A Win–Win Scenario for Agricultural Green Development and Farmers’ Agricultural Income: An Empirical Analysis Based on the EKC Hypothesis

The impact of environmental regulation on farmers' income: an empirical examination based on different sources of income

This study uses Chinese rural household data to examine the relationship between environmental regulation and farmers' income. The study found that environmental regulation has the most apparent promotion effect on farmers' agricultural production income. However, the effects on self-employment and non-farm employment are insignificant. In addition, the increase in agricultural green total factor productivity is a channel for environmental regulation to promote agricultural production income. The stronger the farmers' awareness of environmental protection, the more significant the effect of environmental regulation on agricultural production income increase. In China, the effect of environmental regulations on farmers' income from agricultural production is most significant in the central region, followed by the eastern region. In the western region, environmental regulations do not affect agricultural production income. Finally, we discuss the different impacts of industrial and agricultural environmental regulations on farmers' income. Results show that agricultural environmental regulation affects agricultural production income. By contrast, industrial environmental regulations affect farmers' self-employment and non-farm income.

Spatial Distribution and Convergence of Agricultural Green Total Factor Productivity in China

The power source, spatial-temporal differentiation and convergence of the growth rate of green total factor productivity in China’s agriculture were analyzed. The Malmquist index was used to measure the growth rate, and the spatial-temporal convergence was tested by σ convergence, absolute β convergence, conditional β convergence and dynamic spatial convergence. The study drew conclusions that the impetus for the intensive growth of green agriculture was insufficient, and the driving force for the growth of agricultural green total factor productivity (AGTFP) in the eastern, western and central region was green technology progress. In addition, AGTFP did not have an absolute σ convergence trend. Dynamic spatial absolute β and conditional β convergence indicated that regional differences were not completely related to regional endowment conditions, and regional green agricultural production was unbalanced. This study provides an important support for regional green development in China’s agriculture.

Influence Paths and Spillover Effects of Agricultural Agglomeration on Agricultural Green Development

Analyzing the impact of agricultural industrial agglomeration (AIG) on agricultural green development (AGD) is of a great significance to realizing the sustainable and high-quality development of agriculture. Panel data of 31 provinces in China from 2009 to 2019 were analysed. For measuring efficiency, a non-parametric DEA approach in the presence of undesirable outputs, a slack-based measure (SBM) was used. From the perspective of the spatial spillover analysis and heterogeneity analysis, Moran’s I index and the Spatial Durbin Model (SDM) were used to empirically analyze the impact of AIG on AGD to alleviate conflicts between agricultural sustainable development and environmental pollution and further explore the regional heterogeneity of AIG on AGD-efficiency due to the vast territory of China. The mediation model is constructed to explore the paths of AIG affecting AGD. The results show that: (1) Chinese efficiency of AGD was raised continuously and the high efficiency was mainly located in the southeastern coastal areas. (2) AIG not only has a significant U-shaped impact on the AGD, but also has a nonlinear U-shaped spatial spillover effect in related regions, which shows that the “siphon effect” will be triggered in the early stage of AIG and the “diffusion effect” will be evoked in the later stage of AIG. (3) From the perspective of heterogeneity analysis, AIG significantly promotes the efficiency of AGD in the central region of mainland China. In the eastern region, the AIG has an inverted U-shaped effect on the efficiency of AGD from positive to negative. On the contrary, the AIG has a U-shaped impact on the efficiency of AGD from negative to positive in the western region. (4) The analysis of the mediation model plays a partial positive mediating role for AGD to persist in promoting technology innovation and increasing the speed of talent agglomeration. Accordingly, suggestions are provided to strengthen the coordination and cooperation in sustainable agricultural development among provinces, to drive the efficiency of science and technology through the scale knowledge spillover effect, and to conduct a scientific layout of agricultural industry development.

Evaluation and Influencing Factors of China’s Agricultural Productivity from the Perspective of Environmental Constraints

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 Influence Paths of Agricultural Mechanization on Green Agricultural Development

For sustainable agricultural development, increasing efforts are put on promoting agricultural mechanization and green agricultural development all over the world. Based on the panel data of Chinese provincial agriculture from 2002 to 2018, the System Generalized Method of Moments model and mediation model are constructed to explore the paths of agricultural mechanization affecting green agricultural development. The results show that agricultural mechanization can not only promote the green agricultural development directly but also indirectly by transferring the agricultural labor force and increasing fertilizer input. However, because of the surge of pesticide demand, agricultural mechanization also leads to serious pollution indirectly. With the development of large-scale agricultural machinery, the direct promotion of agricultural machinery on green agricultural development will be more significant. However, it will be less efficient to substitute more agricultural labor force with machinery power. The problem of pesticide abuse will also become more serious. Therefore, it is important for green agricultural development to encourage human capital investment in agricultural mechanization. In addition, more attention should be paid to improving the input efficiency of fertilizers and pesticides so that agriculture will be sustainable in production and the ecological environment.