Zhao Ding

Understanding how farmers’ risk attitudes drive their borrowing behavior and agricultural production decisions is of significant importance for promoting rural financial innovation and sustainable agricultural development. Based on experimental and survey data from 447 agricultural operators in China (Sichuan, Chongqing, and Guizhou provinces), this study employs the “Bomb Risk Elicitation Task” to objectively quantify risk attitudes, innovatively utilizing a 3D-tensor-based neural network as a methodological cross-validation tool. To account for unobservable sample selection bias, we employ joint estimation models to systematically evaluate the impact of risk tolerance across the complete credit decision chain. The findings reveal a baseline of profound risk aversion among farmers. However, individuals with higher risk tolerance exhibit significantly stronger borrowing intentions and secure larger loan amounts. Marginal effects analysis demonstrates structural demographic heterogeneity: this risk-driven borrowing is highly pronounced among younger farmers and smaller households, whereas older and larger households exhibit attenuated responsiveness to risk attitudes. Furthermore, conditional on borrowing, higher risk tolerance drives a significant preference for formal credit channels and productive agricultural investments, ultimately leading to improved post-loan income levels. In contrast, farmers with lower risk tolerance show a preference for conservative management strategies and greater reliance on informal lending channels.

Introduction: In the digital economy era, the application of digital technologies plays a crucial role in strengthening the food supply chain, especially in ensuring food security. The study of how the digital economy impacts the resilience of the food supply chain is of great practical significance.Methods: Based on provincial data from China from 2008 to 2023, this research employs fixed effect, mediation effect, and threshold models. These models are utilized to explore the mechanism through which the digital economy improves the resilience of the food supply chain.Results: The findings indicate that the digital economy has a significant positive effect on enhancing the resilience of the food supply chain. This positive relationship remains stable even after considering potential endogeneity problems. Specifically, the impact of the digital economy is more prominent in major food—producing regions, showing their advantages in using digital development to boost supply chain stability and efficiency. Additionally, information technology adoption acts as an important mediating factor in the relationship between the digital economy and supply chain resilience, and there is a threshold effect of fiscal investment in science and technology on the impact of the digital economy on supply chain resilience.Discussion: The results suggest that to fully utilize the potential of the digital economy, accelerate the digital and intelligent upgrade of the food supply chain, strengthen its resilience, and promote high—quality agricultural development, the government should take actions. These include accelerating the construction of digital infrastructure, promoting the digital transformation of the food industry, strengthening regional cooperation, and enhancing the resilience of the food supply chain to ensure food security.

Introduction: Although rural industrial integration is a crucial pathway for advancing the revitalization of rural economies, it continues to grapple with financial challenges. This paper delves into the theoretical underpinnings of how capital marketization influences rural industrial integration.Methods: Using panel data from China’s provinces spanning the years 2010 to 2020, a comprehensive index of rural industrial integration is constructed from the vantage point of a new development paradigm. The paper employs the system GMM method to empirically investigate the impact of capital marketization on rural industrial integration and to dissect its transmission mechanisms. Additionally, a threshold regression model is applied to explore the specific patterns of the nonlinear relationship between the two variables.Results and discussion: The study’s findings reveal that the degree of rural industrial integration is significantly and positively influenced by its previous level, demonstrating an accumulative effect wherein the prior level of integration lays the groundwork for future advancements. The influence of capital marketization on the degree of rural industrial integration is characterized by a non-linear relationship, adhering to a “U-shaped” curve. Below the inflection point, the development of capital marketization is detrimental to rural industrial integration, whereas above this point, it exerts a positive influence. Currently, China’s overall level of capital marketization is positioned beyond the inflection point, indicating substantial potential for enhancing industry integration in rural China. In addition, the study indicates that at very low levels of economic development, capital marketization does not affect the development of rural industries. As the economic development level rises, so does the impact of capital marketization on rural industrial integration.

Amidst global sustainability challenges, green finance emerges as a crucial instrument for advancing sustainable development, garnering increasing attention for its pivotal role in fostering high-quality economic development (HQED), particularly within the dynamic economic landscape of China. This study delves into the nexus between green finance and HQED across 30 Chinese provinces from 2012 to 2021. Employing the entropy method, indices for green finance and HQED index system are calculated, and their interaction is analyzed through a panel data model, incorporating tests for moderating effects of FinTech and green technological innovation, as well as assessing the heterogeneity across diverse regions. The findings highlight green finance’s significant role in enhancing HQED, with notable regional disparities. Specifically, the eastern region shows the strongest impact, followed by the central region, while the western and northeastern regions exhibit weaker influences. The study also identifies FinTech and green technological innovation as pivotal moderators, amplifying green finance’s positive effect on HQED. These insights underscore green finance’s importance in driving sustainable economic growth and highlight the necessity for region-specific strategies to optimize its impact. Policy recommendations based on these findings include prioritizing the development of green finance, formulating region-specific strategies, and leveraging the catalytic roles of FinTech and green technological innovation to enhance the efficacy of green finance in achieving HQED.

Microfinance has gained significant importance in supporting the livelihoods of individuals in developing economies. This paper examines the influence of self-employment on preferences for microfinance, based on the hypothesis that self-employment choices and participation in microfinance share the same decision-making ability. The analysis utilizes data from a recent survey conducted in rural China, employing a generalized multinomial logit model (GMNL) to account for both preference heterogeneity and scale heterogeneity. This model allows us to investigate the choice probabilities and the impact of different types of self-employment on preferences for microfinance attributes. The empirical findings indicate that engaging in self-employment contributes to a sense of reassurance regarding preferences for microfinance among rural respondents. Specifically, non-agricultural self-employment has a positive effect on this preference, whereas agricultural self-employment has a negative effect.

Introduction: Food production stands as a critical global concern necessitating comprehensive investigation. This study utilizes provincial-level data from China to explore the intricate relationships between farmland transfer, agricultural loans, and grain production, with the aim of shedding light on the complexities of these dynamics.Methods: A two-way fixed effects model and instrumental variable approach are applied to assess the interplay between farmland transfer, agricultural loans, and grain production. These methods provide a robust framework for understanding the complex relationships among these variables.Results and discussion: The study reveals a notable positive correlation between farmland transfer and grain production. Conversely, agricultural loans demonstrate a significantly negative impact on grain production. However, the positive interaction term between farmland transfer and agricultural loans suggests a nuanced relationship. While profit-driven financial activities may not inherently favor grain production, they contribute to more efficient utilization of farmland resources, ultimately promoting grain production. The findings underscore the significance of continued government support for rural land system reform and active guidance of farmland transfer. It is emphasized that a moderate-scale operation of farmland is crucial for finance to play a lubricating and catalytic role. Furthermore, there is a need to guide agricultural finance towards investing in medium and long-term projects of agricultural production. Attention is also directed to preventing potential food crises arising from the phenomenon of “non- farming” associated with agricultural loans.

The payment and clearing system can objectively record the operation of funds for social and economic activities, and the use of payment and clearing data can be made to monitor regional economic changes sensitively. Employing panel data of cities and prefectures in Sichuan Province from 2010 to 2021, this article employs econometric analysis to examine the link between payment and clearing data and the regional economy. The paper’s focus includes the payment and clearing system and economic indicators. The increase in the total amount of payment and clearing data has a significant positive correlation with digital economic development. Only by regression between the total amount of payment and clearing and regional gross domestic product (GDP), it can be found that every 1% increase in payment and clearing can increase regional GDP by 0.476%. After controlling factors such as important production factors, openness, and government intervention, the elasticity coefficient is still 0.1%, and the correlation is significant. Therefore, the amount of payment and liquidation is a valuable predictor of regional economic development. And thus providing Intelligent decision-making references for the policy formulation and strategic planning of governmental departments and regulatory agencies.

Farmland abandonment has been a major concern for policymakers in most developing nations since it is associated with food security and poverty alleviation. In view of this, assessing its potential determinants is essential and timely. This study examines the relationship between financial literacy and farmland abandonment in Ghana using survey data (N = 572). The study employs endogenous switching regression (ESR) for its estimation. Our findings show that financial literacy is low among rural dwellers. Also, the findings depict that financial literacy is positively related to farmland abandonment reduction. Moreover, different household groups depict a heterogeneous relationship between financial literacy and farmland abandonment. Thus, the association between financial literacy and farmland abandonment reduction is more pronounced for low-income farm households and female farmers. We recommended that financial literacy programs can be organized or shown on national radios and television to provide financial education to the country’s residents. Our findings could offer some implications for stimulating agricultural intensification while ensuring rural advancements.

Prior studies explored the production and technical efficiency of fish farms and farmers from the perspectives of factors such as credit access and cooperative membership. We focused on the chronic non-communicable diseases (NCDs) of household members and their quantitative impacts on fish farm production efficiency, based on data of earthen pond fish farms from two regions (Bono East and Ashanti) in Ghana. A data envelopment analysis (DEA) and the IV Tobit technique were employed for the study’s analysis. From the study’s observations, we draw the following conclusions. We found that the NCDs of household members indeed reduce farm production efficiency, and the heterogeneous impact of the NCDs of female members on farm production efficiency was more prominent than that of male members. Insights from this study suggest that the national government should provide farmers with the necessary medical care through the provision of subsidized health insurance, which can facilitate access to healthcare services. Moreover, NGOs and governments should encourage health literacy, i.e., organizing programs aimed at educating farmers on NCDs and their impact on agriculture.