Agricultural green development plays a crucial role in addressing the conflict between agricultural production and ecological environmental protection. This study aims to analyze the impact and mechanisms through which digital inclusive finance influences agricultural green development, providing empirical evidence to support the role of digital inclusive finance in promoting sustainable agricultural practices. Using panel data from 30 provinces (cities and districts) in China spanning from 2011 to 2020, this study measures regional agricultural green development levels using the entropy power method. By clarifying the theoretical mechanisms behind the relationship between digital inclusive finance and agricultural green development, this research employs panel fixed effects, mediation effects, and threshold regression models to empirically examine the impact of digital inclusive finance, specifically its coverage breadth, usage depth, and digitization level, on agricultural green development. Furthermore, this study explores the threshold effects of digital inclusive finance on agricultural green development. The findings from this study indicate that digital inclusive finance significantly contributes to agricultural green development, with a double-threshold effect observed as follows: when digital inclusive finance surpasses critical thresholds, its impact on agricultural green development intensifies. This result remains robust after conducting a series of endogeneity and robustness tests. The mechanism analysis reveals that digital inclusive finance drives agricultural green development by fostering technological innovation and increasing farmers’ income. Heterogeneity analysis further demonstrates that digital inclusive finance has a substantial impact on agricultural green development in eastern China compared to the central and western regions. Consequently, this study suggests that digital inclusive financial services should be further expanded and deepened to foster the integration of financial services with agriculture, creating a sustainable development model that promotes shared prosperity and effectively supports the green development of agriculture.

The growth of farmers’ income is one of the most critical issues in China’s “Three Rural Issues,” and optimizing fiscal policy support and improving credit supply are crucial to improving farmers’ income. Based on the panel data of 30 Chinese provinces from 2003 to 2020, this paper develops a PVAR model in order to explore the relationship between agricultural credit, fiscal support for agriculture, and farmers’ income from a dynamic perspective, considering regional heterogeneity. The empirical results show the following factors for farmers’ income growth: (1) From the GMM estimation, the positive correlation between fiscal support for agriculture is stronger than that of agricultural credit. (2) From the impulse-response function, in the eastern region, the positive shock of agricultural credit is positively correlated in the short run, but it will be negatively correlated as that of fiscal support for agriculture in the long run; in the central region, the positive shocks of agricultural credit and fiscal support for agriculture are persistently positively correlated; in the western region, the positive shocks of agricultural credit are persistently negatively correlated, while fiscal support for agriculture will be positively correlated in contrast. (3) From the variance decomposition, agricultural credit contributes more to famer’s income growth in the short run, while fiscal support for agriculture contributes more in the long run. The policy implications for promoting farmers’ income growth include implementing regionally differentiated agricultural credit development strategies, reasonably enhancing fiscal support for agriculture, and optimizing the structure of fiscal support for agriculture.

The forestry industry is a low-carbon green industry with great potential for development, but its current development model is facing multiple dilemmas that urgently require a shift to high-quality forestry development. Neoclassical theory and endogenous growth theory consider technology innovation as the foundation of economic growth. In order to explore the impact of forestry technology innovation (FTI) on the economic growth of forestry industry, this paper uses the entropy method, spatial Durbin model, and threshold model to explore the spatial effect of forestry technology innovation on forestry industry economy for analysis and exploration of the non-linear relationship between the two, and the panel data from 31 provinces in China from 2002 to 2020 are used as the sample for empirical study. Results show that: (1) Forestry technology innovation has a significant role in promoting the economic growth of the forestry industry and has obvious spatial spillover effects, which also promotes the economic growth of forestry in neighboring regions. (2) There is a threshold effect of forestry technology innovation on the economic growth of the forestry industry. When the forestry technology innovation exceeds its optimal interval, its effect on the economic growth of forestry industry shows diminishing marginal benefits. (3) Forestry technology innovation has industrial heterogeneity on the economic growth of the forestry industry. Therefore, managers should take advantage of the growth effect of forestry technology innovation in the forestry industry at the level of sustainability, and further make full use of the spatial effect resulting from the flow of technology to establish a system of communication and learning to form a virtuous coordination of the forestry economic environment for the high-quality development of the forestry industry.

Forestry output efficiency is key to forestry development. China is now promoting the development of forestry, and thus the research on forestry output efficiency is of practical significance. Through the data envelopment analysis (DEA)-Malmquist index, spatial autocorrelation model, and fixed effect model of panel data, in this study, we analyzed the forestry output efficiency of China with indicators, such as the fixed asset input, employed personnel, total output value, and timber output, and drew the following conclusions. In the time series, the forestry total-factor productivity (TFP) in China saw a rapid increase, which is attributed to the technological progress change (TC), whereas the efficiency change (EC) imposed negative influences upon the forestry TFP. In the spatial distribution, there was a difference in the increase in the forestry output efficiency among the eastern, central, and western regions of China, with the eastern region having the fastest growth and the central region having the slowest growth. According to the spatial autocorrelation, there was spatial aggregation (high–high (HH) and low–low (LL)) with a significant positive correlation. Through the optimized fixed effect regression model, the fixed asset input, employed personnel, total output value, and timber output all had significant influences on the comprehensive technical efficiency of the forestry output, wherein the input indicators had negative influences, and the output indicators had positive influences.

Forests provide goods and services while maintaining ecological security. However, the market does not adequately reflect their economic benefits, posing a significant challenge to the Payments for Forest Ecosystem Services (PFES). The involvement of multiple stakeholders with varying responsibilities and interests complicates collaboration and hinders effective governance. This study proposes an integrated approach using stakeholder analysis, social network analysis, and evolutionary game analysis to explore the collaborative governance of stakeholders in PFES. Through field surveys, the study empirically investigates PFES in China, demonstrating the effectiveness of this integrated approach. The results indicate the following: (i) Stakeholders are classified into three categories; the key stakeholders include the central and local governments, forest managers, and paying users. (ii) Stakeholders still need to strengthen collaboration. Local governments, forest managers, their employees, and communities exert widespread influence; paying users and research institutions have high efficiency in resource sharing. (iii) Five evolutionarily stable strategies are observed at different stages. Government intervention is crucial for changing the stagnant state. Benefits and government incentives have a positive impact on stakeholder collaborative governance. The research findings offer theoretical insights to enhance stakeholder collaboration and promote the development of the PFES. Key strategies include addressing key stakeholders’ needs, diversifying incentives, and establishing an accessible information platform.

State-owned forest farms (SOFFs) help maintain forest ecological security and hold an important strategic position in China’s development. In this study we used 1305 sample data from 16 provinces, a structural equation model (SEM), and a projection pursuit model (PPM) to evaluate the self-development abilities of SOFFs, and used the obstacle model to analyze factors hindering these abilities in various provinces, at different development levels, and with different subordination relationships. The results show that (1) the self-development abilities of SOFFs remain weak, and there are many more provinces with low than with high levels; (2) the subordination relationship significantly affects the self-development ability, which is the highest for municipal SOFFs; and (3) social services, people’s livelihood security, management ability, and forest resources are the main constraints for SOFF’s self-development abilities, and people’s livelihood security has the greatest influence for SOFFs with high self-development abilities, while social services are the most important for those with low self-development abilities.