Improving agricultural green total factor productivity is crucial to promoting high-quality agricultural development. This paper selects the panel data of 30 provinces in China from 2009 to 2020 and uses the super-efficiency SBM model with undesirable outputs to measure the agricultural green total factor productivity of all regions in China. On this basis, this paper uses the panel data fixed-effect model and spatial Durbin model to empirically discuss the impact of agricultural credit input on agricultural green total factor productivity and its spatial spillover effect. The main conclusions are as follows: First, from 2009 to 2020, the average values of agricultural green total factor productivity in national, eastern, central, and western regions are 0.8909, 0.9977, 0.9231, and 0.8068, respectively, and the agricultural green total factor productivity needs to be further improved. Second, the agricultural green total factor productivity presents a significant and positive spatial correlation, and the spatial distribution of agricultural green total factor productivity is not random and irregular. Third, agricultural credit input can significantly promote agricultural green total factor productivity in the local region, but it hinders the improvement of agricultural green total factor productivity in the adjacent regions. Fourth, the impact of agricultural credit input on the agricultural green total factor productivity and its spillover effect has a significant regional heterogeneity. This paper believes that paying attention to the spatial spillover effect of agricultural total factor productivity, optimizing the structure and scale of agricultural credit input, and formulating reasonable agricultural credit policies can improve agricultural green total factor productivity.

The improvement of agricultural TFP is critical to promoting the high-quality development of agriculture. This paper described and identified the spatiotemporal differentiation characteristics and spatial correlation of China’s agricultural TFP in 283 prefecture-level cities from 2001 to 2018 using the Metafroniter-Malmquist and Moran index. The results showed that: (1) From 2001 to 2018, China’s agricultural TFP was 6.64%, and its growth was mainly driven by agricultural technological progress. The contribution of agricultural technological efficiency was small. The growth law showed an “inverted U-shaped” growth trend of first rising and then falling. (2) China’s agricultural TFP has significant characteristics of regional unbalanced growth. (3) The growth rate of agricultural TFP in most prefecture-level cities is medium and slow, and most prefecture-level cities relied on agricultural technological progress to promote growth. (4) The agricultural TFP of various cities showed a significant spatial correlation phenomenon of “high-high” or “low-low.” This study has significant theoretical and practical value for maintaining the stable growth of China’s agricultural TFP and promoting the high-quality development of China’s agriculture.

China is the world’s largest importer of logs, possessing the scale to exert significant influence in the international market. This paper uses a fixed-effect variable coefficient Pricing-to-Market panel model to measure China’s market power in log import trade. It also utilizes the Almost Ideal Demand System model from an elasticity perspective to explore the market behavior characteristics of various source countries in China’s log import trade, thereby validating the mechanism of market power. The results indicate that: ① China’s main trading partners can be categorized into four groups according to their market power in the log import trade. Specifically, China holds superlative market power in log imports from Indonesia, Malaysia, and Myanmar; holds strong market power in log imports from Russia, the Democratic Republic of the Congo, and Mozambique; holds weak market power in log imports from Papua New Guinea, Equatorial Guinea, France, Germany, Australia, and New Zealand; and holds no market power in Japan, Cameroon, and the United States. ② As China’s expenditure on log imports increases, there is a tendency to purchase high-quality precious wood and a greater concern for the legality of market transactions. Consequently, China is anticipated to augment its imports from source countries with no or weak market power. ③ The simple price elasticity of log imports from each source country is negative. Source countries with stronger market power tend to increase prices to achieve higher total revenue, while those with weaker market power are more inclined to lower prices to achieve the same. ④ Log products from various source countries are complementary in the Chinese market, indicating that China’s substantial demand for logs relies on the simultaneous supply from multiple countries and diverse wood types. Based on the existence or absence of market power in China’s log import trade, this paper provides targeted insights into enhancing international market power and reducing trade losses.