Considering the significance of green governance in economic restructuring and the green technology revolution, this study examines the impact of China’s recent green governance policies and their implications in various regions; it also examines new models, methods, and development directions for China’s green governance in the future. Green governance efficiency and spatial patterns have been studied through 2008–2018 data using a three-stage generalized panel Data Envelopment Analysis (DEA) model, spatial autocorrelation model, spatial gravity model, and social network analysis. The study summarizes the status and role of each provincial region in green governance based on the social network of green governance efficiency under the network architecture. It concludes that (1) green governance efficiency in China’s provinces has a U-shaped trend, with non-managerial elements in the external environment masking genuine green governance efficiency. (2) During the study period, the overall efficiency of the industrial system improved. The efficiency of the manufacturing and wastewater stages has been substantially enhanced, but no significant gains were observed in the treatment stages of solid and gas waste. (3) Although China has made progress in enhancing the overall efficiency of its industrial system, there is still potential for improvement. (4) China has established a “three horizontal and two vertical grid-type” green governance spatial correlation structure among the sub-stages of the industrial system, and the radiation impact of major provincial areas would increase overall green governance efficiency.

The purpose of this paper was to analyze the influence mechanism of the new round of Collective Forest Rights Reform (CFRR) on farmers’ production efficiency from the perspective of forestland transfer. Based on the panel data of field investigation in Jiangxi Province, a panel logit model was used to verify whether the new round of CFRR has affected farmers’ forestland circulation behavior. The results showed that the new round of CFRR has played a significant role in promoting forestland circulation. Secondly, the non-parametric DEA method was used to estimate the technical, scale, and comprehensive efficiency of households. DID and panel quantile models were constructed to analyze the impact of forestland inflow policy and forestland outflow policy effects on rural household productivity. The regression results showed that the effect of forestland inflow has had a significantly positive impact on scale and comprehensive efficiency, but it only had a significant effect on technical efficiency in the 0.1 quartile. The effect of forestland outflow was not found to be significant for technical, scale, and comprehensive efficiency, but it was found to be negative for technical efficiency in the 0.75 quartile and negative for scale efficiency in the 0.5 and 0.75 quantiles.

Grain security is an essential issue for countries across the world. China has witnessed over the last decades not only a rapid growth in the volume of the grain production, but also a divergence in its geographical distributions. Existing studies on the influencing factors of grain production have overlooked thus spatial heterogeneity. This paper investigates the factors that cause the geographical heterogeneity in grain output levels in Guangdong province of China, in terms of land, labor and capital. To address the spatial attenuation effect of the influencing factors, we use the Geographically Weighted Regression (GWR) on samples of different spatial ranges, which include a total of 530 southern counties from 2015 to 2017. The results show that (a) the effect of land endowment on grain output vary across the east and the west, and between coastal and inland areas; (b) the effect of labor endowment on grain output are inconsistent in the sign and magnitude of the estimates across counties; (c) the effect of agricultural capital on grain production shows heterogeneity spatially (across the east and the west) and economically (across developed and less developed regions). We then analyze the potential mechanism behind this spatial heterogeneity, as well as its policy implications.

Cropland use stability is vital for sustaining the productive and ecological functions of cropland. Existing multidimensional assessment frameworks rarely distinguish between quantity change and spatial change, nor do they examine their interactions across hierarchical scales. Using annual 30 m land cover data for Guangdong Province, China (1990–2024), this study developed a two-dimensional stability framework integrating quantity and spatial indicators, using a pixel-tracking strategy applied within each five-year interval to capture interannual dynamics. Analyses were conducted at provincial, agricultural zone, and city scales. Results showed that provincial stability exhibited a fluctuating upward trajectory, with the lowest point in 2005–2009. Regional patterns diverged markedly, and city-level stability exhibited spatial heterogeneity, with pronounced disparities between high- and low-stability cities. Grade transition and quadrant analyses further revealed that quantity and spatial stability do not always move in tandem, and single-dimension assessments may provide an incomplete picture of cropland use stability. These findings suggest that incorporating both dimensions into monitoring frameworks could support more differentiated cropland management strategies.