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As China's carbon market continues to develop, its close connection with the financial and energy markets is becoming increasingly apparent. A systematic study of the spillover effects between markets is important, as it can help prevent excessive fluctuations in carbon prices. With this in mind, this study proposes a time‐varying parameter vector autoregression with Lanne–Nyberg decomposition extended joint connectedness approach to analyze quantitatively the spillover effects in the "carbon–energy–financial" system. Empirical results show that a bidirectional spillover effect exists among markets. Not only does the carbon market have the most pronounced return (volatility) linkages with the natural gas (clean energy) market, but the information connected with the energy markets is also more closely linked than with the financial markets. We also find that market fluctuations, caused by the China–US trade conflict and the COVID‐19 pandemic, have increased spillovers in the system. [ABSTRACT FROM AUTHOR]

China has always tried to maintain multilateralism and advocated working together to deal with global climate change through multilateral mechanisms. Although China’s announcement to peak its carbon emissions by 2030 comes as no surprise, its commitment to carbon neutrality does. As the period between its carbon peaking and carbon neutrality is far shorter than that in the developed countries, China’s economic and energy structures need to be adjusted toward the low-carbon and carbon-free end with unprecedented efforts. To that end, China should define the responsibilities of local authorities and industrial entities to promote the orderly accomplishment of carbon peaking in all regions and industries. To supply the huge investments needed to achieve the goals of carbon peaking and carbon neutrality, China has an urgent need to accelerate the development of green finance and a national carbon emissions trading market, guide the rational allocation of resources, and channel resources to eco-friendly projects for green and low-carbon development. At the same time, China and the international community should strengthen dialogue and coordination, promote international cooperation on the way to carbon neutrality, formulate widely acceptable policy guidelines as soon as possible, and avoid unilateral measures that may cause conflicts. [ABSTRACT FROM AUTHOR]

The power sector is one of the major CO2-emitting industries in China. It is also the first key emissions control industry included in China's national carbon trading market established in 2021. Therefore, based on the data of 30 provinces and cities in China from 2015 to 2022, this study analyzes the impact of the national carbon market policy on the carbon emissions of the power industry based on the generalized Difference-in-Difference (DID) model. Based on the method of text analysis, this paper constructs the carbon market policy intensity index of each region and incorporates it into the DID model. Empirical analysis finds that the national carbon market policy can significantly inhibit the carbon emissions of the power industry. However, the heterogeneity analysis of 30 provinces and cities shows that the national carbon market policy has a significant impact on the regions that already have a carbon pilot, but not on the non-pilot regions. Therefore, this paper demonstrates the effectiveness of the national carbon market policy in the power industry emissions control, and also exposes the heterogeneity between regions, providing an important empirical basis for the inclusion of other energy-intensive industries. [ABSTRACT FROM AUTHOR]

In this paper, we select the China Carbon Market Price Index, which reflects the overall price changes in China's carbon market (CCM), and employs the TVP- VAR-BK model to examine the risk spillover effects between the carbon market and high-carbon-emission industries in China from a frequency domain viewpoint. Employing the nonparametric quantile Granger causality test, it delves further into the effects of economic policy uncertainty (EPU) in China on the degree of risk spillovers between the carbon market and high-carbon- emission industries. There are significant risk spillover effects between the carbon market and high-carbon-emission industries. During the short term, the carbon market affects the cement industry more than the electric power and steel industries. However, the carbon market is affected by the volatility of the high-carbon-emission industries over the long term. In addition, the effect of EPU on the magnitude of risk spillovers between the carbon market and high- carbon-emission industries is nonsignificant at extreme quartiles and significant at the middle quartile level, which is typically asymmetric. [ABSTRACT FROM AUTHOR]

The current Chinese electricity market and carbon market are built relatively independently, without coupling and synergy, and the incoherence between the two markets is beginning to emerge. Carbon emissions costs in the carbon trading market will affect the marginal cost of renewable energy and thermal power in the electricity market, limiting market participants' profitability. In order to simulate and evaluate the changes of LCOE of renewable energy and thermal power in the "electricity-carbon" market environment, this paper presents the calculation method of carbon emission cost of thermal power and CCER benefit of renewable energy based on the relevant regulations in China, and calculates the carbon emission cost transmission rate of thermal power based on Cournot model. In addition, we proposed a method for calculating the LCOE based on the international common calculation method for LCOE, combined with China's taxation policy and the cost and benefit factors of renewable energy and thermal power in the carbon market, and proposed a method for calculating the LCOE applicable to the "electricity-carbon" market environment in China. The findings indicate that as a result of the influence of the carbon market, the levelized cost of energy (LCOE) cost of thermal power will increase, and the profitability of thermal power in the electricity market will be further reduced. On the other hand, the LCOE cost of renewable energy will further decrease, and its profitability will improve due to the additional CCER benefits in the carbon market. [ABSTRACT FROM AUTHOR]

Evaluating the effects of China's carbon emission trading scheme (ETS) is crucial for the coordinated development of Chinese cities. Therefore, based on the panel data of 242 cities in China from 2008 to 2019, this paper uses the multi-period difference-in-difference (DID) model to comprehensively evaluate the impact of carbon market on the coordinated development of cities from the perspectives of carbon market policy and carbon market efficiency, and then analyzes the mechanism and heterogeneity of the effect of carbon market efficiency. The results show that both carbon market policy and carbon market efficiency can promote the coordinated development of cities. Science and education expenditure plays a significant intermediary role in the impact of carbon market efficiency on the coordinated development of cities. The heterogeneity test finds that the stricter the performance penalty system, the higher the level of urban coordinated development, and the stronger the effect of carbon market efficiency. The findings of this paper provide policy recommendations for further improving the construction of China's pilot and national ETS and enhancing the coordinated development of Chinese cities. [ABSTRACT FROM AUTHOR]

By decomposing the changes of carbon emissions into effects of economic growth, industrial structural change, technological change and energy structure change, the paper firstly discusses the contribution of each effect to China's carbon emission changes between 2020 and 2030, and forecasts China's total carbon emissions in 2030. In particular, the paper strengthens that a decrease in population and a significant slowdown in urbanization will significantly reduce the construction demand, the main driver for high growth of carbon emissions in China, and provide a relatively favorable economic environment for China to achieve carbon peaking by 2030. The paper then discusses on how to achieve the "dual carbon" goals with the lowest possible economic cost by relying on market and price mechanisms. [ABSTRACT FROM AUTHOR]

Industrial structure low-carbon restructuring is an essential channel to accelerate China's economic growth and fulfilling carbon emission reduction goals. Whether carbon emission trading pilot policy, as an influential carbon reduction instrument, fosters industrial structure low-carbon restructuring is of major significance to green economic development. This paper empirically investigates the shock of the carbon emission trading pilot policy on industrial structure low-carbon restructuring using the differences-in-differences (DID) and synthetic control method (SCM). Statistics reveal that sectors with low carbon productivity, such as electricity, steam, and hot water production and supply, ferrous metal smelting and pressing, etc., and sectors with high carbon productivity, such as electrical equipment and machinery, electronics and telecommunication equipment, etc. The industrial structure did not develop a stable trend of change before the 12th Five-Year Plan, but a stable trend of low-carbon restructuring emerged after such a period. Carbon emission trading pilot policy significantly facilitates industrial structural low-carbon restructuring. Carbon emission trading pilot policy inhibits energy-intensive industries in the industrial sector significantly, which promotes industrial structure low-carbon restructuring. Therefore, policymakers need to develop a nationwide carbon emission trading market that includes more industries to guide production factors to industrial sectors with high carbon productivity for industrial restructuring and dual carbon goals. [ABSTRACT FROM AUTHOR]

With the acceleration of the global response to climate change, increasing attention has been paid to the risks associated with climate change mitigation, such as regulation uncertainties and market interactions. As the country with the greatest CO2 emissions globally, China has launched a national carbon market to speed up its climate mitigation. While the national carbon market provides a platform for regional coalitions to reduce emissions, its incomplete sectoral coverage might allow for the strategic behavior of industries in different regions and ultimately affect the efficiency of the carbon market. This paper explores how the sectoral expansion of the national carbon market affects regional emission reductions in China when emissions trading sectors engage in strategic behavior in the output market. From the sectoral perspective, our numerical results show that the strategic effect in the electricity and steel sectors is more significant than in other sectors. From a regional perspective, the western regions of China, which are mostly permit sale regions, have less strategic power than the eastern regions in the output and carbon markets. Finally, this paper suggests that measures, such as the dynamic adjustment of emission allowance allocation, should be considered by policy makers to prevent the widening of regional economic disparities when extending the sectoral coverage of the carbon market in China. [ABSTRACT FROM AUTHOR]

There has been a financial trend in China's carbon market. However, the legal and policy pathways in China have not specifically focused on carbon finance, which has led to some suspicions about the legitimacy and efficiency of the carbon market. China is following an ambiguous and complicated route in the financial market rules and specialized regime of the carbon market. Meanwhile, the EU has classified carbon emission allowances as financial instruments, and adopted financial market rules for all segments of the carbon market. On the basis of the financial regulation in the EU this paper will try to find an appropriate legal and policy pathway to carbon finance in China. Application and exemptions as regards financial market rules concerning different market participants and their behaviors will be suggested. [ABSTRACT FROM AUTHOR]

China has adopted a gradualism principle in establishing its carbon emission trading system from the regional pilot markets to a national one. In view of the huge market potential and large differences across China, this paper applies the cointegration test and VECM (Vector Error Correction Model) to investigate the long-run trends and the price dynamics of regional pilot markets. The results show that the prices of the regional pilot markets form three long-run trends exhibit mean-reversion patterns. The launch of the national market marks the different performance of regional pilot markets. After the launch of the national market, the number of long-run trends reduces from three to one and the severity of the mean-reversion patterns is eased, indicating the efficiency improvement in China's carbon market from a fragmented toward a unified market. The policy implication is that China should further develop its national market by incorporating the regional markets into the national one and encouraging more market participants for market transaction. [ABSTRACT FROM AUTHOR]

The European carbon emission trading market is the largest and most mature market, while China's carbon market has a short history. Institutionally, cross-market transaction is infeasible between the two markets. This paper investigates the long-run trend between the two markets as well as the price dynamics. Results show that a long-run trend exists between the Chinese and European carbon markets. Both markets possess self-correction capability in reducing price deviations, signaling a certain level of market efficiency. However, both markets also exhibit pricing inefficiency as historical price movements are able to impact prices. The European market informationally leads the Chinese market. Policy implications are that China should further upgrade its information disclosure system, such as unifying information disclosure standards across industries, and further develop its carbon derivatives markets to improve market transparency and market competition. [ABSTRACT FROM AUTHOR]

A reasonable energy structure can secure the orderly development of the economy and effectively control carbon emissions. This paper builds a CGE (Computable General Equilibrium) model that incorporates the carbon market module, uses 2012 as a base period, and uses carbon prices and energy investments as starting points to simulate and assess China's impact on macroeconomics and carbon markets under three scenarios. The results show that a reasonable energy structure has a positive impact on macroeconomics, and macroeconomic indicators under the three scenarios show an increasing trend compared with 2012. The comparison of economic indicators under the different scenarios shows that the expected energy structure of the 12th Five-Year Plan is the most judicious among the three scenarios and can produce greater economic benefits with lower energy investments. The study concluded that carbon market spending as a percentage of GDP is the most appropriate indicator for analyzing the relationship between carbon prices and carbon dioxide emissions. Our analysis of the indicators found that the higher the carbon price, the smaller the carbon dioxide emissions, and the lower the carbon price, the greater the carbon dioxide emissions. This article will help provide a reference for China's future energy structure adjustment. [ABSTRACT FROM AUTHOR]

This paper interrogates the impact of policy events on the efficiency of carbon market in China. The analysis covers five piloting emission trading schemes (Beijing, Shanghai, Guangdong, Shenzhen and Hubei), particularly focusing on Guangdong pilot for its weak form efficiency and the richness of policy events. Twenty-five policy events between 2014 and 2016 are categorized into seven groups. The efficiency test indicates that only Guangdong ETS has reached weak form efficiency. After exploring the policy events occurred in Guangdong ETS, it finds that although a clear long-term climate policy has been set up over the country, China's carbon market still has a conservative risk appetite and its governing institutions still needs further development. The policy makers need to be aware of and avoid the negative impacts of policy events to the market evolvement, by introducing effective consultancy process with the stakeholders and nurturing market expectations in the long run. We also find that events like allowance auctions have considerably less impacts than previously expected and argue that auction approach should be considered a preferable option over a free allocation system in the future policy design. [ABSTRACT FROM AUTHOR]

The carbon market has been playing an increasingly important role in mitigating carbon emissions. However, with the tightening of the carbon allowance, where the carbon market will evolve is still unclear. Abstracting three agents—Government, Carbon-supplier('CS'), Carbon-buyer('CB'), this paper intends to investigate the operation mechanism of carbon market from the perspective of the stakeholders. Based on the simulation analysis, it is suggested that: 1) the carbon market in China may become a major "seller's market" when carbon quota experienced dramatic reduction; 2) when the carbon price is constant, CS with excessive carbon productivity will crowd out and exploit CB in the carbon market competition; 3) strict administrative penalties and information disclosure would help promote proactive participation of CS and CB in the carbon market; and 4) the interaction between CS and CB in different strategic scenarios is influenced by the carbon price and the coefficient of demand variation for carbon quota. In contrast with previous studies, this paper has uncovered a dynamic strategic evolution mechanisms of stakeholders in the carbon market at the micro-level, contributing to carbon market governance and providing stakeholders with tailor-made climate policy tools and strategic choices. • The carbon market in China may evolve into a "seller's market" with a scarcer allowance. • We first identify the phenomenon of carbon exploitation in the carbon market. • Improving the carbon price under buyer's market would facilitate positive participation of three agents. • Carbon accounting, carbon disclosure, and strict administrative penalty help regulate non-compliance actions by enterprises. • The equilibrium of agents' strategy are influenced by dual aspects—parameters and other stakeholders' choices. [ABSTRACT FROM AUTHOR]

Carbon emissions trading is being used by more and more countries or regions to solve the global warming problem. The establishment of China’s carbon market mechanism is still under exploration and improvement. This paper focuses on the price determination mechanism in the carbon market. Based on the price theories, we analyze the theoretical basis of the carbon price formation and the carbon price transmission mechanism from the perspective of the agents that affect carbon price. From these angles including residents’ demands, enterprises’ actual emissions and indirect effects on residents’ demands, the government’s setting for carbon market institutions and indirect effects on residents and enterprises, as well as energy markets and financial markets, we analyze how these factors influence the carbon price. In turn, we discuss how carbon price affects the enterprise costs, energy-saving technologies and residents’ welfare. Besides, we summarize the current price mechanism of domestic and overseas major carbon markets. Finally, based on the current research on carbon price theory and its influencing factors, we also present some further directions on carbon price mechanism and influencing factors including China’s carbon market price mechanism design, the quantitative analysis of carbon price factors and improvement of carbon price theory. [ABSTRACT FROM AUTHOR]

With the development and refinement of the carbon emissions trading market, the relationship between the carbon market and the stock market has grown increasingly intertwined. This has led to a surge in research investigating the interactions between the carbon market and related sectors. This study examines the intensity and direction of spillover effects among ten industries associated with carbon emissions, spanning traditional and emerging energy sectors. Through static analysis, we find that spillover effects between industries in the carbon and stock markets are bidirectional and asymmetric. Dynamic analysis reveals that the carbon market, acting as the primary recipient of spillover effects, is notably influenced by traditional energy industries such as coal and oil, followed by photovoltaics, new energy vehicles, and others. The magnitude of these spillover effects is subject to fluctuations influenced by energy crises and events like the COVID-19 pandemic, while policy interventions can alter the overall trends in net spillover effects across various industries. [ABSTRACT FROM AUTHOR]

Equilibrium capacity expansion is an effective tool to help regulators predict the generation evolution of power systems by analyzing the decision-making of generation companies (Gencos). With the development of carbon markets (CMs) and electricity markets (EMs), Gencos' decisions in these two markets (encompassing investment and bidding decisions related to carbon emission allowances and electricity) are deeply intertwined through market clearing results. However, existing studies mainly focus on equilibrium capacity expansion with fixed carbon prices and usually ignore the realistic clearing process of CMs, which cannot simulate Gencos' coupled decision-making and accurately predict generation evolution under the CMs and EMs. This paper proposes a two-level equilibrium capacity expansion model for power systems which considers the coupled decisions of Gencos between CMs and EMs. At the upper level, multiple Gencos' coupled decision models are proposed based on their interaction with market clearing results. At the lower levels, CMs and EMs are respectively cleared to determine the varying carbon and electricity prices. Furthermore, the developed equilibrium capacity expansion model is reformulated as an equilibrium problem with equilibrium constraints (EPEC), which is solved by a diagonalization-based solution procedure. Finally, a provincial power system of southeast China is used to validate the performance of the proposed framework. The results illustrate that under CMs and EMs, non-fossil energy would account for 81.3% of total capacity and 73.88% of total generation in 2050. Compared to the existing model using fixed carbon prices, the consideration of realistic carbon market clearing will promote the installation of renewable energies and improve social welfare. The proposed model can provide beneficial references for regulators to perceive the evolution of power systems in CMs and EMs. • A two-level equilibrium capacity expansion model for power systems is proposed. • A novel coupled decision model for Gencos in CMs and EMs is developed. • The proposed model is solved by a diagonalization based solution procedure. • The results can guide the transition of power systems under the CMs and EMs. [ABSTRACT FROM AUTHOR]

Carbon market is the most effective market tool for carbon emission reduction. China, the largest carbon emitter in the world, established the national carbon market in 2021, covering over 2000 key units in the power sector. Therefore, the forecasting of carbon price has profound implications for environmental and energy policies. In this paper, two traditional econometric model and three kinds of machine learning (ML) algorithms are used to predict carbon returns in the Chinese carbon trading market based on carefully selected predictors. Among all forecasting models, the Random Forest (RF) has the best forecasting performance, followed by some GARCH models using various factors. Compared with the traditional benchmark of ARMA model, the BP neural network (BP) and the GA improved BP method (GA-BP) are less competitive in predicting carbon returns in China because of their large forecasting errors. According to the optimal model, social attention to the carbon market, the international crude oil returns and the overall performance of the stock market are the most important predictors. The findings are robust to the change in the sample set. Overall, the ML approach shows an advantage in forecasting carbon returns, but the selection of predictors is also important. • Machine learning and econometric models are used to forecast carbon returns in China. • The selection of predictors is based on economic analysis. • The Random Forest (RF) outperforms the other ML and econometric methods. • The energy market is extremely important for predicting carbon returns. • Social concerns and stock market performance improve forecasting accuracy. [ABSTRACT FROM AUTHOR]

The China Certified Emission Reduction scheme (CCER) and the Cap-and-Trade (CaT) mechanisms jointly constitute the Emission Trading Scheme (ETS), which is expected to have a profound impact on China's social and economic decarbonization. However, previous studies have primarily focused on the impact of the CaT mechanism, neglecting the fact that CCERs serve as a carbon offset trading mechanism. This paper focuses on the impact of the CCER mechanism on China's energy economy and environment by constructing a recursive dynamic computable general equilibrium model that couples CaT and CCER mechanisms. Introducing the CCER mechanism based on the CAT mechanism leads to increased output and reduced prices in renewable energy sectors, cascading positive effects across various energy-utilizing sectors to counter the decline in Gross Domestic Product (GDP) and residential welfare. The finding suggests that China's unique CCER mechanism is poised to play a more important role in promoting renewable energy to mitigate global warming, given its potential to transform the structure of energy production and consumption. Finally, targeted policy recommendations are proposed for implementing the CCER mechanism. [ABSTRACT FROM AUTHOR]

Accurately predicting carbon trading prices using deep learning models can help enterprises understand the operational mechanisms and regulations of the carbon market. This is crucial for expanding the industries covered by the carbon market and ensuring its stable and healthy development. To ensure the accuracy and reliability of the predictions in practical applications, it is important to evaluate the model's robustness. In this paper, we built models with different parameters to predict carbon trading prices, and proposed models with high accuracy and robustness. The accuracy of the models was assessed using traditional survey indicators. The robustness of the CNN-LSTM model was compared to that of the LSTM model using Z-scores. The CNN-LSTM model with the best prediction performance was compared to a single LSTM model, resulting in a 9% reduction in MSE and a 0.0133 shortening of the Z-score range. Furthermore, the CNN-LSTM model achieved a level of accuracy comparable to other popular models such as CEEMDAN, Boosting, and GRU. It also demonstrated a training speed improvement of at least 40% compared to the aforementioned methods. These results suggest that the CNN-LSTM enhances model resilience. Moreover, the practicality of using Z-score to evaluate model robustness is confirmed. • Deep learning by combined CNN-LSTM networks for carbon price forecasting. • Hyperparameter tuning of deep learning models for improving forecast accuracy. • CNN-LSTM models outperform single CNN models and single LSTM models. • Performance metric of deep learning for abrupt changes in carbon price variation. [ABSTRACT FROM AUTHOR]

Using the available information and a standard econometric approach analyzing the time series dataset, this study identifies the interactions between electricity, fossil fuel and carbon market prices in Guangdong, China. The result confirms a long running co-integration between carbon market prices and the prices of coal, diesel and liquid natural gas (LNG). Conversely, fossil fuel prices have no impact on the short term dynamics of carbon prices. The price of electricity on the monthly forward market in Guangdong is significantly and positively associated with the first difference of the price of coal, but has no significant relationship with the first differences of carbon, diesel and LNG prices. This analysis provides certain implications for ongoing power sector reform and nationwide carbon market development in China. The liberalization of the power industry should be further advanced to create conditions for carbon cost pass-through on to the electricity market. Meanwhile, the national emissions trading scheme (ETS) should apply simpler and stricter benchmarks to allocate emissions allowances for the power sector. Fewer categories of benchmarks promote competition among different types of power generators and a shift to an electricity supply portfolio with lower carbon intensity. Stricter benchmarks create more demand for emissions allowances and result in higher carbon market prices. To increase the ratio of emissions allowances by auctioning is also necessary to put substantial pressure on thermal power plants to pass their carbon costs on to end users. • This paper identifies the interactions between electricity, fossil fuel and carbon market prices. • A standard econometric approach is used to analyze the time series data in Guangdong, China. • The result confirms a long run co-integration between the prices of carbon and fossil fuels. • Carbon price change is not a significant factor to electricity prices of the monthly forward market. • This study gives insights to China's power sector reform and national carbon market development. [ABSTRACT FROM AUTHOR]

Carbon trading and new energy markets are two key mechanisms for carbon reduction. However, theoretical analysis cannot reveal the complex links between carbon, green, and grey markets. Therefore, this study resorts to the frequency spillover index to explore the overall and directional connectedness of carbon-energy systems in China. The spillover effect indicates the cross-market propagation of information shocks and the potential ripple effects of specific shocks on system-wide changes. Dynamic spillovers suggest that the role of a certain market is not unchanged. In the time domain, both the overall and directional spillovers are closely related with the trading of carbon allowances and tend to show jumps at the beginning and end of the cycle. In the frequency domain, the short-term effects are much stronger than the medium- and long-term effects on all dimensions of the spillover effect. Comparatively, the grey energy is the main information transmitter at the high frequency, whereas it is the green energy playing such a role at medium and low frequencies. Comparing the overall spillovers on carbon markets, the effect of grey energy exceeds that of green energy. Even so, the carbon market plays an important role in the carbon-energy system with extremely significant effects on green and grey energy stocks at certain periods. The results provide profound implications for the management of carbon markets and portfolio optimization. [ABSTRACT FROM AUTHOR]

The emissions trading scheme (ETS) has piqued substantial interest among economists and policymakers. China officially launched the electricity sector's national carbon emissions trading market in 2021, making it the world's largest compliance carbon market. In contrast to the cap-and-trade (C&T) system prevalent in other economies, China's national carbon market employs a rate-based mechanism that implicitly subsidizes the output of regulated entities; however, is it effective? This study uses a market-design theoretical framework to explore whether China's national carbon market functions effectively and, more critically, what leads to its (slight) underperformance. We discover that policy design, policy conflicts, policy uncertainty, inexperienced market regulation, and excessive or inappropriate government intervention are the primary constraints on this emerging market, resulting in shrinking market thickness, congested market transactions, and lack of safety. For China to establish a better national carbon market, stronger market-oriented rules, appropriate market regulation, improved policy coordination, and greater electricity market reforms are required. [ABSTRACT FROM AUTHOR]

Highlights • Design a framework for modeling carbon emissions in China's power sector. • Employ a methodology that combines top-down, bottom-up and the integration of both. • Showcase on how to combine quotas design, quotas allocation, and abatement estimate. Abstract China has started its design of national emissions trading system (ETS), and power sector is included in its initial stage. In this paper, we propose a systematic framework to estimate total carbon emission quota required to meet the national GDP energy intensity target, and allocate the emission quota. The theoretical framework consists of three basic approaches - "top-down", "bottom-up" and "the integration" approaches, and assumes key parameters such as CO 2 emission intensity target, contribution of emission abatement from ETS, coverage range of ETS, and industry emissions standards. Based on actual data from 2011, we forecast development of China's thermal power industry into 2020 under different official planning scenarios. With the approaches proposed, we show on to adjust the emissions benchmarking at technology level for reaching expected contribution of emissions abatement from ETS. The proposed methodology is informative to ETS market regulators and power utilities. [ABSTRACT FROM AUTHOR]

Highlights • We provide an analysis of the local policy innovations for constructing pilot emission trading schemes in China. • We argue that these experimental measures played an important role to establish effective trading facilities and regulatory frameworks. • We investigate the role of these local policy innovations to meet the challenges of applying market instrument in China's unique political, economic, and industrial contexts. • We discussed how these local policy innovations can be learned for the construction of nationwide carbon market. Abstract Harnessing market instruments of climate governance, such as emission trading schemes (ETS) into an authoritarian and highly fragmented governance system like China can be challenging. It requires tremendous efforts from local states for policy experiments and innovations. This paper examines these local adaptive measures to develop pilot ETS around China. The key finding is that these local policy innovations have played an important role to kick off carbon trading activities effectively, by addressing a number of challenges such as highly imbalanced economic and political contexts, very limited emissions data and technological capacity, and low participants' awareness of ETS. The implications of such policy innovations to the construction of a nationwide ETS system are also discussed. Some of local policy innovations can be legitimised and adopted into the design of national carbon market, while others are more likely appreciated only at initial stage of market development at local level. [ABSTRACT FROM AUTHOR]

This paper integrates China's energy market, carbon emission trading market, and stock market of energy-intensive sectors into one framework based on a system perspective. We quantify the return and volatility spillover effects respectively, and deeply examine the structures and driving factors of these two spillovers. Our findings demonstrate that (i) the spillover linkage in the "Energy – Carbon – Stock" system is considerable, particularly the return spillover connectedness; (ii) the stock market occupies a dominant position in the system and primarily serves as a net transmitter in the spillover structure; (iii) policy adjustment and energy market turbulence are the main driving events for the sharp rise of the overall spillover; (iv) there exists an obvious cluster effect in the spillover network structure, and the occurrence of major events will make the most affected assets move to the network center and become the main spillover sources; (v) the state of the energy market, the stock market stability and the monetary policy orientation all have a strong explanatory power for the overall spillover. Our research provides useful implications for policy makers, energy-intensive industries and green investors. • Exploring the information and risk transmission mechanisms in China's "Energy – Carbon – Stock" system. • Time-varying characteristics of the overall spillovers and their relevance to major events are discussed. • We deeply study the structures of the spillover effects. • We examine the impact of macroeconomic factors on different kinds of spillovers. [ABSTRACT FROM AUTHOR]

A carbon market is a widely used policy tool worldwide. This study employs a difference-in-differences (DID) model to estimate the impact of a carbon trading policy on green technology innovation and applies a spatial DID (SDID) model to investigate its spatial spillover effects. The findings suggest that China's carbon market effectively promotes green technology innovation, as green invention patent applications for listed enterprises increase by 28.8% when implementing the carbon trading policy. Moreover, implementing a carbon trading policy promotes local green technology innovation and has spatial spillover effects on neighboring cities. Furthermore, heterogeneity test results show that the spatial spillover effects differ by geographical region, economic development levels, ownership type (state-owned and non-state-owned enterprises), and degree of government intervention. Therefore, we suggest enhancing enterprises' technological innovation by providing policy support and prioritizing the development of carbon markets in regions with high economic development levels. [ABSTRACT FROM AUTHOR]

In recent years, with the intensification of global warming and the greenhouse effect, the global consensus has focused on efficient, clean, low-carbon, and green development as a means of achieving new economic growth. China, as a major carbon emitter, has been at the forefront of efforts to reduce carbon emissions. The establishment of the carbon emissions trading market, commonly known as the "carbon market", provides an economic solution for reducing carbon emissions in both the carbon and energy markets. As China's carbon market continues to grow rapidly, fluctuations in the energy or carbon markets caused by information shocks can easily spread between the two markets, leading to increased interconnectedness. Moreover, the spillover effect of the volatility between China's carbon market and energy market is not constant, and the intensity and direction of this effect vary depending on different market volatility levels and periods. Therefore, it is crucial to conduct a comprehensive study on the characteristics of the volatility spillover effect between China's carbon market and energy market and to fully understand the mechanism of energy regulation on carbon prices. This research will have significant practical implications for promoting the establishment of a well-functioning internal price transmission mechanism between China's carbon market and energy market. This study took the risk spillover between the carbon market and energy market as the research object and systematically combed through its pricing mechanism and spillover impact. Through constructing the DY overflow index model based on a VAR model and generalized variance decomposition method, this study explored the linkage between China's carbon and energy markets, i.e., the linkage of price fluctuations between China's energy and carbon markets, as well as the time-varying nature of inter-market spillovers, and provides suggestions on the risk control of price fluctuations between the carbon and energy markets. [ABSTRACT FROM AUTHOR]

This paper estimates the potential influence of China's future nationwide carbon market on clean technology innovation. To overcome data limitation issues, the energy price is adopted as a proxy for the carbon price to estimate its impact on clean innovation and R&D. Then, a counter-factual method is introduced in which the potential carbon price is mapped onto the equivalent percentage change of energy price by sector. According to our results, the carbon market shows both a redirection and a crowding-out effect on technology innovation, with the former overwhelming the latter. If the future nationwide carbon market yields a carbon price of 50 Yuan, our findings estimate that it would result in an increase in the quantity and proportion of clean invention patents in ETS-covered sectors of 2.2% and 3%, respectively, and in an increase in the quantity and proportion of clean utility patents of 3.6% and 1.4% respectively. However, the effect on overall R&D is negative, indicating that carbon costs might crowd out some R&D expenditures, but in a limited manner. Generally, the carbon market in China is expected to help redirect technology innovation onto a cleaner path. [ABSTRACT FROM AUTHOR]

• Regional ecological benefits of developing forest carbon sequestration projects in carbon markets are empirically investigated. • The pilot policy of China's one regional offset mechanism (Guangdong PHCER) is used as a quasi-natural experiment. • The carbon market can effectively increase city greening by encouraging the development of forest carbon sequestration projects. • This effect does not crowd out arable resources.Thank you very much. This paper investigates the regional spillover effects of the project-based voluntary market under the carbon emissions trading scheme (ETS). By exploiting one local offset mechanism (China's PHCER) as a quasi-experiment, we detect the unintended causal effect of the carbon market on greening the city. Using the difference-in-differences (DiD) estimator, we find that the voluntary carbon market resulted in a 14.45% (14.34%) increase in city-year-level NDVI summary value (per capita). The primary mechanism is the expansion of forest carbon sequestration projects. Cities with lower carbon emissions and fewer carbon market participants experience a greater causal effect. More importantly, we find no evidence to support the crowding out of arable land by forest carbon sequestration projects. Finally, several policy implications for a more functional carbon market are discussed. [Display omitted] [ABSTRACT FROM AUTHOR]

As a crucial tool to conserve energy utilization and reduce greenhouse gas (GHG) emissions, carbon market has drawn close attention from political circles and academia. A mature carbon market makes the market run orderly and achieve the goal of reducing emissions effectively. It is meaningful to assess the maturity of carbon market. This paper aims at identifying the comprehensive criteria for evaluating the maturity degree of carbon market and proposing a feasible method to evaluate the maturity level of the European Union Emission Trading Scheme (EU ETS) and carbon markets in China. Firstly, this paper proposes 23 specific criteria based on triple bottom line (environmental, economic, and social aspects) to assess the maturity of carbon market. Secondly, we put forward a novel multi-criteria decision approach, which integrates subjective weights and objective weights. Rough set theory is introduced into this method to deal with subjectivity and vagueness problems. Lastly, a case study is applied to assess the maturity level of the EU ETS and carbon markets in China. The results indicate that the EU ETS is currently the most mature carbon trading market. Comparing with the EU ETS, the maturity degrees of carbon markets in China are lower overall. Chinese carbon markets could be divided into three levels according to maturity: Hubei and Guangdong rank the first level; Shenzhen, Beijing and Shanghai rank the second level; Tianjin and Chongqing are at the lowest level. • Comprehensive criteria are identified to assess carbon market maturity. • A weighting method considering subjective weights and objective weights of criteria is developed. • Rough TOPSIS is integrated to manipulate the subjectivity and vagueness of evaluation. • Comparisons are conducted between the carbon market maturity of EU and China. [ABSTRACT FROM AUTHOR]

To offer a scientific basis and reference for policy makers when developing the regulation framework for Chinese national carbon market, this research analyzes the environmental and economic effects of the carbon market from a mid- to long-term perspective in China. Through a computable general equilibrium model, with technological progress as an endogenous variable, this study provides a comprehensive investigation on the relationships between the price of carbon, technological development, emission reduction and economic growth in low, mid- and high emission reduction scenarios. Furthermore, it analyzes the potential of price-setting mitigation measures to create incentives for technological progress. The results indicate that the carbon market will have a positive impact on the R&D investment in China and in turn would promote technology development. Consequently, it is vital that the carbon price is high enough; otherwise, the pressure on technological development will not be sufficiently strong; there is compatibility between carbon intensity reduction and mid- and long-term GDP growth, but it seems impossible to realize the positive effects on both emission reduction and economy development at the early stage. Hence, the carbon market alone will not be a cost-effective instrument for emission abatement and other auxiliary policies will also be needed in the early stages. Meanwhile, selection of reasonable emission reduction scenarios will play a crucial role in achieving the pre-2020 and post-2020 carbon reduction commitments efficiently in China. [ABSTRACT FROM AUTHOR]

• The influencing factors of carbon prices in China's carbon market are analysed. • The influencing factors and historical data are combined to predict the carbon price. • The EEMD-BP-ELM model and the CHINAGEM-E model are constructed and combined. Carbon price is one of the core indicators of the carbon market. Making accurate predictions of carbon prices based on insight into the volatility characteristics of the carbon market will not only provide a scientific basis for investors and regulators to make decisions and greatly promote emission reduction, but also effectively promote the healthy development of the carbon financial market. Based on the historical carbon price data of the national carbon market, this paper constructs the EEMD-BP-ELM model to predict the high and low frequency components of China's future carbon price. On this basis, according to China's goal of peaking carbon emissions before 2030 and achieving carbon neutrality before 2060, the CHINAGEM-E model is used to predict the trend component of the carbon price under the baseline and the 2060 carbon neutral scenarios. Finally, the trend component is combined with the high and low frequency components to obtain the price range from 2022 to 2060. We find that under the baseline scenario, China's carbon price range in 2060 is [343, 785] CNY/tCO2, while under the 2060 carbon neutral scenario, this price range is [1543, 3531] CNY/tCO2. [ABSTRACT FROM AUTHOR]

Carbon emissions trading is a major innovation in the practice of using market mechanism to control and reduce greenhouse gas (GHG) emissions and promote green and low-carbon development. It is an important way to achieve China's carbon peaking and carbon neutrality goals (the "dual carbon" goals) at a relatively low cost. Starting late and having gone through three development stages, China's national carbon market has entered a new stage. However, given the problems such as incomplete institutional, regulatory and carbon emissions verification systems, less balanced and vibrant market, limited transaction entities and trading products, and lack of voice due to insufficient participation in relevant international affairs, continuous efforts are still required to further improve this market by deepening reform, strengthening capacity building and increasing international cooperation. [ABSTRACT FROM AUTHOR]

The scientific judgement of the structural abrupt transition characteristics of the carbon market price is an important means to comprehensively analyze its fluctuation law and effectively prevent carbon market risks. However, the existing methods for identifying structural changes of the carbon market based on carbon price data mostly regard the carbon price series as a deterministic time series and pay less attention to the uncertainty implied by the carbon price series. We propose a framework for identifying abrupt transitions in the carbon market from the perspective of a complex network by considering the influence of random factors on the carbon price series, expressing the carbon price series as a sequence of probability density functions, using the distribution of probability density to reveal the uncertainty information implied by carbon price series and constructing a recurrence network of carbon price probability density. Based on the community structure, the break index and statistical test method are defined. The simulation verifies the effectiveness and superiority of the method compared with traditional methods. An empirical analysis uses the carbon price data of the European Union carbon market and seven pilot carbon markets in China. The results show many abrupt transitions in the carbon price series of the two markets, whose occurrence period is closely related to major events. [ABSTRACT FROM AUTHOR]

Carbon market, which is capable of scientific quantifying and marked-based pricing of carbon emission, is an important way for countries to achieve the target of carbon emission reduction. The global carbon market, after more than ten years of development, has developed a mature mechanism. China started the trial of carbon market in 2011. After ten years of exploration, the national carbon trading market was officially launched in mid-July 2021. Against the backdrop of carbon neutrality, the national carbon market will shoulder a greater mission of carbon emission reduction and speed up its financialization and internationalization. However, it should take a dialectical attitude toward the opportunities and risks of carbon market financialization. In the future, China can promote the development of carbon market through efforts to develop market participants, clarify the attributes of carbon finance, prevent potential risks of carbon finance, improve the connection mechanism with the international carbon market, and innovate carbon finance services. [ABSTRACT FROM AUTHOR]

To investigate the impacts of regulatory announcements on China's pilot carbon markets, as well as test the semi-strong form of market efficiency, a multivariate regression model with GARCH effects combined with multiple bilaterally modified dummy variables is established which allows us to investigate the potential overlapping influence from two timely adjacent events. The Shanghai, Guangdong and Hubei pilot carbon markets are taken as case studies. Based on the ADF test and the runs test, the results show that the China's pilot carbon markets have achieved the weak form of efficiency but not the semi-strong form of efficiency. With the regression model the results show that the release of the allowance allocation plan will affect the carbon price trend, and the allowance auction can only play an auxiliary role as its impact on the carbon price is not decisive. In addition, ubiquitous ex-ante impact proves that the information leakage exists in each pilot carbon market. The model established in this paper is suitable for analyzing the impacts of overlapping events in different markets, which can effectively assist decision makers to distinguish the effects caused by overlapping events. [ABSTRACT FROM AUTHOR]

China is the world's largest developing country and a carbon dioxide emitter. A functional carbon market can effectively reduce carbon emissions. This paper uses the Markov chain Monte Carlo-stochastic volatility model and the wavelet multi-resolution model to analyze the volatility of price returns and the dynamic characteristics of price fluctuations in the carbon pilot markets in Hubei, Shanghai, and Shenzhen. The price movements in these markets are compared to the emissions trading system of the European Union (EU-ETS). The results show that there is a volatility clustering in the price of carbon trading in Hubei, Shanghai, Shenzhen and the EU-ETS. China's carbon pilot markets have a deficiency in terms of volatility stability, as does the EU-ETS. From a long-term perspective, China's carbon market lacks a detailed development plan, which is vital because the construction of the market system is not yet optimal. From a short-term view, China's carbon market is not active and the participants' attitude toward risk is extremely sensitive. • MCMC-SV and wavelet multi-resolution model applied to carbon price volatility. • Three major Chinese markets are compared to the EU-ETS. • All markets evidence volatility clustering. • China's carbon market lacks a detailed development plan for the long term. • Short-term, China's carbon market must become more active and offer more products. [ABSTRACT FROM AUTHOR]

As an economic means to cope with climate change, carbon trading has become an important measure to reduce carbon emissions in China. It has been over seven years since the initiation of seven pilot carbon markets, but has the implementation achieved the goal of controlling carbon emissions in the region? Are the effects really resulted from the carbon market other than other energy-saving and emission reduction policies? Based on the provincial panel data of China from 2005 to 2016 this paper conducts an empirical study on the emission reduction effects of pilot projects using the Difference-in-differences model (DID). The results show that: (1) The implementation of carbon markets in Beijing, Shanghai and Hubei exhibited a significant inhibitory effect on local carbon emissions, but a promoting effect in Guangdong, and no significant effect was found in Tianjin; (2) In terms of time lag effect, no significant inhibiting effect on the local carbon emissions is found during the first year of opening of Shanghai carbon market but the effect grew significantly from 2015 to 2016; while for Hubei and Beijing, significant effect was shown from the first year of running. Being an experimental program to see whether the carbon trading policy would work in China or not and if it does, under what conditions and settings the policy becomes effective, the 7 pilot markets provide important experiences and lessons to the upcoming nationwide market in China. Based on the empirical result that the carbon trading system in Beijing, Shanghai and Hubei effectively reduced carbon emissions, it is suggested that the national carbon market should actively learn from the experiences of these three pilot markets particularly. [ABSTRACT FROM AUTHOR]

China's carbon market has become increasingly active in recent years, and thus it is of great significance to study the characteristics of the carbon allowance price fluctuation for the healthy and steady development of this market. As leverage is common in asset prices in general financial markets, this paper adopts the leverage stochastic volatility (SV-L) model to characterize the price volatility of the five pilot carbon markets in China. We first make a Bayesian inference for the SV model, then construct a Monte Carlo calculation process based on Gibbs sampling for empirical analysis, and finally compare the SV-L model with the normal stochastic volatility (SV–N) model. The results show that the carbon price fluctuations of the five pilot markets are quite different. Among them, Shenzhen, Guangdong, Shanghai, and Beijing have a "positive leverage effect", and Hubei has an "anti-leverage effect". Through comparative analysis, we find that the SV-L model is superior to the SV-N model in terms of the degree of data fitting and simulation ability. Finally, we offer suggestions on the development of China's unified carbon market. • We explore the characteristics of carbon price fluctuation in different pilot markets in China. • The SV-L model indicates that the carbon price fluctuation of each pilot province or city shows great difference. • Five pilot carbon markets show different degree of leverage effect. • The SV-L model is superior to the SV-N model for characterizing the carbon price of pilot markets in China. [ABSTRACT FROM AUTHOR]

China is attempting to initiate its own carbon market—an important market-based policy instrument which would determine the fate of global climate policy as the largest emitter of carbon dioxide across the world. This article looks at carbon trading development so far and examines the key challenges ahead in China. These past experiences—whatever from international CDM practice, or SO2emission trading and a domestic voluntary carbon market—have paved the solid way to build the existing ETS pilots similar to European Union Emissions Trading System (EU ETS). The investigation into China’s ETS pilots discovered some important and urgent issues such as the capsetting and deepening energy market reform. [ABSTRACT FROM AUTHOR]