Impact Mechanism of Contracted Land Transfer on Agricultural Eco‐Efficiency in Metropolitan Areas: Shanghai as a Case Study

Developing green and low-carbon agriculture is an important and effective way to promote farmers’ income growth. Given the country’s “dual carbon” goal, the study of the impact of green and low-carbon agriculture on the income of farmers in ethnic minority areas is crucial for China to achieve the goals of socialist modernization and common prosperity. Taking Y Town, Zhijin County, Guizhou Province as an example, this paper uses the OLS regression method to empirically study the impact of green and low-carbon agricultural production methods on the income of farmers in ethnic minority mountainous agricultural areas based on the field survey data of 881 farmers. The regression results indicate that there is a positive correlation between green and low-carbon agricultural production and the household income levels of farmers; adopting green and low-carbon agricultural production technologies can effectively promote the growth of farmers’ household income. In addition, education level, health status, and the new rural social pension insurance have all had a significant effect on the income of rural households, however, due to the difficulty in establishing trust relationships, agricultural service outsourcing has reduced the household income level of farmers. As an example, the land transfer behavior in Y Town has no significant effect on increasing farmers’ incomes. Finally, it is recommended to increase fiscal and financial support as well as effectively enhancing farmers’ policy awareness and perception of green and low-carbon agricultural production technologies by improving farmers’ general trust and institutional trust by strengthening farmers’ agricultural education and skills training while cultivating technology-based farming. At the same time, it is necessary to break the geographical restrictions on land transfer scale and achieve moderate-scale land management while promoting the use and adoption of green and low-carbon agricultural production technologies, thereby improving agricultural production efficiency and product quality, and increasing the sustainable growth of farmers’ income. The main contribution of this study is to expand the research scope of green and low-carbon agriculture to ethnic minorities and mountainous agricultural areas.

The future of sustainable farming: An evolutionary game framework for the promotion of agricultural green production technologies

Understanding how industrial agglomeration affects agricultural green production efficiency is essential for green agricultural development. This study uses the super-efficient Epsilon-Based Measure (EBM) model and Global Malmquist–Luenberger (GML) index to measure and analyze the spatial and temporal evolution characteristics and core sources of dynamics of agricultural green production efficiency in China by using panel data from 30 Chinese provinces from 2006 to 2020. It also empirically investigates the relationships between industrial agglomeration, land transfer, and agricultural production efficiency. By using fixed, intermediary, and threshold effect models, the internal links between industrial agglomeration, land transfer, and agricultural green production efficiency are examined. The findings indicate the following. (1) The green production efficiency of Chinese agriculture exhibits the regional characteristics of being “high in the west and low in the east, high in the south and low in the north” in terms of space; in terms of time, the overall trend is that green production technology efficiency is growing, with an average annual growth rate of 11.45%, and the growth primarily depends on the “single-track drive” of green technological progress. (2) Industrial agglomeration significantly affects agricultural green production efficiency, green technology efficiency, and green technology change; the corresponding coefficient values are 0.115, 0.093, and 0.022. (3) According to the mechanism-of-action results, land transfer mediates the effects of industrial agglomeration on agricultural green production efficiency, green technology efficiency, and green technology change. These effects have effect values of 28.48%, 27.91%, and 47.75%, respectively. (4) The threshold effect’s findings demonstrate a double threshold effect of industrial agglomeration on the green production efficiency of agriculture in terms of land transfer, with threshold values of 1.468 and 3.891, respectively. As a result, this study suggests adhering to the idea of synergistic development, promoting agricultural green development, strengthening the development of industrial agglomerations, promoting the quality and efficiency of industry, improving land-transfer mechanisms, and placing a focus on resource efficiency improvements, as well as other policy recommendations.

The digital development in rural areas has become an important driving force for promoting green production in agriculture. But the lack of digital skills among farmers remains a problem. The main reason why farmers cannot master digital skills well is their lack of digital literacy, which leads to market information asymmetry and the inability to truly distinguish the difference between green production and traditional production. Based on this, this article uses field research methods to collect data from 1,116 farmers in China, calculates agricultural green production efficiency using the SBM model, and empirically tests the relationship between farmers’ digital literacy and green production efficiency in agriculture. The results showed that digital literacy has a significant promoting effect on agricultural green production efficiency. Secondly, it was found that digital literacy can effectively enhance farmers’ cognition of green agricultural products and green production technology adoption. Among them, the effect of cognition of green agricultural products is reflected in farmers’ self-cognition and market cognition. The green production technology adoption is reflected in the breadth and depth of technology adoption. Third, we discuss the effect of different dimensions of digital literacy on agricultural green production efficiency. The effect of the digital literacy on the production efficiency of the five typical green technologies used by farmers is further discussed. Although there are certain differences, overall, they all have a significant promoting effect. It is necessary to comprehensively improve farmers’ digital literacy, bridge the digital divide and promote the green transformation of agricultural production.

Improving agricultural green total factor productivity is important for achieving high-quality economic development and the SDGs. Digital inclusive finance, which combines the advantages of digital technology and inclusive finance, represents a new scheme that can ease credit constraints and information ambiguity in agricultural production. First, this study focused on agro-ecological functions; we incorporated total agricultural carbon sequestration and emissions extraction into the evaluation system and used the mixed-direction-distance function to calculate agricultural green total factor productivity. Then, based on panel data from 31 provinces in China collected from 2011 to 2021, we used the two-way fixed effect model, the interactive fixed effect, and the plausibly exogenous variable method to test the impact of digital financial inclusion on agricultural green total factor productivity, and its mechanism of action. The panel-corrected standard error and fixed effect Driscoll–Kraay methods were used to account for the unobserved heterogeneity and cross-section dependence in the panel data. The results showed that digital financial inclusion can significantly improve agricultural green total factor productivity. This conclusion remained valid following robustness tests using the spatial econometric model and the method of changing explanatory variables. Digital financial inclusion can improve agricultural green total factor productivity by facilitating the transfer of agricultural land. Sound digital infrastructure and strict green credit policies enhance the role of digital inclusive finance in promoting the green development of agriculture. These conclusions could help the financial sector to formulate flexible, accurate, reasonable, and appropriate financial policies and products that would support agriculture, and enhance the role of digital inclusive finance in promoting sustainable agricultural development.

Based on provincial panel data for the past 15 years in China, the SBM-ML index method was used to measure agricultural productivity under the environmental-constraint perspective with agricultural surface source pollution as the non-desired output. A dynamic panel regression model was used to empirically analyze the factors influencing agricultural productivity to provide a reference for formulating policies to alleviate the conflict between economic development and environmental pollution. The results show that the green total factor productivity of Chinese agriculture exhibits a slow, incremental trend year by year. The growth of green total factor productivity in agriculture mainly comes from the increase in the rate of green technological progress. In terms of geographical disparity, the eastern, central, and western regions show a high-to-low gradient of agricultural green total factor productivity. Agricultural green total factor productivity showed a significant positive spatial correlation in some years. As for the influencing factors, foreign trade in agricultural products is conducive to enhancing green total factor productivity in agriculture, whereas foreign direct investment in agriculture and agricultural technology input inhibit the growth of green total factor productivity in agriculture. This research also found a significant U-shaped relationship between environmental management inputs and green total factor productivity in agriculture. Accordingly, suggestions are provided to optimize the international trade structure of agricultural products, selectively introduce high-quality green foreign investment projects, drive the efficiency of R&D investment through digital technology, and increase investment in special funds for agricultural pollution control.

The direction of promoting smallholders' adoption of agricultural green production technologies in China

Adopting agricultural green production technologies (AGPTs) is crucial for enhancing agricultural sustainability. This study draws on data from 1281 rice farmers in Jiangxi Province, China, surveyed in 2023. Using multivariate ordered probit models and mediated effects models, it examines whether cooperative membership affects the utilization of AGPTs. The findings reveal that the means of sample farmers' adoption of AGPTs and cooperative membership are 0.764 and 0.234, respectively, indicating that the adoption rate of AGPTs and the cooperative participation rate among farmers are relatively low. Cooperative membership, along with services such as land transfer, agricultural input procurement, production technology, and product marketing, significantly promotes the use of AGPTs. Specifically, cooperative membership encourages the adoption of organic fertilizers, soil-formula fertilizers, water-fertilizer integration, and green pest control technologies. However, it has no significant influence on the uptake of water-saving irrigation technologies. The impact of cooperative membership is powerful among farmers with lower educational attainment and in villages with higher economic levels. Additionally, cooperative membership enhances the application of AGPTs by improving farmers' environmental awareness, risk attitude, operational scale, and credit accessibility. Therefore, the government should encourage farmers to actively adopt AGPTs through measures such as supporting the development of cooperatives and improving the quality of their services.

The high-quality development of agriculture requires not only sustainable growth of agricultural productivity but also green agricultural production. Internet technology has played an essential role in agricultural production and marketing in China over the past decades. This paper estimates provincial agricultural green growth in China from 1997 to 2019 and decomposes it into technological progress (TP) and efficiency changes (EC) based on the Luenberger productivity indicator method. Then an econometric model is employed to analyze the impact of the Internet on the growth of agricultural green productivity and each sub-component, and moderating role of farmer education in such effect. The empirical results indicated that annual average growth rate of agricultural green productivity in China is 1.33% from 1997 to 2019, and technological progress dominates its growth. The development of Internet technology has a significant positive impact on agricultural green productivity and its decomposition. Farmer education has strengthened the effect of Internet technology on agricultural green productivity and its decomposition TP and EC.

Stakeholders have become worried about the environmental problems of agricultural production activities. Therefore, there is pressure on smallholder farmers to observe environmental regulations and embed sustainable green technologies in their production. The literature on green production has thoroughly emphasized the critical role of behavioral factors in adopting environmental sustainability practices. We develop a probabilistic linguistic preference selection index method to assess the behavioral constructs that promote the adoption of agricultural green production technologies (AGPTs) among smallholder rice farmers in an emerging economy. The result shows that the five most-important factors promoting the adoption of AGPTs include knowledge (0.828), perceived cost and benefit (0.819), descriptive norm (0.810), moral and environmental concern (0.809), and injunctive norm (0.807). The study findings offer insightful directions for examining rice farmers’ decisions on the adoption of AGPTs. Our findings imply that policymakers should consider multiple behavioral factors when designing policies that promote AGPTs. This study enriches farmers’ adoption decisions by modeling the uncertainties in the decision-making process.

The application of agricultural green production technologies (AGPTs) promotes green agricultural development and enhances the rural environment. Scale operations can allocate land resources rationally and modernise agricultural technology and management practices. Although previous studies have shown that expanding land transfer facilitates the adoption of AGPTs by farmers, research on how to further promote farmers’ adoption behaviour is still lacking. To understand the mechanism of land transfer on farmers’ adoption behaviour of AGPTs, this study uses survey data from farmers in Jiangxi Province, China, and employs an endogenous switching regression (ESR) model for counterfactual estimation. The results show that farmers who have acquired land through transfer adopt AGPTs at a significantly higher rate than those who have not. Land transfer promotes farmers’ adoption behaviour by increasing household income, financial support, and agricultural socialised services. Land transfer contracts, long-term transfers, and moderate land rent are also conducive to farmers’ adoption behaviour of AGPTs. The impact of the land transfer on farmers’ adoption behaviour of AGPTs is more significant among large-scale farmers, those with higher field fertility, and those with lower land fragmentation.

Does agricultural factor misallocation hinder agricultural green production efficiency? Evidence from China

The role of agricultural green production technologies in improving low-carbon efficiency in China: Necessary but not effective

Against the backdrop of worsening global ecological and environmental problems and the "dual carbon" goal, the promotion of agricultural green production technology is of great significance for achieving sustainable development. This article takes 200 households in Hongdong County, Shanxi Province as the research object. Based on the Theory of Planned Behavior (TPB) and the Technology Acceptance Model (TAM), a questionnaire survey and logistic regression model are used to systematically analyze the willingness of farmers to adopt green agricultural production technologies and its influencing factors. Research has shown that high upfront costs and insufficient market premiums are the main obstacles in economic factors; The perception of technological complexity significantly reduces the willingness to adopt; Policy support, especially subsidy policies, has the strongest effect on promoting adoption willingness; 50% of farmers in social networks have a neighborhood demonstration effect, and the significant improvement in environmental awareness promotes adoption. Based on this, policy recommendations such as increasing financial subsidies, optimizing the technical training system, and strengthening the social network dissemination effect are proposed to provide a theoretical and practical basis for the green transformation of agriculture.

The scientific and reasonable measurement of agricultural green total factor productivity is helpful to grasp the direction of rural-factor-market reform. This study constructs a Malmquist productivity index based on a non-radial and non-angular SBM directional distance function. This study calculates the agricultural green total factor productivity of 28 provinces (cities and autonomous regions) in China from 1997 to 2020 by considering unexpected outputs such as carbon emissions and agricultural non-point-source pollution. Finally, this study uses the spatial Dobbin model to explore the spatial impact of agricultural green total factor productivity under the distortion of the factor market. The results show that the agricultural green total factor productivity, considering the unexpected outputs, is more in line with the level of high-quality green development in China’s agriculture. Regardless of whether the unexpected output is included, the increase in China’s agricultural total factor productivity is primarily due to progress in agricultural technology, and the double boost is little in agricultural technology progress and technical efficiency. Agricultural green total factor productivity shows an increasing trend, but the growth rate is slow, and differences in different regions are significant. Factor market distortion negatively impacts agricultural green total factor productivity, and other factors improve the agricultural total green factor productivity. However, factor market distortion has a particular spatial spillover effect, which hinders the synchronous growth of agricultural green total factor productivity in different regions. Therefore, the government should promote the reform of the agricultural mode of production and agricultural green production, eliminate the blocking effect of factor market distortion on the improvement in agricultural green total factor productivity, narrow the regional gap of agricultural total factor productivity, and establish a policy system for high-quality green development of modern agriculture.