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.

The “time-space compression” effect of high-speed rail (HSR) has effectively improved the accessibility of the cities and has had a profound impact on tourism. This study explores the impact of HSR on tourism development in cities along HSR lines from the perspective of transfer of transport advantages, then evaluates the impact of HSR on tourism development using panel data of 286 cities in China from 2005 to 2013 by the difference-in-differences (DID) method. The empirical results show that the opening of HSR has significantly increased the tourism revenue and tourist arrivals. These results are still holds after considering endogenous HSR lines placement, and by various robustness checks. Further analysis of nodal effect shows that node cities experienced greater growth in tourism revenue than non-node cities. The analysis of mechanism found that tourism development in node cities relied on hotel industry, while tourism development in non-node cities relied on scenic spots industry. The findings of this study validate the role of HSR as a catalyst for urban tourism development, and reveal the comparative advantages of tourism in different cities under the influence of HSR. This study has important reference value for the development of tourism industry policies in cities along and around HSR lines.

This study analyzes the potentially differentiated impacts of actual and perceived tenure security on rural households' forestland transfer behavior. Logit and Tobit models were estimated using repeated survey data from 505 households in 50 villages of Jiangxi Province during 2017–2018. The results show that there is a great difference in the influence of actual and perceived tenure security on the transfer behavior. Issuing forest tenure certificates promotes the renting out of forestland by households but has no significant effect on forestland renting in. Meanwhile, perceived tenure security has a significant effect on forestland transfer behavior. Households' understanding and evaluation of the existing tenure policy also has a significantly positive impact on household's rent‐out behavior. Further, the logging quota system has a significantly negative effect on household's renting in and out behavior. Our analysis suggests that the government should strive to improve the awareness of rural families regarding forest tenure policy and that the logging quota should be modified to incentivize farmers' active participation in forest management.

The construction and development of digital infrastructure have emerged as a crucial indicator of national competitiveness, which holds significant importance in driving the sustained growth of the national economy and the comprehensive advancement of society. This paper explores the impact of digital infrastructure on farm households’ scale management, aiming to reveal the role and potential of digital technology in agricultural modernization. Additionally, it seeks to offer a scientific foundation for the government to formulate agricultural policies and advance agricultural modernization. Using the OLS (Ordinary Least Squares) model, moderating effect model, and other methods, this study investigates how digital infrastructure affects farm households’ scale management based on micro-level research data of 2510 farm households from the CRRS (China Rural Revitalization Survey). The following conclusions are drawn: Firstly, the enhancement of digital infrastructure can motivate farm households to expand the land management area and increase the unit output of land. Secondly, farm households’ digital literacy positively moderates the effect of digital infrastructure on their land unit output; moreover, digital skills training for farm households exhibits a positive moderating effect on the influence of digital infrastructure on their management area. Finally, there is a heterogeneity in the impact of digital infrastructure on farm households’ scale management. Specifically, the promotion of farm households’ scale management is stronger in plain areas and weaker in hilly and mountainous areas; stronger for middle-aged and older and small-scale farm households; and weaker for youth groups and large-scale farm households. Based on this, this paper suggests increasing the investment in digital infrastructure construction, improving farm households’ digital literacy, carrying out digital skills training, and formulating differentiated regional policies for reference.

Investigating the impact of rural digitalization on agricultural carbon emissions contributes to achieving carbon neutrality goals and facilitates the green transformation of agriculture with enhanced efficiency. Based on panel data from 31 provincial-level regions in China spanning 2005 to 2022, this study employs a dynamic panel model to analyze the influence of rural digitalization on agricultural carbon emission intensity. Heterogeneity analysis, mechanism testing, and spatial effect examination are also conducted. The main findings are fourfold. (1) Rural digitalization effectively promotes the reduction of agricultural carbon emissions. (2) Heterogeneity analysis revealed that the effect of rural digitalization on lowering agricultural carbon emission intensity is particularly significant in production-marketing balanced regions. (3) The carbon emission reduction effect of rural digitalization is primarily realized through the scaling of agricultural operations, the accumulation of human capital, and the improvement of total factor productivity. (4) A positive spatial correlation exists in the agricultural carbon emission intensity across provinces, and the inhibitory effect of rural digitalization on agricultural carbon emission intensity exhibits spatial spillover effects. Therefore, to accelerate rural digitalization and advance agricultural carbon emission reduction, it will be essential to promote the scaling of agricultural operations, guide farmers in adopting advanced technologies, and enhance their ability to utilize digital tools.