Sustainable development has become a global consensus, and cities are important spatial carriers to achieve sustainable development. There are more than 200 resource-based cities in China. These cities have a single industrial and energy structure. With the gradual depletion of urban resources, they are generally facing problems such as difficult industrial transformation, lagging development of alternative industries, and serious damage to the ecological environment. They are facing multiple challenges to achieve sustainable development. Our paper creatively uses the multiple interactive feedback relationships among the systems of “driving force–pressure–state–influence–response” in resource-based cities to establish a comprehensive evaluation model for the sustainable development of resource-based cities through the comprehensive evaluation index system of sustainable development. It is concluded that the higher the coordination degree of each subsystem in the model is, the stronger the sustainable development ability of the city is, which provides new ideas and suggestions for the sustainable development of resource-based cities. The case study shows that the coordinated dispatching C value tends to 2.216, indicating that the sustainable development evaluation values of each subsystem in the model tend to be close, and the coordination between subsystems is high. This confirms the rationality of establishing a comprehensive evaluation model for the sustainable development of resource-based cities.

为破解农业面源污染治理困境，探索政企农协同治理模式，本文构建地方政府、农业企业、农户的三方演化博弈模型，研究地方政府通过经济激励或行政处罚作用于农业企业，农业企业借助产业链主导优势，通过农产品分级收购和绿色溢价返还等方式倒逼农户绿色生产的内在机理，以及协同治理成为演化稳定均衡的条件。研究表明：①适度的经济激励既能保证地方政府环境规制的持续推进，又有利于激发农企的主导治理行为；②降低农企的主导治理成本、提高农企对主导治理带来的长期环境收益的重视度有利于农企积极主导；③绿色溢价最优返还比例存在某临界值，只有当返还比例大于该临界值时，农户才倾向于绿色生产，且没有农企主导时需要给予农户更高的绿色溢价返还比例，才能激励农户绿色生产；④三方博弈主体的成本收益比满足一定条件时，系统将演化稳定于理想的均衡状态(1，1，1)。通过对政企农三方协同机理分析，为构建农业面源污染多元共管共治新模式提供理论依据和政策支持。

Rural non-point source pollution governance is an important element of ecological environmental protection，which is related to the construction of rural ecological civilization，national food security and agricultural green development，and the water tank，rice bag and vegetable basket of urban and rural residents．In order to solve the pollution problem of rural non-point source，explore the co-governance mode of multi-subject participation consisting of government，agribusinesses and farmers，evolutionary game model of local government，agribusinesses and farmers is built，the dominant advantage of local government in forcing farmers is explored to “reduce the amount at source” by taking advantage of the leading role of agribusinesses in the industrial chain to link up with the market and farmers．Specifically，local governments act on agribusinesses through administrative orders and financial subsides to supervise and support the development of agribusinesses and gain policy benefits from the central government. Agribusinesses，as government agents，supervise the green production behavior of farmers，after supervising and testing the quality of agricultural products，adopt a graded purchase system or give farmers green premium dividends to take care of farmers，thus driving farmers to provide high-quality green products according to the contract signed between the two parties．At the same time，agricultural enterprises also realize the green supply chain revenue．

在跨国绿色创新合作中,机会主义行为会让本土企业与外商企业之间的合作陷入短期化的尴尬境地。利用三方演化博弈模型,分析了本土企业、外商企业和我国政府在跨国绿色创新合作过程中的策略选择,并运用仿真分析探讨了跨国绿色创新合作中的相关影响因素。研究表明:我国政府应在跨国绿色创新合作的初期给予相应的政策补贴以及税收优惠等支持性政策以促进双方协同绿色创新活动的进行,随着合作的深入和对成本利益的考虑,我国政府最终会用罚金来限制双方的机会主义行为;我国政府的惩罚措施对企业间的合作具有正向作用,过少的惩罚不能限制企业的机会主义行为;本土企业对绿色创新合作中成本的敏感度大于外商企业;外商企业对我国政府政策和协同合作所获额外收益的敏感度大于本土企业。

Since the reform and opening up for 40 years, based on the rapid development of industrial enterprises, China’s economy has achieved a rapid take-off. However, the rough development mode at the cost of resources is now limiting the sustainable development of China’s industrial enterprises, and the previous development mode has also had a serious negative impact on China’s ecological environment. Against the background of deepening economic globalization, attracting foreign investment and strengthening synergistic cooperation between local and foreign enterprises to accelerate the process of green innovation in China’s enterprises have become an important way for solving the problem of insufficient green innovation capacity of China’s local enterprises. However, in the existing cooperation model, opportunistic behaviors have put green innovation cooperation between local and foreign firms in an awkward situation of short-termism. <br/>Although the existing research results have a certain leading and reference role in the development of transnational green innovation cooperation, the research background of most of the current studies is mostly the general cooperation between multinational enterprises. There is a lack of research on the governance of opportunistic behaviors in transnational green innovation cooperation. Most of the studies have only added our government as a set of exogenous variables into the research model, neglecting the main role of our government in the governance of opportunistic behaviors in green innovation and lacking a systematic analysis of the governance of opportunistic behaviors in transnational green innovation cooperation among our government, local enterprises and foreign enterprises.Therefore,to solve this problem, this paper analyses the strategic choices of local enterprises, foreign enterprises and China’s government in the process of transnational green innovation cooperation by using the three-party evolutionary game model, and explores the relevant influencing factors in transnational green innovation cooperation by using simulation analysis. <br/>The results show that the Chinese government should provide corresponding policy subsidies and tax incentives in the early stage of transnational green innovation cooperation to promote the coordinated green innovation activities of both sides. With the deepening of cooperation and consideration of cost and benefits, the Chinese government will eventually restrict the opportunistic behavior of both sides with fines. The Chinese government’s punishment measures have a positive effect on the cooperation between enterprises, and too little punishment can’t limit the opportunistic behavior. Local enterprises are more sensitive to the cost of green innovation cooperation than foreign ones. Foreign enterprises are more sensitive than local ones to the Chinese government policies and the extra benefits gained from cooperation. <br/>Therefore, based on the above findings, this paper puts forward four countermeasure suggestions, with a view to providing reference for the Chinese government to implement different policies for the different characteristics of local and foreign enterprises, as well as the partner selection and contract signing of cooperating enterprises, so as to solve the opportunistic behaviors in transnational green innovation cooperation. First, the regulatory system for transnational green innovation cooperation activities should be improved. Second, different policies should be formulated and implemented at different periods of transnational green innovation cooperation. Then, the cost of participation in transnational green innovation cooperation by local enterprises should be appropriately lowered.Lastly, a system of “black and white lists” for transnational green innovation cooperation should be established.

通过建立由重污染企业、银行业金融机构和地方政府构成的三方演化博弈模型,分析了博弈系统的动态演化过程,并利用Matlab 2018a仿真分析进一步研究了各主体初始意愿和政府规制措施等相关因素对三方博弈演化行为的影响。研究结果表明:地方政府进行规制的初始意愿提高对重污染企业绿色技术创新和银行业金融机构开展绿色信贷有促进作用,且重污染企业策略的演化速度快于银行业金融机构,重污染企业绿色技术创新和银行业金融机构开展绿色信贷的初始意愿提高会减慢地方政府策略的演化速度;地方政府规制的奖惩力度显著促进重污染企业绿色技术创新,补贴力度对推动银行业金融机构开展绿色信贷作用较小;重污染企业创新反馈力度不改变地方政府策略稳定性,寻租成本增大有利于企业向绿色技术创新方向演化。

Green finance represents a novel growth point and serves as a fresh impetus for the advancement of the green economy. It plays an important role in enhancing the ecological environment and promoting high-quality economic development. Currently, the focal point of green finance development in China centers on green credit. Both theoretical and empirical evidence indicates that green credit can effectively facilitate the transition to a green economy and achieve green growth by promoting cleaner production methods, enhancing the efficiency of green technology innovation, and optimizing energy consumption patterns. Nevertheless, as the green credit policy gains traction, challenges such as difficulties in verifying the authenticity of information pertaining to enterprise green innovation, concealment of environmental risks, and the absence of external oversight and guidance mechanisms are becoming increasingly salient. These issues significantly impact the willingness of banking and financial institutions to engage in green credit, thereby impeding the progress of the green financial system. To address these concerns, this paper formulates an evolutionary game model aimed at elucidating the dynamic interplay among enterprises, banking financial institutions, and the government within the context of green credit policy implementation. It further scrutinizes the dynamic influences of the initial participation intentions of decision-makers, government regulations, and the rent-seeking costs incurred by enterprises on the evolutionary system. This examination seeks to provide a certain degree of theoretical foundation and strategic recommendations for advancing the development of green credit.<br/>From the perspective of bounded rationality, this paper analyzes the strategy selections of local governments, heavily polluting enterprises, and banking financial institutions. It proposes relevant basic assumptions grounded in evolutionary game theory. Subsequently, using Wolfram Mathematica 13.0, the revenue payoff matrix and evolutionary stable points are derived. The evolutionary stable strategy of the three-party game system is further delved into across four scenarios. Ultimately, based on the actual situation and initial parameter constraints, and in alignment with model parameter settings related to government regulation, banking financial institution investment, and enterprise green technology innovation, Matlab 2018a is utilized to simulate the dynamic evolution process of strategy choices among heavily polluting enterprises, banking financial institutions, and local governments under varying initial conditions. The influence of each subject’s initial willingness, local government incentives, punishments, subsidies, heavily polluting enterprises’ innovation feedback coefficients, and rent-seeking costs on the three-party game system is analyzed based on the simulation results.<br/>The results show that: A)An enhancement in the local government’s initial regulatory willingness can motivate heavily polluting enterprises to embrace green technology innovation and encourage banking financial institutions to implement green credit practices. Notably, the rate of strategic evolution among heavily polluting enterprises is swifter than that of banking financial institutions. As the initial willingness of both heavily polluting enterprises and banking financial institutions rises, the evolutionary pace of local government strategies decelerates. B)Government incentives and penalties serve as substantial drivers for heavy pollution enterprises to adopt green technology innovation. However, subsidies play a comparatively minor role in nudging banking financial institutions towards green credit strategies. C)The innovation feedback coefficient of heavy pollution enterprises does not alter the regulatory strategies of local governments. Conversely, an escalation in rent-seeking costs favors enterprises in choosing green technology innovation strategies.<br/>

In the context of achieving carbon peak and carbon neutrality goals, the power industry has become a key and challenging place to promote the green and low-carbon transformation of the economy and society. We selected green power generation enterprises and thermal power generation enterprises in the power industry as the research objects and applied relevant theories such as game theory and low-carbon economy theory to analyze the low-carbon transformation path of electricity under the “dual carbon” goal. We quantitatively analyzed the competition and cooperation relationship between green power and thermal power. Based on mutual benefit preferences, a competitive game model was constructed, and the optimal competitive equilibrium electricity quantity and price of both parties were discussed in different scenarios. The master–slave game problem was transformed into a double-layer game model and solved using the GA algorithm. We draw the following conclusions: (1) When green power enterprises and thermal power enterprises compete to achieve equilibrium, a high degree of altruistic willingness is a necessary condition for both parties to maximize their own utility. (2) A high-level mutually beneficial relationship is a key factor in effectively improving overall profits. (3) In the long-term mutually beneficial competitive relationship between green power and thermal power, by quantitatively adjusting the internal and external factors that affect system evolution, the quantitative adjustment of the feasible domain boundaries of the evolution of the mutually beneficial competitive relationship can be achieved, thereby influencing the existing transformation of the competitive relationship to evolve toward the desired direction.

We present a new estimator for causal effects with panel data that builds on insights behind the widely used difference-in-differences and synthetic control methods. Relative to these methods we find, both theoretically and empirically, that this “synthetic difference-in-differences” estimator has desirable robustness properties, and that it performs well in settings where the conventional estimators are commonly used in practice. We study the asymptotic behavior of the estimator when the systematic part of the outcome model includes latent unit factors interacted with latent time factors, and we present conditions for consistency and asymptotic normality. (JEL C23, H25, H71, I18, L66)