During the critical period of agricultural green transformation, clarifying the evolutionary logic of farmers' green production behavior under a multi-stakeholder framework provides significant insights for implementing "Dual Carbon" goals, establishing long-term mechanisms for high-quality agricultural development, and resolving deep-seated contradictions in agricultural non-point source pollution. Based on the social co-governance and public participation framework, this paper constructs a tripartite evolutionary game model involving government departments, farmer groups, and the general public, grounded in cost-benefit analysis, social governance friction, and evolutionary game theory. Through simulation, the study explores the equilibrium states and the specific impacts of varying parameter values on stable points. The findings reveal that: (1) The "interest price scissors" (benefit disparity) between green and conventional production is the key determinant of farmers' strategic equilibrium. Once this structural contradiction is resolved, green production becomes the optimal strategy. (2) Farmers are highly sensitive to marginal cost-benefit fluctuations, leading to a sequential behavioral cascade: farmers retreat first, followed by the government, and finally the public. (3) Public participation cost is the pivotal variable for activating the co-governance mechanism, and the application of digital governance tools determines the time required to reach equilibrium. (4) A "Success Paradox" exists in government regulation; incentive mechanisms must be adjusted promptly after initial success. (5) Integrated policy combinations outperform single instruments; breaking the "locked-in" state requires a policy shock of sufficient intensity. This research offers a theoretical basis and policy enlightenment for optimizing the social co-governance landscape and promoting sustainable agricultural modernization.

This study evaluates the efficiency of fiscal support policies for village-level collective economies in S Province, a frontier region of China, over the analytical period of 2018-2023, which includes the policy implementation years (2019-2022) plus one pre-policy and one post-policy year. Integrating theories of collaborative governance, resource alertness, and inclusive rural development, we construct an efficiency measurement framework to assess policy performance across 13 regions. Static efficiency is measured using DEA-BCC and super-efficiency SE-DEA models, while dynamic total factor productivity (TFP) is analyzed via the DEA-Malmquist index. The entropy-weighted method is employed to ensure robust indicator weighting. The findings reveal the following: (1) The average super-efficiency is 0.855, indicating relatively high expenditure efficiency but significant regional disparities and room for improvement. (2) The TFP declined by an average of 9.7% over the analytical period (2018-2023), primarily due to technological regression, despite stable technical efficiency. Based on the TFP performance, regions are categorized into high-, middle-, and low-efficiency tiers. Accordingly, we propose policy recommendations including efficiency-driven funding allocation, long-term support mechanisms combining technological innovation and management empowerment, regionally differentiated strategies, and strengthened multi-stakeholder collaboration. This study provides empirical evidence for optimizing fiscal policies to promote the sustainable development of rural collective economies and advance inclusive rural development in frontier regions.

Multilevel public finance is a social-administrative system in which authority, fiscal resources, information, and implementation responsibilities circulate across government tiers. China’s Province-Managing-County (PMC) reform provides a case for evaluating how governance redesign affects county-recorded fiscal expenditure. We define the system boundary as the province–prefecture–county fiscal governance chain and decompose the reform into administrative power delegation (D1), which changes decision rights, and fiscal direct reporting (D2), which changes fiscal-flow paths. Using a county-level panel of 2219 counties in 31 provinces from 2000 to 2019, we combine generalized synthetic control, Matrix Completion, panel unconditional quantile regression, and spatial diagnostics. The average effect is positive in the preferred gsynth specification and the Matrix Completion benchmark, but the magnitude is model-dependent: 16.7% under gsynth and 8.1% under Matrix Completion, with further sensitivity to latent-factor choices. Reform-type estimates and a common-model CATE equality test suggest stronger estimated effects for D1 than D2, interpreted as institutional heterogeneity rather than causal dominance. Distributional and spatial diagnostics indicate weaker lower-tail effects and geographically uneven absorption. The findings suggest that changing decision rights and fiscal-flow paths can reshape county fiscal system outputs.

County economic growth in multi-tiered fiscal systems depends not only on the volume of transfers but also on whether those transfers pass through intermediary governments. This paper separates administrative delegation from fiscal chain redesign in province-managed county reforms in China. We study 1537 counties from 2000 to 2023 and compare D2, which creates direct province-county fiscal accounts, with D1, which delegates administrative authority but keeps the prefectural intermediary. The empirical design uses panel difference-in-differences estimators, synthetic difference-in-differences, double machine learning robustness checks, and exploratory heterogeneity diagnostics. Based on a placebo-corrected lower bound and a cross-estimator upper bound, D2 is associated with a conservative growth range of 0.35 to 1.0 percentage points per year, while the D1 estimate is imprecise. D2 is also associated with higher contemporaneous per capita fiscal expenditure, but the one-year lagged mediator check does not support a fully identified expenditure mechanism. Heterogeneity patterns are consistent with stronger effects in transfer-dependent counties, but they remain exploratory. The outcome is county economic growth, not a composite sustainability index. The results support a focused governance claim. More reliable transfer delivery is consistent with improved local growth capacity, while fiscal, social, and environmental sustainability remain outside the measured outcome space.

This study evaluates the impact of fiscal support policies on village-level collective economies in Province S, a frontier region in China. Using panel data from 2195 administrative villages (6585 village-year observations) spanning the period before, during, and after policy implementation, we construct a “policy empowerment–resource matching–governance synergy” framework and employ two-way fixed effects, instrumental variables, heterogeneity analysis, and mediation models. The results show that (1) fiscal support significantly increases village collective income by about 7%, a finding that is robust to endogeneity and various checks; (2) the policy works better for mid-to-distant suburban villages, those without collective land, villages with pre-policy income below 50,000 yuan, and villages that adopted models of land transfer, high-standard farmland, equity dividends, specialty agriculture, or factory leasing, confirming resource matching; (3) the policy operates through increased project net returns, social capital, farmer participation, and multi-departmental coordination, validating governance synergy. This study provides micro-evidence from a frontier region and practical insights for optimizing fiscal support policies.

The complex market environment places unprecedented pressure on business decision-making processes. Effectively utilizing existing social resources to establish risk prevention mechanisms and accurately assess an enterprise’s risk-taking capacity has become a core issue for corporate survival and development. This paper examines 1810 listed companies on the Shanghai and Shenzhen A-shares markets from 2010 to 2022, constructing comprehensive social networks based on multiple corporate governance entities. It investigates the influence and transmission mechanisms of corporate social networks on risk-taking levels. The results reveal that (1) enhanced corporate social network centrality, structural holes, and connectivity significantly and positively affect corporate risk-taking levels; (2) information transparency and corporate governance quality serve as important mediating mechanisms through which social networks influence corporate risk-taking; (3) significant heterogeneity exists regarding executives’ backgrounds and industry attributes—specifically, in firms with executives possessing financial backgrounds and in high-tech industry enterprises, network characteristics play a more pronounced role in promoting risk-taking. This research not only enriches the literature on factors influencing enterprise risk-taking but also provides theoretical foundations and practical insights for improving corporate risk management capabilities through optimized social network structures.

Amidst escalating global policy uncertainties and the painful transformation phase of the Chinese economy, studying the time-varying characteristics of risk spillover among the real economy, real estate market, and financial system holds substantial practical relevance for preventing and resolving significant systemic risks. This paper employs the TVP-VAR-DY model, selects indices from the real sectors to construct a risk spillover index for the real economy, and incorporates indices from the real estate and financial sectors to develop a trivariate SV-TVP-VAR model for empirically analyzing the time-varying nature of risk spillover relationships among these variables. This study reveals that risk spillover among different sectors of the real economy exhibits asymmetry and volatility, with the industrial sector experiencing the highest degree of risk spillover. The prosperity of the real estate market consistently aligns with that of the financial system; however, shocks during periods of risk accumulation in the real estate market significantly amplify risks in the real economy. The financial system serves the real economy, which suffers lesser impacts. Nonetheless, post-2008, the financial system’s support for the real estate market has gradually diminished. Crises exacerbate the extent of risk spillover, but the causative factors and socio-economic context create heterogeneity in fluctuations. Based on these findings, in response to the current real estate shock, the Chinese government should discuss the real economy, the real estate industry, and the financial system within the same research framework. Policies should primarily focus on fiscal measures to promote the recovery of the real economy more rapidly. Additionally, by allowing local governments to implement tailored policies based on local conditions, potential homebuying demand has been effectively stimulated.

Land system face multiple threats due to the long-term effects of climate change, global geopolitical and economic. Our research simulates the static and dynamic resilience of land systems under increasing socioeconomic pressures and frequent disturbances from natural disasters. We use an improved load-capacity model to simulate the cascading failure effects of agricultural land systems. The study finds that parameters change after deliberate attacks much earlier than random attacks that cause network collapse. The core nodes in the trade structure carry most of the functions, and such regions and land types should be focused on. Cascading failures make the network more vulnerable due to the transmissibility of pressure. Static attacks can cause network collapse when more than 30% of nodes are attacked, while dynamic attacks only need to attack 10% of nodes. According to parameter optimization, the node capacity should be maximized while reducing the gap in the initial load of the nodes, thereby weakening the cascading effect. To ensure the reliability of the results, the article conduct robustness tests. Finally, in order to develop sustainable land systems, the article propose that it is necessary to assess resilience, identify key elements, effectively monitor land systems, and develop sound land protection plans.

In this paper, we propose a new approach to analyze financial contagion using a causality-based complex network and value-at-risk (VaR). We innovatively combine the use of VaR and an expected shortfall (ES)-based causality network with impulse response analysis to discover features of financial contagion. We improve the current research methods by building a Granger causality network on VaR and ES and using conclusions drawn from network analysis as a foundational step before impulse response analysis. First of all, we select 30 stock indices that are very well-known globally and collect their trading data. After calculating the risk indicators of VaR and ES, we perform the Granger causality test on them and then build networks based on their respective Granger causality square matrix. Next, we examine the networks’ topological features to discover different degrees of risk transmission among all stock indices in the system. Lastly, we identify the most and the least active stock indices in the risk transmission network and conduct impulse response analysis on them. We discover that BSESN (India S&P BSE SENSEX) is the most risk-sensitive stock index as its VaR significantly increases by 0.03–0.04% and its ES jumps even more, by 0.07–0.08%, in response to an impulse from a few key stock indices. We also find that either PSI20 or XU100 is the most risk-proof stock index, depending on whether we choose VaR or ES as a risk indicator.

This paper uses CiteSpace software to conduct a bibliometric analysis of research literature under the topic of game theory which specifically focuses on energy and natural resources in the Web of Science Core Collection. The results show that: since 1990, the number of documents covering the topics of “energy” and “game theory”, and “natural resources” and “game theory” has continued to grow steadily, and entered an explosive growth stage after 2017. In terms of disciplinary classification of published papers, Energy & Fuels has the highest frequency, 311 with a significant centrality, 0.22. In terms of journal publications, Applied Energy is the most cited journal whose frequency is 311 and centrality is 0.01. In terms of country, China has the highest number of published papers, and the United States with the highest overall centrality of papers. North China Electric Power University published 31 papers, the largest number of documents from one institution. In terms of author productivity, Puyan Nie has been the most productive author since 2016. The co-citation cluster analysis on the literature topics shows that the game theory of energy and natural resources have roughly gone through four stages: (1) From 1990 to 2009, this is the embryonic stage with no more than 15 new papers per year; (2) From 2010 to 2014, this stage had microgrid as its mainstream research topic, and other topic clusters officially emerged; (3) From 2015 to 2017, the main research topics became the integrated energy system, subsidy mechanism and household energy management, with a hot topic on the evolutionary game process between government and enterprises; (4) From 2018 to 2021, this stage continued to focus on the previous topics, and the research goes much deeper, resulting in more models and new green technologies. Finally, the keyword analysis concludes with nine themes of concern in this research field, and has come to a comprehensive summary of the mainstream research methods in the field of game theory of energy and natural resources.

With China’s rapid industrialization and urbanization, sustainable urban development is one of the most significant challenges that the country will face in the future, and the rational evaluation and improvement of urban land-use efficiency (ULUE) are becoming crucial for land and urban development. Existing studies rarely examine ULUE, and there is a dearth of urban land use analysis in terms of different functions, regional differences in levels of development, and innovation capacity. Therefore, we take the Pearl River Delta (PRD), China’s economic and innovation center, as our research target and propose a new framework to analyze its comprehensive ULUE. First, we summarized the patterns of land-use change in the PRD region as a whole along with nine major cities from 2000 to 2020 on the basis of data from the China Land Survey. Then, we constructed a multidimensional evaluation model for ULUE and analyzed the spatial differences and causes of multidimensional performance in nine major cities. Finally, we calculated the innovation capability index of the PRD region and established a coupling coordination–evaluation model to analyze the coordination relationship between innovation capability and urban land use. The three main findings of this study are as follows. (1) The growth rate of urban land in the PRD region as a whole exhibited stage differences. (2) The comprehensive ULUE in the PRD urban agglomeration was high, and the spatial variability of functional performance in each dimension was obvious. (3) The level of coordination between innovation capability and urban land use in the PRD region was high, and the coupled coordinated development exhibited a decreasing spatial distribution pattern. Thus, the PRD region mainly relies on the cities of Shenzhen and Guangzhou to drive innovation development of the region.

China has experienced dramatic changes in its land use and landscape pattern in the past few decades. At present, a large number of studies have carried out in-depth and systematic analyses on the landscape variation and its ecological effects in Central and Eastern China, but research on the northwest arid region is relatively deficient. In the present study, the city of Hami, which is located in the northwest arid region of China, was selected as the study area to investigate the responses in the habitat quality, water yield and carbon storage to land use and cover change during 2000–2020. We found that (1) during the entire study period (2000–2020), the variation intensity of the first decade (2000–2010) was significantly greater than that of the second decade (2010–2020), and the conversion between desert and grassland played a dominant role in the conversion among these land types. (2) The maximum value of the habitat degradation degree in Hami city increased during the study period, indicating that the habitat presented a trend of degradation. (3) The total carbon storage in Hami city was approximately 11.03 × 106 t, 11.16 × 106 t and 11.17 × 106 t in 2000, 2010 and 2020, respectively, which indicated an increasing trend. (4) According to the calculation, the average water yield and the total water conservation showed a decreasing trend in the study area. The corresponding results will help to formulate protective measures that are conducive to the restoration of ecosystem functions in extremely arid regions.

Flash floods are devastating natural disasters worldwide. Understanding their spatiotemporal distributions and driving factors is essential for identifying high risk areas and predicting hydrological conditions. In this study, several methods were used to analyze the changing patterns and driving factors of flash floods in the Altay region. Results indicate that the number of flash floods each year increased in 1980–2015, with two sudden change points (1996 and 2008), and April, June, and July presented the highest frequency of events. Habahe and Jeminay were known to have high flash flood incidences; however, currently, Altay City, Fuhai, Fuyun, and Qinghe are most affected. In terms of driving force analysis, precipitation and altitude performance have a key impact on flash flood occurrence in this settlement compared to other subregions, with a high percentage increase in the mean squared error value of 39, 37, 37, 37, and 33 for 10 min precipitation in a 20-year return period, elevation, 60 min precipitation in a 20-year return period, 6 h precipitation in a 20-year return period, and 24 h precipitation in a 20-year return period, respectively. The study results provide insights into spatial–temporal dynamics of flash floods and a scientific basis for policymakers to set improvement targets in specific areas.

党的二十大报告提出,中国式现代化是人与自然和谐共生的现代化,并擘画了美丽中国建设蓝图.当前,生态文明建设的新征程已开启,笔者认为,应站在人与自然和谐共生的中国式现代化的高度来认识自然资源工作,从实现美丽中国建设的战略目标出发来推进自然资源工作.

Climate change is one of the most urgent challenges facing the world. All countries should take joint actions to achieve the goal of carbon neutrality, which include controlling global warming to within a 1.5 °C temperature rise, to mitigate the extreme harm caused by climate change. However, ways in which to achieve economically and environmentally sustainable carbon neutrality are yet to be established. Carbon neutrality appears frequently in international policy and the scientific literature, but there is little detailed literature. It is necessary to conduct an in-depth analysis of the development context of its research. This paper analyzed the literature on carbon neutrality using bibliometric methods. A total of 1383 research papers were collected from the “Web of Science core database” from 1995 to 2021. Descriptive statistical analysis and keyword co-occurrence and literature co-citation network analyses were utilized to sort the research hotspots, and the detected bursts, the top 30 keywords in terms of word frequency, and 12 clusters were selected. It was found that the existing carbon neutrality research literature mainly focuses on carbon neutrality energy transformation, carbon neutrality technology development, carbon neutrality effect evaluation, and carbon neutrality industry examples. The analysis process involved comprehensively reading the key articles and considering the co-citation, burstiness, centrality, and other indicators under clustering; the carbon neutrality research was then divided into three stages, and evolving themes were observed. Based on the burst detection, this paper holds that with the energy structure transformation, energy consumption assessment and carbon neutrality schemes of various industries, carbon dioxide capture technology, and biogas resource utilization, urban carbon neutrality policy will become a research hotspot in the future. This paper helps to provide a reference for scholars’ theoretical research and has important reference value for policymakers to formulate relevant policy measures. It is helpful for enterprises to make strategic decisions and determine the direction of technology, for R&D and investment, and it is of considerable significance to promote the research of carbon neutrality technology.

草地是中国面积最大的陆地生态系统,其在保障国家“大粮食”安全生产、遏制气候变化、维持生物多样性、涵养水源、促进可持续社区建设等人类可持续发展目标中具有极其重要的价值.由人类活动和气候变化导致的草地生态系统服务能力衰退、生态功能降低,严重威胁着中国生态经济安全,而问题的产生原因和解决办法又要回归于草地生态系统本身.因此,需要明晰草地生态系统多功能性和多重服务与可持续发展目标的关系,科学研判家畜管理对可持续发展目标的重要作用.据此文章提出4条保障措施支撑未来草地健康发展,为实现全球可持续发展目标贡献中国智慧提供路径选择.

自"十四五"规划开始,各地普遍将自然资源发展规划作为重要专项规划,由政府部署编制和批准实施.自然资源发展规划的编制实施将成为常态化工作,而自然资源发展战略研究作为规划编制的前期核心工作也需要不断深化和规范化.自然资源发展战略的研究内容、基本理论、研究方法和实施工具,构成了自然资源发展战略的研究范式.本文认为,自然资源发展战略的研究内容由规划体系、自然资源属性和管理体制综合决定,其基础理论是生态文明基本理念、制度体系、辩证思维和自然资源治理理论,研究方法主要有SWOT分析、资源环境承载力评价、SD-CA方法等,实施工具包括重大举措、重大工程和重大改革.按照上述研究范式,本文对贵州省"十四五"时期自然资源发展战略进行了实证研究.

新修订的《中华人民共和国土地管理法实施条例》(以下简称新《条例》)于2021年9月1日起施行,这是继2019年8月修订土地管理法后,我国土地制度又一次重要的立法行动.新土地管理法最主要的制度突破是将以放权赋能为导向的农村土地制度改革经验,特别是允许集体经营性建设用地入市写进法律以及大幅下放建设用地审批权限.

This paper empirically investigates the impacts of climate factors, including temperature and precipitation, on household portfolio choices based on the panel data of 2,110 households continuously observed from the China Family Panel Studies (CFPS) for 2010, 2012, 2014 and 2016. The results show that climate factors significantly affect household portfolio choices mainly through channels including income, asset prices, health and risk attitudes. Furthermore, the results also show that climate factors moderate the effects of income, asset prices and investors’ confidence on household portfolio choices. This research contributes to the literature by introducing theories regarding behavioral finance and climate economics into the research on household portfolio choices, which provides insights into the impact mechanisms of climate factors on household behaviors and enriches the studies of behavioral investment decision making and environmental economics.