Lei Du

Assessing incremental land value is a key issue in rural land system reform. This study clarifies the formation mechanism of incremental income of idle homestead (IIIH), analyzes its spatial distribution characteristics using exploratory spatial data analysis methods, and identifies the spatial heterogeneity of its influencing factors using a geographically weighted regression model. The results showed that: (1) The idle homesteads have higher increment income. The Cities with high IIIH are concentrated in the Yangtze River Delta (YRD), Pearl River Delta (PRD), Chengdu-Chongqing and Bohai Rim urban agglomerations. Provincial capitals and cities specifically designated in the state plan exhibit higher IIIH than ordinary prefecture-level cities; (2) The IIIH involves two stages, “implicit” and “explicit”, and follows two distinct paths characterized by “high development capacity” and “low development capacity”; (3) Spatial heterogeneity exists in the effects of the factors influencing IIIH. The regression coefficients for urban grade, output value of the tertiary industry, health care resources and education funding input show increasing trends from north to south, west to east, south to north and northwest to southeast respectively. Based on the conclusions, this article proposes that: first, cross-province and cross-city trading mechanisms for surplus construction land quotas should be promoted according to local conditions. Second, farmers’ contributions during the “implicit” increment stage should be recognized in the distribution of incremental income. Third, a differentiated distribution pattern for increment income should be established based on the primary drivers of IIIH for different types of idle homesteads.

The agricultural credit scale plays a crucial role in improving the agricultural green production efficiency (AGPE) in China. This paper selected the panel data of 30 provinces in China from 2009 to 2020 and used the Metafrontier-Malmquist-Luenberger index to calculate the agricultural green production efficiency. On this basis, this paper uses the Panel Tobit model to analysis the impact of agricultural credit scale on AGPE. The main conclusions are as follows: 1) From 2009 to 2020, the average AGPE in 30 provinces was 4.2%, and agricultural technology progress was the main driving factor for AGPE growth. 2) The agricultural credit scale significantly promotes AGPE, and the impact of the agricultural credit scale on AGPE presents a significant inverted U-shape. 3) The impact of the agricultural credit scale on AGPE in eastern, central, and western regions is significantly heterogeneous. 4) AGPE has significant spatial spillover effects. This paper believes that improving agricultural green production efficiency requires paying attention to the important role played by the scale of agricultural credit.

Digital inclusive finance has an essential impact on improving the urban green economy efficiency by demonstrating environmental friendliness in agglomerating factors and promoting the flow of factors. Based on the panel data of 284 cities in China from 2011 to 2020, this paper uses the super-efficiency SBM model with undesirable outputs to measure the urban green economy efficiency. Then, the fixed effect model and spatial econometric model of panel data are used to empirically test the impact of digital inclusive finance on urban green economic efficiency and its spatial spillover effect, and the heterogeneity analysis is carried out. This paper draws the following conclusions. (1) The average value of urban green economic efficiency of 284 Chinese cities from 2011 to 2020 is 0.5916, showing a “high in the east and low in the west.” In terms of time, it showed a rising trend year by year. (2) Digital financial inclusion and urban green economy efficiency have a high spatial correlation, both showing “high-high” and “low-low” agglomeration characteristics. (3) Digital inclusive finance significantly impacts urban green economic efficiency, especially in the eastern region. (4) The impact of digital inclusive finance on urban green economic efficiency has a spatial spillover effect. In the eastern and central regions, digital inclusive finance will inhibit the improvement of urban green economic efficiency in adjacent cities. In contrast, it will promote urban green economy efficiency in the western regions in adjacent cities. (5) The coverage and depth of digital inclusive finance significantly affect the urban green economy efficiency, while the level of digitization has yet to show a significant effect. This paper puts forward some suggestions and references for promoting the coordinated development of digital inclusive finance in various regions and improving urban green economic efficiency.

Based on the characteristics of underdeveloped areas, this paper selects the panel data of 15 underdeveloped counties in Anhui Province from 2013 to 2019 and uses the panel threshold model to empirically analyze the sustainability of rural tourism development. The results show that: (1) Rural tourism development has a non-linear positive impact on poverty alleviation in underdeveloped areas and has a double threshold effect. (2) When the poverty rate is used to express the poverty level, it can be found that the development of rural tourism at a high level can significantly promote poverty alleviation. (3) When the number of poor people is used to express the poverty level, it can be found that the poverty reduction effect shows a marginal decreasing trend with the phased improvement of the development level of rural tourism. (4) The degree of government intervention, industrial structure, economic development, and fixed asset investment play a more significant role in poverty alleviation. Therefore, we believe that we need to actively promote rural tourism in underdeveloped areas, establish a mechanism for the distribution and sharing of rural tourism benefits, and form a long-term mechanism for rural tourism poverty reduction.

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.

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.

Improving green energy efficiency is crucial to promoting China’s high-quality economic development and reducing the environmental pollution. In this paper, the Malmquist-Luenberger index measures the green energy efficiency of 30 provinces in China from 2004 to 2019. Based on the measurement results, the spatial Durbin model is used to empirically study the impact of environmental regulation on green energy efficiency and its spatial spillover effects. The results show that China’s green energy efficiency is low, and its growth mainly comes from technological progress (TECH) rather than technological efficiency (EFFCH). The eastern region has the highest efficiency of green energy, followed by the West and the lowest in the Central region. The estimation results of the spatial Durbin model show that both environmental regulation and green energy efficiency have a significant spatial correlation. Environmental regulation can improve the green energy efficiency in the local province but inhibit green energy efficiency in the adjacent provinces. Finally, this paper puts forward relevant policy suggestions according to the research results.