Durbin model. The results are as follows: firstly, there is a significant inverted U-shaped relationship between the digital economy and forestry green total factor productivity, which first promotes and then inhibits. Secondly, the relationship between the digital economy and the level of urban green innovation shows a positive U-shaped relationship, first inhibiting and then promoting, and can have an indirect impact on forestry green total factor productivity by promoting the level of green innovation. Third, China is still on the left side of the inverted U-shaped relationship between the digital economy and forestry green total factor productivity, i.e., it is at a stage where the digital economy can significantly contribute to forestry green total factor productivity. Fourth, the effect of the digital economy on green total factor productivity in forestry is heterogeneous in the east, central, and west and is more pronounced in regions with faster economic development or rich natural resources. Fifth, the impact of the digital economy on forestry green total factor productivity has a significant positive spatial spillover effect.

Getting rid of multidimensional poverty is both the people’s wish and the direction of governance. Based on 2018 China Household Tracking Survey (CFPS) data, this paper identifies household multidimensional poverty in rural areas using a combination of the MPI index and the A-F method. The relationship between social capital and multidimensional poverty was also empirically analyzed using a Logit model. The results showed that: (1) 1599 multidimensional poverty households were identified, the incidence of multidimensional poverty was 24.94%, and the multidimensional poverty index was 0.103. In terms of poverty incidence, the three highest indicators of poverty incidence are adult education, health, and chronic diseases, reaching 42.06%, 37.65%, and 29.90%, respectively, and mainly concentrated in the education and health care systems. (2) Social capital can significantly reduce the probability of multidimensional poverty in rural households. Among them, social network significantly and negatively affects the occurrence of multidimensional poverty in rural households, social trust in neighbors has a significant negative effect on multidimensional poverty in rural households at the 1% level, and social prestige is positively related to multidimensional poverty in rural households. (3) Age of household head, household size, and income from working outside the home are significantly associated with multidimensional poverty in rural households. This paper expands the scope of social capital theory research and provides new perspectives and empirical evidence for alleviating multidimensional poverty.

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.

In the framework of China new urbanization construction, migrant workers are of great significance for urban sustainable development. Based on the data of CLDS2016, we used the multi- -ordered Logistics model to effectively explore the influence of migrant workers ’ language use on the urban settlement will. The research results showed that the mastery of the urban dialect and the language used after work had a significant impact on the willingness of the migrant workers in the urban settlement, while the language used at work had no significant impact on the migrant workers’ willingness to settle in cities. Therefore, policy implications are proposed on improving the social integration of migrant workers, enhancing the sense of belonging, and removing the obstacles and doubts in the process of urban settlement.

The farmland lease is an important way to improve the scale of farmland management and agricultural modernization. Based on survey data for 578 rural households in Jiangxi Province, a Tobit model, and intermediary effect analysis method were used to determine how family care affects farmland lease by influencing off-farm employment. The main conclusions were as follows: (1) When more members of a family needed care, more rural households tended to rent in farmland. Care for the elderly and care for children aged 0–4 years had no significant impact on farmland lease, but care for children aged 5–15 years had a significant and positive influence on farmland rent-in. (2) The number of members in need of care within the family did not significantly affect farmland rent-out, but the care of children aged 0–4 years significantly reduced the possibility of farmers renting out their farmland. (3) Family care reduced the possibility of farmers renting out land but promoted land rent-in by inhibiting labour migration. (4) The intermediary effect of out-county off-farm employment in the influence of family care on farmland lease was significant, but the intermediary effect of local off-farm employment was not significant.