The influence mechanism and spatial effect of carbon emission intensity in the agricultural sustainable supply: evidence from china's grain production

Can the development of the rural digital economy reduce agricultural carbon emissions? A spatiotemporal empirical study based on China's provinces

Rapid advancement of the rural digital economy has intensified the demand for leveraging digital tools to foster low-carbon and sustainable agricultural practices, garnering widespread academic and bureaucratic attention. Understanding how the rural digital economy influences agricultural carbon emissions is crucial for unlocking emission reduction potential, facilitating a transition towards sustainable energy usage in rural areas, and nurturing green agricultural development. In this study, we employ the entropy method, a spatial Durbin model, and a panel threshold model to assess the impact of the rural digital economy on agricultural carbon emissions across each province in China from 2010 to 2022. Additionally, we delve into the mechanism through which the rural digital economy facilitates agricultural carbon reduction, particularly in terms of "agricultural socialized services". Our findings reveal several key insights. Firstly, the rural digital economy contributes significantly to reducing agricultural carbon emission intensity. Secondly, there is a non-linear relationship between the rural digital economy and agricultural carbon emissions. With the development of rural digital economy showing a marginal decreasing trend, there is an obvious threshold effect. Thirdly, enhancing agricultural socialized services through the rural digital economy can curb agricultural carbon emissions. Lastly, the carbon reduction effect of the rural digital economy is more significant in more economically developed areas, areas with moderate levels of economic development, and areas with low technological investment; implementation of a "zero growth" policy for fertilizers strengthens this carbon reduction effect. This study sheds light on the mechanisms and effects of agricultural carbon emissions, offering quantitative evidence and theoretical support for the transition towards low-carbon and sustainable agricultural development.

Quantifying biased technical progress in China: Heterogeneous human capital and labor force dynamics

The main objectives of this study are to estimate the biased technical progress in China considering heterogeneity in human capital and labor force, examine how this heterogeneity quantitatively impacts the elasticity of substitution and biased technical progress compared to homogeneous labor assumptions, and compare the growth rates of human capital-augmenting and labor-augmenting technical progress. The estimation procedure involves a constrained Seemingly Unrelated Regression (SUR) using provincial-level panel data from 1985 to 2021. By comparing results with and without accounting for labor force heterogeneity and human capital, the analysis quantifies their impact on the estimated elasticity of substitution between factors and the magnitude and direction of technical bias. Results found that the elasticity of capital-labor (human capital) substitution is between 0.7 and 0.8, and the elements are generally complementary. Although it does not affect the overall trend of elasticity of substitution and biased technical progress, the heterogeneity of human capital and labor force has a quantitative impact on them. It means that the elasticity of substitution increased, and the biased technological progress decreased. Moreover, the growth rate of human capital-augmenting technical progress was significantly lower than that of labor-augmenting technological progress. This study estimates the biased technical progress in China, where the human capital and labor force are heterogeneous. The findings suggest that policymakers should prioritize human capital investments and technological upgrades in industries to rebalance China's technical progress and boost productivity growth.

Exploring the dual impact: Dissecting the impact of tourism agglomeration on low-carbon agriculture

Despite extensive research on the relationship between tourism and agriculture, the specific impact of tourism on agriculture's low-carbon transition has not been thoroughly investigated. This study analyzes the effects of tourism agglomeration on agricultural carbon intensity across 30 Chinese provinces from 2001 to 2020. It is framed within the context of rural digitalization, with a particular emphasis on the integration of agro-tourism and the total factor productivity of agriculture. Utilizing spatial econometric models, we find that tourism agglomeration hinders the low-carbon transition in agriculture by influencing carbon intensity both directly and indirectly. At the national level, the impact of tourism agglomeration follows an inverted-U curve with respect to agro-tourism integration and carbon intensity. At the regional level, the effects vary, with weaker indirect influences in major grain-producing areas. Furthermore, rural digitalization appears to lessen the adverse impacts of tourism on carbon intensity. This study also identifies significant spatial spillover effects from tourism agglomeration. The findings suggest that provinces with high tourist influx should enhance investments in climate-smart agricultural practices and technologies to counteract these negative impacts. Moreover, integrated governance of tourism and agriculture is essential for achieving carbon neutrality in both sectors.

Spatial autocorrelation and driving factors of carbon emission density of crop production in China

Mitigating carbon emissions from crop production is essential for addressing global warming. At a macro-level, existing studies have often relied on the calculation of carbon emission intensity of crop production to understand comparable carbon effects between regions. However, this approach obscures the differences in crop planting scale and natural attributes across regions, leaving room for improvement in the methods and scope of analysis. To extend the existing research, we proposed an idea for calculating the carbon emission density of crop production based on planting area. Additionally, we developed an analytical framework for driving factors of carbon emission density of crop production from a spatial interaction perspective. The provincial carbon emission density of crop production in mainland China between 2000 and 2020 was calculated, and spatial econometric models were utilized to investigate the spatial autocorrelation and driving factors. The results indicate that the national average carbon emission density of crop production was 1.462 t/hm2 annually. Over 21 years, the carbon emission density of agricultural materials, rice cultivation, soil management, and straw burning evolved from 0.384 to 0.470 t/hm2, 0.409 to 0.367 t/hm2, 0.171 to 0.169 t/hm2, and 0.317 to 0.448 t/hm2, respectively. The global Moran's index indicated a positive spatial autocorrelation of carbon emission density of crop production and the subdivided carbon sources among provinces. Regarding direct effects, an increase in the proportion of paddy fields in cropland composition and irrigation efficiency would significantly promote the carbon emission density, while factors such as cropland area, multiple cropping, agricultural personnel numbers, departmental proportion, and disaster degree would decrease the local carbon emission density. Certain factors, such as cropland area and agricultural disasters, had a spatial spillover effect on carbon emission density between provinces. The study suggests harnessing key drivers and spatial spillover effects to achieve regional low-carbon crop production.

Grain industrial agglomeration and grain green total factor productivity in China: A dynamic spatial durbin econometric analysis

Appropriate industrial agglomeration has several benefits, including reducing environmental pollution, promoting innovation and enhancing grain green total factor productivity (GTFP). It is an effective strategy for promoting high-quality and sustainable development in the grain industry. In this study, the slacks-based measure of the global Malmquist-Luenberger (SBM-GML) model is used to estimate China's grain GTFP using the panel data of 31 provinces from 2001 to 2020. Furthermore, a dynamic spatial econometric model is employed to empirically investigate the impact of grain industry agglomeration on grain GTFP and its regional heterogeneity. The results show that GTFP exhibits a fluctuating growth tendency, with advancements in green technology serving as the primary engine of that expansion. (2) The deepening of grain industrial agglomeration has a long-term promoting effect on the grain GTFP of local and neighbouring areas, with the long-term effect being more significant than the short-term effect, as revealed by the dynamic spatial Durbin model. (3) According to the heterogeneity analysis, industrial agglomeration's impact on grain GTFP is most noticeable in the production and sales balance. Therefore, encouraging regional cooperation and communication while raising the grain industrial agglomeration standard is crucial. The degree of regional economic growth, the state of the agricultural infrastructure and the conditions of the natural resources should all be considered by policymakers when developing distinct and focused policy assistance for each region.

Examination of the relationship between agricultural carbon emission efficiency and food quality and safety: from the perspective of environmental regulation

An important breakthrough in the coordinated development of China's low-carbon goals and food security strategies is agricultural development oriented toward quality, safety, green, and low carbon. This study integrated command-control and market-incentive environmental regulation (ER), agricultural eco-efficiency (ACEE), and food quality and safety (FQS) into a unified theoretical framework. The unexpected output-oriented Super-SBM model was used to calculate the ACEE of China's provinces and cities from 2011 to 2020 and test the bidirectional causality between ACEE and FQS through the system generalized moment estimation model. A dynamic panel smooth transition (PSTR) model was used to explore the nonlinear impact mechanisms of different types of ERs on ACEE and FQS. The results showed that there was a long-term, two-way causal relationship between ACEE and FQS. The impact of environmental regulations on ACEE and FQS has a nonlinear relationship. Among them, the role of market-incentivized ER is more significant. Therefore, building an interregional coordinated development mechanism, improving the utilization rate of agricultural resources such as fertilizers and pesticides, and coordinating the positive effects of different types of ERs are the keys to improving the ACEE and ensuring the coordinated development of FQS.

Food security and overuse of agrochemicals: evidence from China's major grain-producing areas policy

China's major grain-producing areas (MGPA) policy is the core policy to ensure national food security. While achieving long-term stable growth of grain production, assessing the impact of MGPA policy on agrochemical application has important practical significance in sustainable agricultural development and environmental protection. Based on panel data of 31 provinces in China from 1997 to 2020 and taking the MGPA policy introduced in 2004 as a quasi-natural experiment, we construct a difference-in-difference (DID) model to evaluate the overall impact and dynamic effect of MGPA policy. It is found that the MGPA policy do not exacerbate chemical overuse as a whole, but significantly reduce the fertilizer use by 11% and the pesticide use by 6%. Using the event study to decompose the policy effect year by year, we find that the MGPA policy significantly increased the fertilizer and pesticide use in a short period of time. Its influence on the application amount of two chemicals began to turn negative until the fourth and sixth years of the policy implementation and became more and more obvious. We conclude the intermediate paths of MGPA policy to change planting structure, deepen agricultural division of labor, and reduce the use of agrochemicals, which were verified by the intermediary effect model. From the perspective of provincial differences, MGPA policy reduced chemical use more in provinces with large output contribution and northern provinces. In addition, the MGPA policy has reduced the amount of fertilizer application in major rice-growing provinces, but not the amount of pesticide application. Our research can provide implications for other developing countries and emerging economies where agricultural production is highly dependent on chemicals and has green agricultural transition plans.

Coupling and Coordinating Relationship between Agricultural Eco-Efficiency and Food Security System in China

Carbon peaking, carbon neutrality goals and food security are the basis of sustainable development, and exploring the coordination relationship between China's agricultural eco-efficiency and food security system has a major significance for the implementation of relevant strategies. This paper is based on collaboration research on the synergistic relationship between agricultural eco-efficiency and food security systems using methods such as entropy weight method, coupling coordination model, spatial autocorrelation model, etc., revealing the evolution-driven mechanism of the coupling coordination degree. This study found that a higher level of coupling coordination always occurs in those areas with high standard farmland construction and large grain production scale, while economically developed areas appear to have a lower overall coordination level limited by endowment constraints and division of labor in development planning. It shows a positive spatial correlation in terms of geographical distance between agricultural eco-efficiency and food security, and the positive spillover effect gradually increases but is not strong overall. China should combine regional resource endowment and development planning, pay attention to the improvement of large-scale and standardized agricultural production, continue to strengthen the development of clean agricultural production, and achieve food security under the constraints of the carbon peaking and carbon neutrality goals.

A Study on the Impact of Low-Carbon Technology Application in Agriculture on the Returns of Large-Scale Farmers

The relationship and mechanism between agricultural low-carbon technology application and farm household returns are not yet clear, especially the lack of evidence from developing countries. This paper takes large-scale farming households in Jiangxi Province, China, from 2019 to 2020 as the research object, and obtains relevant data from field research to explore the intrinsic impact of agricultural low-carbon technology application on the returns of large-scale farming households. Based on the relevant theoretical analysis, the division dimensions of agricultural low-carbon technologies were proposed, and agricultural low-carbon technologies were subdivided into ten specific low-carbon technologies according to six dimensions: tillage system, breeding, fertilization, irrigation, medicine application, and waste treatment. Relevant questions were designed and researched to obtain data on the application status of low-carbon technologies in agriculture and the income cost status of large-scale farmers. Based on the theoretical analysis, the research hypotheses were proposed, and an empirical analysis was conducted based on the obtained data from large-scale farmers. The application of seven low-carbon technologies in agriculture: conservation tillage system, direct sowing technology, selection of compound fertilizer/organic fertilizer/controlled-release fertilizer, soil formula fertilization technology, deep fertilization/irrigation fertilization, sprinkler/drip irrigation/wet irrigation/intermittent irrigation, and straw resourceization significantly improved the income level of large-scale farmers. Furthermore, the application of biodegradable agricultural membranes, biopesticides, and new pesticide-controlled release technologies did not have significant effects on the income level of large-scale farmers, due to their low application and penetration rate. Based on the findings of the paper, the government should strengthen the promotion and subsidies of agricultural low-carbon technologies, especially those technologies that have no significant impact on large-scale farmers' income, such as biodegradable agricultural membranes, biopesticides, and new pesticide controlled-release technologies, so as to achieve a win-win situation of reducing carbon emissions and increasing farmers' income.

Can the Adjustment of China's Grain Purchase and Storage Policy Improve Its Green Productivity?

While the sustainability of grain production has been extensively studied, there have been few studies focusing on the impact of grain policy adjustment on its sustainable production, and the quantitative relationship between these two aspects and the internal mechanism is not completely clear. The main objective of this paper was to explore the impact of grain purchase and storage policy (GPSP) adjustment on its green productivity by expounding the evolution logic and influence mechanism of GPSP. Therefore, taking maize production as an example, this paper constructs the analysis framework of the evolution logic and influence mechanism, and the super-epsilon-based measure model (Super-EBM) is adopted to measure maize green productivity (MGP) in main producing areas from 1997 to 2019, then two groups of difference-in-differences (DID) models are constructed to study the influence of the temporary purchase and storage policy (TPSP) and the producer subsidy policy (PSP) on MGP. The main conclusions include: the implementation of TPSP reduces MGP in Heilongjiang, Jilin, Liaoning and Inner Mongolia (experimental group), whereas the implementation of PSP improves MGP in these provinces is due to the difference in policy effects under the different regulatory objectives and measures; under the demonstration effect of two policies, the increase in effective irrigation and agricultural financial expenditure are important factors to improve MGP, but the backwardness of agricultural mechanization has been hindering the improvement of MGP; after the reform from TPSP to PSP, the continuous increase in production capacity hinders the improvement of MGP under the support effect, the impacts of farmers’ income and agricultural production price on MGP both shift from negative to positive under the wealth effect, and the influence of production agglomeration on MGP shifts from negative to positive under the siphon effect. The excessive implementation of GPSP has seriously affected the sustainability of grain production, thus, this study has certain practical significance and guiding value. The paper emphasizes that the effective way to achieve sustainable food production is to combine the adjustment of GPSP with improving the subsidy mechanism, enhancing the agricultural mechanization and maintaining the appropriate scale of operation.