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.
As one of the means of informal environmental regulation, environmental information disclosure has an essential impact on improving green energy efficiency. This paper selects the panel data of 113 environmental information disclosure cities in China from 2008 to 2018 and uses the Super-efficiency SBM model with undesirable outputs to measure green energy efficiency. Based on the measurement results, this paper empirically studies the impact of environmental information disclosure on green energy efficiency and its spatial spillover effect using the spatial Durbin model. The main conclusions are as follows: 1) From 2008 to 2018, the average green energy efficiency of 113 environmental information disclosure cities in China was 0.6676, and the regional distribution showed the characteristics of “high in the East and low in the west.” 2) Both environmental information disclosure and green energy efficiency have significant spatial correlation and show the characteristics of “high-high” and “low-low” agglomeration in spatial distribution. 3) Environmental information disclosure can significantly improve green energy efficiency in the region and surrounding areas. After the robustness test and endogenous test, the conclusion is still robust. 4) The impact of environmental information disclosure on green energy efficiency in the eastern region is significantly more significant than in the central and western regions. This paper provides a theoretical reference for the government to formulate corresponding environmental policies to promote green energy efficiency and promote green and sustainable economic development.
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.
First of all, the paper discusses the theoretical relationship of financial ability and industrial development. It is suggested that the financial ability is the basic requirement of industrial development, and is the comprehensive reflection of industrial competitiveness. Second, the status quo of the financial ability of Chinese timber industry is analyzed in such respects as internal financing, equity financing and debt financing. It is concluded that the financial ability of Chinese timber industry is weak.There are some problems in such respects as internal financing, equity financing and debt financing. Finally, aiming at existing problems, the paper puts forward relevant policy suggestions.Keywords-timber industry financial ability internal financing equity financing debt financing
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