Based on the microdata of 11,547 farmers from the China Labor Dynamics Survey (CLDS) database in 2017, an ordered multi-classification logistic model was constructed to empirically test the impact of social capital (i.e., social networks, social participation, and social trust) on farmers’ willingness to adopt agricultural technology. The moderating effect of demographic changes (i.e., the number of instances of hukou migration) on social capital and farmers’ willingness to adopt new agricultural technology was further investigated. The results show that the following: (1) Social trust has a significant positive impact on farmers’ willingness to adopt new agricultural technologies, while social participation has no significant impact on farmers’ willingness to adopt new technologies. (2) Social networks influence farmers’ technology adoption behavior differently, e.g., the scope of relatives’ wedding gifts has a significant and positive influence on farmers’ technology adoption behavior, while the scope of non-relatives’ wedding gifts has no significant influence on farmers’ technology adoption behavior. (3) Demographic change plays a moderating role in the impact of social capital on farmers’ willingness to adopt new agricultural technologies. In other words, the greater the number of instances of hukou migration, the less the promoting effect of social capital on farmers’ willingness to adopt agricultural technology. (4) In the eastern and central regions of China, social capital has a significant positive impact on farmers’ adoption of new agricultural technologies. In the western region of China, social capital has a significant negative impact on farmers’ adoption of new agricultural technology. In the northeast region of China, social capital has no significant impact on farmers’ adoption of new agricultural technologies. Social capital and population changes are important factors that affect farmers’ willingness to adopt new agricultural technologies. Therefore, attention should be paid to cultivating and promoting farmers’ social capital to improve farmers’ willingness to adopt new agricultural technologies.

There is serious debate among researchers regarding the sustainability implications of economic prosperity and energy dependence. Energy consumption has a critical linkage with economic growth, but it also degrades environmental quality. Therefore, it is important to investigate the relationship between economic growth, the energy mix, and environmental sustainability. However, empirical literature utilizes narrow variables to capture environmental sustainability. Because of this, this research introduces a new environmental sustainability variable using entropy weighting and combining deforestation, household carbon emissions, and life expectancy. This study examines the relationship between environmental sustainability, economic growth, and other selected variables using data from 2002 to 2019 for the G20 and its high-, upper-, and low-middle-income member countries. Since shocks in one G20 country can affect another, this study uses the Augmented Mean Group (AMG) technique for empirical analysis. The results of this study indicate that Gross Domestic Product (EG) and its square term did not support the Environmental Kuznets Curve (EKC) theory. The energy mix has a positive impact on the environmental sustainability gap across all the samples except for the upper-middle-income group. Foreign direct investment positively affects this gap, while population growth has no significant impact. These findings demonstrate that policymakers should support environmentally friendly and clean energy sources to foster long-term economic growth and sustainability.