In recent years, the changing climate has become a major global concern, and it poses a higher threat to the agricultural sector around the world. Consequently, this study examines the impact of changing climate and technological progress on soybean yield in the 13 major provinces of China, and considers the role of agricultural credit, farming size, public investment, and power of agricultural machinery from 2000 to 2020. Fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) are applied to assess the long-run effect, while Dumitrescu and Hurlin’s (2012) causality test is used to explore the short-run causalities among the studied variables. The results revealed that an increase in the annual mean temperature negatively and significantly affects soybean yield, while precipitation expressively helps augment soybean yield. Furthermore, technological factors such as chemical fertilizers accelerate soybean yield significantly, whereas pesticides negatively influence soybean yield. In addition, farming size, public investment, and power of agricultural machinery contribute remarkably to soybean yield. The causality results endorse that chemical fertilizers, pesticides used, agricultural credit, public investment, and power of agricultural machinery have bidirectional causality links with soybean yield. This study suggests several fruitful policy implications for sustainable soybean production in China.

Nutritional status plays an indispensable role in enhancing human capital and preventing the return to poverty. In the context of the three-child policy and the aging society in China, intergenerational care will inevitably become a core component of family support. Thus, this paper evaluates the impacts of intergenerational care behavior on nutritional intake in Chinese rural residents from the perspective of household consumption. The study’s data is from the China Family Panel Studies (CFPS) (2010–2014), and, the fixed effect model and analyses are applied to achieve the study’s objective. The results reveal that rural residents with intergenerational family care behavior have significantly higher food diversity. Thus, Chinese rural residents with intergenerational care consumed 22.4% more food. A possible mechanism is that intergenerational care improves young mothers’ labor participation and income, thus optimizing their dietary structure. Moreover, there was heterogeneity concerning the nutrition intake among rural residents in different geographic and family net income groups. Finally, the robust check is consistent with the baseline regression results. In summary, governments should fully affirm the elderly contribution to families to give full play to the elderly family benefit maximization.

Amid global population growth and the pressures of climate change, traditional factors in driving grain production are increasingly inadequate. In this context, this study utilizes panel data from 31 provinces in China (2001–2022) to examine the impact of digitalization (DG), technological innovation (TI), and financial innovation (FI) on grain production (GP). Specifically, the study constructs a comprehensive evaluation framework where DG is measured by mobile communication penetration, TI by agricultural R&D expenditure, and FI by the loan-to-GDP ratio of financial institutions. Employing a fixed effects model, the empirical results demonstrate that DG, TI, and FI yield significant positive returns on GP, with elasticity coefficients of 0.262, 10.675 and 6.589, respectively. Furthermore, synergistic effects are observed, where the interaction between DG and TI (coefficient 0.0402 × 10⁻³) and between DG and FI (coefficient 0.221 × 10⁻²) significantly amplify production capacity. Channel analysis reveals that DG and TI promote GP by fostering agricultural industrial agglomeration, TI and FI by advancing agricultural mechanization, and DG and FI by expanding the agricultural insurance scale. Heterogeneity analysis indicates that these factors significantly boost GP in major grain-producing regions but are insignificant in grain production–marketing balanced regions. In major grain-consuming regions, DG has an adverse effect, TI has no significant impact, and FI has a positive effect. Additionally, in non-humid regions, the positive impacts of DG, TI, and FI on GP are greater.