Agriculture is the foundation of every country’s survival and development. This paper analyzes the interaction between the business environment, agricultural opening-up and high-quality agricultural economy from the perspective of China’s provinces. According to the panel data of 31 provinces and municipalities in China from 2009 to 2019, the empirical analysis was carried out based on the panel vector autoregression (PVAR) model. The results show that there is a quantitative interaction between China’s business environment, agricultural opening-up and high-quality agricultural development, and the long-term time effect is very obvious. Specifically, (1) the impact of the business environment and the high-quality development of agriculture on itself is decreasing year by year. The agriculture opening-up itself has a strong impact and has always maintained strong stability. (2) The high-quality development of the agricultural economy has little impact on the business environment and the opening of agriculture to the outside world, but it has a certain stable and continuous effect. It is particularly important that the agricultural opening-up has an increasingly strong effect on the business environment and the high-quality development of the agricultural economy as time progresses. Therefore, we must always adhere to the agriculture opening-up. The regional business environment and the agriculture opening-up can jointly promote the high-quality development of the agricultural economy. The research results can provide a basis and reference for the central and local governments to formulate relevant agricultural development policies and provide a reference for relevant agricultural economic entities and enterprises.

Water and land resources are related to the security and stability of agricultural production, and the degree of matching in time and space directly affects regional agricultural production capacity and sustainable agricultural development. This paper intends to use the panel data of nine provinces in the Yellow River Basin from 2000 to 2019 and incorporate the static and dynamic spatial Durbin models with spatial effects under the geographical adjacency matrix and the comprehensive weight matrix of economic geography, so as to explore the direct effects and indirect effects, short-term effects and long-term effects of the matching coefficient of agricultural water and land resources on the agricultural economic growth in the Yellow River Basin. The results show the following: (1) The matching situation of agricultural water and land resources in different provinces along the Yellow River Basin are different; some are relatively short of water resources, some are relatively balanced in water and land resources, and some are relatively short of land resources. (2) The static spatial Durbin model shows that the direct effect of the matching coefficient of agricultural water and land resources on the agricultural economic growth of the province is not significant; the indirect effect and the total effect of the spatial spillover is significantly positive. (3) The dynamic spatial Durbin model under the two matrix forms shows that the short-term total effect of the matching coefficient of agricultural water and land resources on agricultural economic growth is significantly positive, while the long-term total effect is significantly negative, and the direction and degree of the short-term and long-term effects are inconsistent. This study provides a comprehensive analysis framework from the perspective of local and neighborhood effect, and short-term and long-term effect, which can provide a reference to reasonably adjust the matching of agricultural water and land resources to promote agricultural sustainable economic growth, especially for developing countries.

As world resources and environmental constraints have increased, environmental cost has become a concern that affects the sustainable development of the logistics industry in various countries. Carbon emissions are an important part of any environmental cost assessment. How to scientifically and rationally evaluate the green GDP impact and regional efficiency in the logistics industry, especially when under carbon emission constraints, is of great significance to the realization of green and sustainable development. This study evaluated the logistics efficiency of 30 provinces in China from 2003 to 2016 by constructing a super SBM (Slack Based Model) model with undesirable output to explore provincial efficiency and its regional differences. The input–output ratio of the regional logistics industry was optimized through the calculation of the frontier slack variables. The research results showed that, first, it was more reasonable to adjust efficiency under carbon constraints, and it was consistent with the actual performance of the logistics industry. Second, technological progress and deeper capital investments promoted the development of the logistics industry, but technological barriers and low-scale efficiency between regions often limited technological efficiency. Therefore, decision-makers in the logistics industry should reconsider the challenges presented in each reason, encourage industrial technological innovation between regions, and especially promote energy-saving and emission-reduction technologies, so as to maintain the sustainable growth of the logistics industry.

As the global economic development intensifies the plunder of resources and the environment, the constraints are becoming more and more obvious. Based on the background of the strategy for ecological conservation and high-quality development of the Yellow River Basin, this paper intends to construct a resource-environment-constrained economic growth drag effect model and a spatial Dubin model, and explore the economic growth drag effect and its spatial differences in the Yellow River Basin under the constraints of resources and environment. The study found that the total drag effects of the overall economic growth of the Yellow River Basin that were obtained by the classic panel model without spatial effects is significantly negative. This is consistent with the conclusion that the average total drag effects of 80 prefecture-level cities is negative. The total drag effects of the overall economic growth of the Yellow River Basin changes from unconstrained to medium-constrained after adding spatial constraints, indicating that the spatial correlation of factors will restrict economic growth. From the level of the Yellow River sub-catchment, the total drag effect of the direct effects of the upper, middle, and lower reaches of the Yellow River is consistent with the total drag effect of the total effect. It shows that the upper economic growth is strongly constrained by the local resources and environment, while the downstream is strongly constrained by the adjacent resources and the environment. The research results provide references for resolving the resources and environment constraints in the Yellow River Basin. It provides useful inspiration for promoting ecological protection and high-quality development strategies in the Yellow River Basin.

At present, there are large number of articles on the impact of COVID-19, but there are only a few articles on the impact of COVID-19 and international agriculture. Agriculture product is different from other industrial products. If domestic food cannot be self-sufficient, it must be resolved through imports. This will inevitably face the dilemma between the opening up agriculture and the risk of importing COVID-19. This paper pioneered the use of entropy method, TOPSIS method and grey correlation analysis to predict the correlation between agricultural opening to the outside world and the input and spread of COVID-19. We use the correlation matrix quantifying the number of confirmed COVID-19 cases and agricultural openness to deduce that there is a significant positive correlation between the flow of agricultural products caused by China’s agricultural opening-up and the spread of COVID-19, and use the proposed matrix to predict the spread risk of COVID-19 in China. The results of the empirical analysis can provide strong evidence for decision-makers to balance the risk of COVID-19 transmission with the opening of agricultural markets, and they can take this evidence into full consideration to formulate reasonable policies. This has great implications both for preventing the spread of COVID-19 and for agricultural opening-up.