Green credit is an indispensable funding source through which China can achieve its carbon neutrality goal. This paper quantifies the influences of different green credit scales on energy structures, carbon reduction, the industrial economy, and the macroeconomy. It creates a green credit mechanism related to green technology innovation in a Chinese carbon neutrality computable general equilibrium (CGE) model and integrates energy, environmental, economic, and financial (3EF) systems. The green credit scale can influence green technology innovation and hence CO₂ emissions. The results show that (1) green credit can accelerate China’s achievement of its carbon neutrality goal, and the larger the green credit scale, the less time it takes to achieve goals; (2) the influence of green credit scales confers marginal decreasing effects with realistic policy considerations; (3) using a cost–benefit perspective, 60% is the most appropriate green credit scale to use to achieve dual carbon goals in China; (4) the different green credit scales have a heterogeneous impact on the industry output, and high-carbon-emission producers from nonenergy industries need to pay attention to their green credit risk. This research provides a scientific reference for the policy design of China’s future green financial market development.

The coronavirus outbreak in the global scale has raised the concern about potential risks to the global economy. This research applies the global computable general equilibrium model (CGE) to simulate the economic shocks of Covid-19, taking into account the changes in labor supply, consumption, international trade and shocks to global tourism. The finding suggests a significant impact of the disease on China’s economy and industries, which may continue to threaten the global supply chain and economic growth.

Computable general equilibrium models have been a popular tool for policy analysis in recent decades, but rarely applied for fisheries policy and management. This paper presents an inter-temporal computable general equilibrium model with fisheries details. While the model in a full-scale and disaggregate way describes the structure and dynamics of a regional fisheries economy, it further specifies the heterogeneous bottom-up fish producers, such as harvesters, aquaculture and fish-processing firms, and links fisheries with the top–down non-fisheries economic sectors. In addition, the model can be externally linked with fish biological models to consider interactions between economic and biological systems. The model is designed to provide a comprehensive tool for analysis of new fisheries policy in general and to study five European fishery regions in particular. The empirics in the paper evaluate the impact of several important management and policy instruments on the Salerno economy and on recovery of endangered species.

The COVID-19 outbreak in the global scale has raised the concern about severe economic effects caused by the pandemic disease. Extant literature on global pandemic mainly focuses on the direct and indirect economic costs of the disease. However, the global outbreak of public health emergencies should not only be assessed by a partial equilibrium approach by merely focusing on the health sector or disease-related costs. A comprehensive approach of assessment is essential to evaluate the overall economic impacts of the global pandemic. In this sense, the episode of global COVID-19 does not fit into the standard approach, as this wide-spread disease has caused economy-wide shocks to both supply and consumption sides. The disruption of global supply chains and shrinking demand of consumption has tremendously damaged global economy, which also caused spillover effects on China’s regional economy through the globalized value chains and international trade. To measure the global economic impacts of the pandemic on China’s regional economy as well as to provide practical policy suggestions for economic recovery, this paper applies and integrates the global and regional computable general equilibrium (CGE) models to conduct an economy-wide analysis, taking into account the changes in morbidity, labor supply, consumption, international trade, shocks to global tourism and oil demand. The research set four scenarios to capture the nature of the pandemics in different stages: (S1) the outbreak within China; (S2) the spread of the disease to advanced countries and regions; (S3) the escalation of the pandemic in the global scale; and (S4) the second wave of the pandemics. As a focal point of China’s regional planning and opening-up policies, the Guangdong-Hong Kong-Macao Greater Bay Area entails greater attention amid the pandecmic. This study provided an insight into challenges and opportunities the local economy faces in dealing with the pandemic and in economic recovery. The standard GTAP framework is unable to capture the unevenness of regional economies inside the country. In the meantime, the regional CGE model is inadequate to analyze the interaction of the regional economy and the global economic system. Therefore, it is essentially important to build an integrated framework to address the dynamic interaction between the regional and global economic systems and to acutely assess the global shocks to local macroeconomics and industries. To achieve this goal, this study builds an integrated global-regional framework that links the GTAP model to the regional TERM model and transmits the shocks of global pandemics to the regional model. The results show that: (1) The global pandemic has significant negative effects on China’s economy and industries, especially on China’s export-oriented industries such as automotive, machinery and electronic sectors; (2) China’s trade with the key trade partners including the United States, the EU, Japan, Korea and ASEAN has been significantly affected due to the economic shocks, which may cause restructuring of global value chains in the post-pandemic era; (3)For the Greater Bay Area, cities relying on export-oriented economy and manufacturing industries have greater damage on their economic growth; (4)The inter-regional flow of commodities has been obstructed by the pandemic, which will further generate negative spillover effects on the regional industrial clusters within the area. To strengthen the local governance in dealing with the pandemic and in steering the long-term economic reforms, the government should pay more attention to the reform in the public health system as part of the supply-side structural reform. In terms of the industrial reforms, the efforts of moving up the value chain is essential in building a high-quality mode of economic growth and in pushing for the restructuring of global value chains. Cross-regional cooperation mechanism should be put forward by leveraging “New Infrastructure” projects and consumption-driven economic policies. In short, the property of the Greater Bay Area is not only important for local economic recovery but also for deeper integration of Hong Kong and Marco into China’s economic development.

Chinese 自2019年5月以来，中美贸易战再次升级。美国宣布对中国5500亿美元商品加征关税，中国随后采取反制措施。本文采用全球可计算一般均衡模型（CGE），根据中美贸易战不同阶段政策进行短期、长期模拟。模拟结果表明，中美贸易战将为两国带来两败俱伤的结果，其中中国短期、长期福利受损程度都要大于美国。中美两国居民消费、政府支出、投资、就业、贸易将出现全面下滑。行业部门指标方面，中国出口大类电子设备、机械设备部门行业产出下滑幅度最大；美国农产品部门则受损严重。除服务贸易外，中美双边贸易量都将经历大幅下跌。中国国内商品价格将有所下跌，消费者物价指数进一步萎缩，美国大部分商品物价将出现上涨，贸易战成本最终将转嫁至美国消费者。由贸易战引发的影响将波及到其他经贸领域以及世界其他地区，对经济增长带来负面影响。 English China-US trade war has been escalating since May 2019. The US announced to increase tariffs on US$550 billion of Chinese goods. Then China announced a new round of retaliatory tariff on the US goods. This article uses global Computable General Equilibrium model (CGE) to examine the short- and long-term economic impact of the China-US trade war. The result shows that China and the US will be negatively affected by the trade war. But trade war escalation will hit China harder than the US in the short and long term. Both countries’ consumption, government expenditure, investment, employment and trade will slow down. In terms of industrial sectors, the outputs of China’s electrical equipment and machinery will plunge. The US agricultural sector will be seriously damaged. Except service trade, China-US bilateral trade volumes will experience a large amount of reduction. The prices of China’s domestic goods will decline with CPI deflation. But for the US, the prices of most domestic goods will rise, which means that the trade war will eventually hurt American consumers.