Carbon Emission Trading Market Research Articles

Impact of carbon emission trading system on green technology innovation of energy enterprises in China

China proposed establishing a carbon emission trading market in its 12th Five-Year Plan to reduce carbon dioxide emissions through market mechanisms, promote the development of science and technology and help China become an environment-friendly country. To examine the impact of carbon emission trading on green technology innovation in Chinese energy enterprises, data from 1993 to 2020 were collected from 494 A-share-listed energy enterprises. Enterprises located in the pilot area of carbon emissions trading were assigned to the treatment group, while those in the non-pilot area were assigned to the control group. The propensity-score-matching method was utilized to match the treatment group with the control group, and the resulting samples were used as the actual sample data. The difference-in-differences method was then employed to assess the net impact of carbon emission trading and investigate its effect on green technology innovation in energy enterprises. This empirical study suggested that carbon emission trading has a positive impact on green technology innovation in energy enterprises, particularly state-owned ones. Larger enterprises are more willing to engage in green technological innovation than small enterprises. Furthermore, when faced with a carbon emission trading system, ‘mature’ companies tend to pay more attention to green technology innovation than younger enterprises do. This study puts forward policy measures for establishing a national-level carbon emission market in China in the future.

Governance effects of pollution reduction and carbon mitigation of carbon emission trading policy in China

China's carbon emission trading policy plays a crucial role in achieving both its “3060” dual carbon objectives and the United Nations Sustainable Development Goal 13 (SDG 13) on climate action. The policy's effectiveness in reducing pollution and mitigating carbon emissions holds significant importance. This paper investigated whether China's carbon emission trading policy affects pollution reduction (PM2.5 and SO2) and carbon mitigation (CO2) in pilot regions, using panel data from 30 provinces and municipalities in China from 2005 to 2019 and employing a multi-period difference-in-differences (DID) model. Furthermore, it analyzed the heterogeneity of carbon market mechanisms and regional variations. Finally, it examined the governance pathways for pollution reduction and carbon mitigation from a holistic perspective. The results indicate that: (1) China's carbon emission trading policy has reduced CO2 emissions by 18% and SO2 emissions by 36% in pilot areas, with an immediate impact on the “carbon mitigation” effect, while the “pollution reduction” effect exhibits a time lag. (2) Higher carbon trading prices lead to stronger “carbon mitigation” effect, and larger carbon market scales are associated with greater “pollution reduction” effects on PM2.5. Governance effects on pollution reduction and carbon mitigation vary among pilot regions: Carbon markets of Beijing, Chongqing, Shanghai, and Tianjin show significant governance effects in both “pollution reduction” and “carbon mitigation”, whereas Guangdong's carbon market exhibits only a “pollution reduction” effect, and Hubei's carbon market demonstrates only a “carbon mitigation” effect. (3) Currently, China's carbon emission trading policy achieves pollution reduction and carbon mitigation through “process management” and “end-of-pipe treatment”. This study could provide empirical insights and policy implications for pollution reduction and carbon mitigation, as well as for the development of China's carbon emission trading market.

Research on the Impact of Carbon Emission Trading Market on Regional Economic Development: A Case Study of East China

This article delves into the impact of carbon emission trading mechanism on regional economy, especially in East China, and focuses on analyzing how this mechanism promotes green transformation and high-quality development of the economy by influencing green technology innovation of enterprises. Research has found that carbon emission trading not only incentivizes companies to reduce greenhouse gas emissions, but also guides capital and technological innovation to flow towards low-carbon areas through market mechanisms, thereby promoting the optimization of industrial structure and sustainable economic development. This article also discusses the impact of different quota allocation methods on green innovation in enterprises, pointing out that the benchmark method can more effectively stimulate the innovation drive of enterprises compared to the historical method. Therefore, according to the research findings, it is necessary to improve the construction of carbon markets, scientifically formulate quota allocation systems, avoid negative impacts on early green innovation enterprises, and provide policy support to reduce innovation costs for enterprises.

Effect Analysis of China's Carbon Emission Trading Pilot Policy on Carbon Emission Control

Many countries have achieved a fundamental consensus to decrease carbon dioxide emissions in order to address environmental and climate issues. China, as the foremost energy consumer and carbon emitter globally, has significantly contributed to the exacerbation of greenhouse gas issues. The most effective method for lowering carbon emissions is through the trade of carbon emissions. In 2011, China began the process of implementing pilot projects for pricing carbon emissions as a means of addressing environmental and climate-related issues. This study use the literature review approach to examine the current state of China's carbon emission trading pilot policies on carbon emission management. It also analyzes the technical and economic impacts of these pilot policies in comparison to non-pilot carbon emission trading policies. The objective of this study is to propose recommendations for the implementation of the national carbon emission trading market in 2021.

Can carbon emission trading improve regional eco-efficiency? Based on the environmental innovation perspective.

This paper uses green innovation and environmental pollution as the mediating variables to construct a mediating effect model to investigate whether China's carbon emission trading policy can improve regional eco-efficiency by reducing regional environmental pollution and stimulating green innovation. This study is based on panel data from 30 provinces and municipalities directly under China's central government and autonomous regions from 2003 to 2019. The eco-efficiency of these provinces is measured using the super-efficiency DEA model and the difference-in-difference method (DID). The results show that (1) China's emission trading policy significantly improves regional ecological efficiency and the per capita GDP. The improvement can effectively improve regional ecological efficiency. (2) The mediating effect of green innovation and environmental pollution is significant. That is, China's carbon emission trading policy further improves regional ecological efficiency by stimulating more green innovation and reducing the synergy brought by environmental pollution. (3) There are differences in the feedback of this impact mechanism between different regions: It shows the characteristics of the western region being more significant than the eastern region. The central region has no significant effect. The research conclusion can provide a policy reference for the subsequent unified promotion of the construction of a carbon emission trading market nationwide and a theoretical basis for helping to achieve the "dual carbon" goal.

Research on the spatial spillover effect of carbon trading market development on regional emission reduction

This paper introduces the current situation of carbon trading market in China and the effect of carbon emission reduction in each region. Theoretically, it expounds the influence mechanism and spatial spillover way of carbon trading market on regional carbon emission. Next, we use the data of 30 provinces in China from 2006 to 2019 to build a continuous spatial difference in difference model (SDM-DID) to empirically study the spatial spillover effect of carbon trading market on regional emission reduction. The results are as follows: First, the implementation of the pilot policy of carbon emission trading has significantly promoted the carbon emission reduction in the pilot areas. From the perspective of impact mechanism, the implementation of carbon trading pilot policy promotes carbon emission reduction in pilot areas by promoting clean transformation of energy consumption structure, improving technology absorption capacity and stimulating development of low-carbon technologies. From the perspective of spatial spillover effect, China’s regional carbon emissions have significant spatial spillover effect, and carbon emissions trading has spatial spillover effect. From the perspective of spatial spillover, the carbon emission trading market promotes the carbon emission reduction in neighboring areas by promoting the clean transformation of energy structure in neighboring areas, improving technology absorption capacity and promoting technological progress.

Modeling the Nexus between European Carbon Emission Trading and Financial Market Returns: Practical Implications for Carbon Risk Reduction and Hedging

The carbon–financial nexus helps firms evaluate susceptibility to carbon risk more effectively. This is the first research article to model the short- and long-run co-integrating association between European financial markets, the CBOE oil price volatility index (OVZ) and the European carbon emission trading system (EU-ETS) by using the daily returns from 1 October 2013 to 1 October 2023. We utilize co-integration test followed by the ARDL framework with an error correction mechanism (ECM). Moreover, we utilize the DCC-GARCH-t copula framework to estimate the hedge ratio and to select an optimal portfolio weight for carbon risk hedging. Overall, the findings suggested that EU-ETS (OVZ) has a consistent positive (negative) short-term influence on all the equity returns of Belgium, Denmark, Finland, France, Germany, Ireland, Italy, Netherlands, Spain and the stock indices of the whole Eurozone. However, in the long term, EU-ETS has a positive (negative) effect on the stock returns of France and the Eurozone (Belgium and Spain). Belgian and Spanish companies could implement long-term carbon reduction policies. Belgian and Spanish firms should focus on the utilization of green energy resources and the internalization of carbon emission-free mechanical processes as this may offer a safeguard against the additional pressure arising from escalating carbon prices. Finally, an optimal portfolio weight selection strategy based upon the DCC-GARCH-t copula approach aims for higher hedging effectiveness (HE) than the hedge ratio strategy when adopting short-term positions in Italian and Danish equity markets to reduce the risk of long-term EU-ETS volatility.

Trading strategies of energy storage participation in day-ahead joint market based on Stackelberg game

The goal of "carbon peak, carbon neutral" and the increasing expansion of new energy have helped to advance the development of energy storage. However, since the operating cost of energy storage is high, carbon emission trading and power market trading have emerged, effectively improving the efficiency. In this paper, a trading strategy and bidding framework of energy storage participation in the day-ahead joint market are studied. A market bidding model has been established in a framework based on the Stackelberg game. Finally, the "Day-Ahead and Intra-Day and Carbon Emission Trading (CET)" market clearing model has been constructed. It has been simplified to solve the equivalent mixed-integer linear programming (MILP) problem with equilibrium constraints through the use of the Karush–Kuhn–Tucker (KKT) optimality criterion and duality principle. The proposed model is validated through improved examples to obtain thermal unit output cuts of up to 32.2% during load trough periods, and up to 16.75% increase in clearing prices during peak load periods. The storage life is extended and the storage output variation is minimized.

A study on the dynamic impact of carbon emission trading on green and high-quality development.

As a pivotal element in market mechanisms, carbon trading is increasingly recognized as crucial for achieving China's Carbon Peaking and Carbon Neutrality Goals. This study introduces a comprehensive dynamic model, integrating carbon trading, emissions, economic growth, and green technology innovation, to offer a holistic understanding of the interplay between these domains. Utilizing principles from nonlinear dynamics and chaos theory, the model is adept at simulating various scenarios and assessing the effectiveness of government policies in stabilizing these complex systems. In-depth analysis provided by this research sheds light on the nuanced impact of carbon trading policies on sustainable development. Key findings highlight (1) Carbon trading's essential role as a catalyst in propelling sustainable and high-quality growth. (2) A strong positive relationship is observed between the sophistication of the carbon trading mechanism and its effectiveness in stimulating green technology innovation and fostering high-quality green development. Notably, carbon trading's influence on green technology innovation markedly enhances the efficacy of carbon emission reduction strategies. (3) Government regulations are instrumental in augmenting carbon prices, thus incentivizing increased corporate participation in emission reduction and enhancing the overall impact of carbon emission reduction. Nevertheless, the study identifies a critical threshold in regulatory intensity, beyond which there is a risk of system destabilization ( ). These findings underscore the imperative for developing an integrated national carbon emission trading market, prioritizing sustainable growth strategies and diligently pursuing China's environmental objectives.

Substantial innovation or strategic innovation: An evolutionary game analysis of companies' green technology innovation strategies under carbon emission trading market

AbstractAlthough both the carbon emission trading market (CETM) and government regulatory actions promote companies' green technology innovation (GTI), little research has considered whether such innovation is substantial. In this paper, we categorize companies' GTI strategies into substantial innovation and strategic innovation. Considering market powers, the heterogeneity of companies, and the mutual influence of governments and companies, we construct a tripartite evolutionary game model that involves large and small companies and the government and conduct a simulation utilizing data on China's CETM. Our findings reveal that carbon trading prices, innovation subsidies, and the government's verification mechanism are the main factors that affect companies' choices regarding substantial innovation. However, the current carbon trading prices in China are relatively low, and companies are still likely to choose strategic innovation. Moreover, we find that when the substantial innovation of large companies exerts a greater impact on the product revenues of small companies, small companies are more inclined to choose substantial innovation. Therefore, in an effort to induce companies to choose substantial innovation, the CETM should play the leading role in this situation, and the government should implement different innovation subsidies and improve the verification mechanism.

The price behavior characteristics of China and Europe carbon emission trading market based on the perspective of time scaling and expected returns.

China has the world's largest carbon market in terms of greenhouse gas emissions, but its system needs to be improved and enhanced. In comparison, the European carbon market stands as the most mature and well-developed carbon market globally. Carbon trading prices, serving as a barometer for the carbon market, are significantly influenced by investor behavior. Therefore, it is necessary to analyze the characteristics of carbon trading prices in both China and Europe, considering the impact of investor trading intervals and psychological expected returns. This study utilizes the Zipf method to characterize the dynamic behavior of carbon trading prices between China and Europe, conducting a comparative analysis. The results show distinctive asymmetry in the behavior of carbon trading prices in both markets. In the Chinese market, when τ < 277, the absolute deviation da(τ, ε) value gradually changes but consistently indicates a bullish trend. However, when τ ≥ 277, the da(τ, ε) value surges rapidly, reflecting a pronounced bullish sentiment among investors toward carbon trading prices in China. In the European market, within the sample period, regardless of variations in τ and ε, the da(τ, ε) value shows a linear upward trend, indicating a significant overall bullishness in prices. This suggests a higher probability of long-term bullishness in carbon trading prices. Investors' investment time scale (τ) and expected returns (ε) both influence the behavior of carbon trading prices in both China and Europe. Generally, a longer τ implies a higher probability of bullishness. As for ε, higher values lead to more extreme judgments on price movements, resulting in greater distortion in carbon trading prices. Short-term investors (τ<1 month) anticipate extreme fluctuations, exhibiting random behavior when ε < 0.15 and converging rapidly to extreme values of 1 or 0 when ε ≥ 0.15. Long-term investors (τ>quarter) are less biased, expressing a bullish outlook on both Chinese and European carbon prices. With increasing ε, the probability of bullishness either increases or decreases rapidly until reaching the saturation point. Once saturated, there is no further distortion in carbon price behavior. Furthermore, the Chinese carbon market displays a positive trend in carbon trading prices and a higher probability of long-term bullishness. For the European market, lower expected returns contribute to considerable carbon trading price fluctuations, exacerbating risk and uncertainty. The results of this study contribute to understanding the diverse trading behaviors in Chinese and European carbon markets and provide guidance for avoiding extreme volatility in carbon trading prices.

Dynamic Analysis on Carbon Metabolism of the Northern Region of China Under the Background of Carbon Emission Trading Policy

The launch of the national carbon emissions trading market in China is a policy to carry out the Beautiful China initiative and to establish a low-carbon economic development system that promotes carbon emission and waste reduction. In order to detect the carbon metabolic processes of the pilot and nonpilot municipalities or provinces in the northern region of China， the theory of urban carbon metabolism and the methods of input-output analysis and ecological network analysis were introduced and used. The results showed that the direct carbon emissions of Beijing and Tianjin had decreased， but their embodied carbon emissions had increased since 2012. The direct and embodied carbon emissions of the pilot sectors in Beijing and Tianjin had the same trend； specifically， the emissions of the sectors of mining and washing of coal， extraction of petroleum and natural gas， and manufacture of non-metallic mineral products decreased significantly， but the sectors of production and supply of electric power and steam with high carbon emission increased. The same trend of the embodied carbon emission intensities of sectors with that of their embodied carbon emissions verified that the embodied added values were not growing with the promotion of the carbon emission trading market. Subsequently， the embodied carbon emission of the pilot sectors in all the municipalities and provinces of the northern region were all contributed mainly by the emissions embodied by a path length less than 6； therefore， it showed that more attention should be paid to the trade among sectors with a path length less than 6 and reducing their carbon emissions. Furthermore， from 2007 to 2012， products or service trading among sectors mostly concentrated on sectors within one municipality or province， and these products or services had the characteristics of low carbon emission. Since 2012， the integration development of the Beijing-Tianjin-Hebei urban agglomeration and the new regional economic patterns established in the northern region both promoted the trading across provinces and across sectors. This research is based on the background of the carbon emission trading policy and aims to build a methodology to identify the key actors and paths in a metabolic system. This could provide a scientific basis for regional policy implementation and regional long-term sustainable development.

Analysis of the Tripartite Evolutionary Game between MRV Institutions, Government, and Enterprises in the Context of the Carbon Trading Market

As the global carbon emission trading market develops, the role of Monitoring, Reporting, and Verification (MRV) institutions is becoming increasingly important. This paper analyzes the tripartite evolutionary game among MRV institutions, local government, and enterprises within the carbon trading market context and explores the impact of various factors on market behavior through sensitivity analysis. We find that changes in carbon prices, market maturity, the rent-seeking cost of enterprises, penalty policies of local government, and the supervisory intensity of MRV institutions significantly influence the strategic choices of the participating entities. Notably, high carbon prices may lead to collusive behaviors between enterprises and local government, while strengthened supervision and a reasonable penalty mechanism can promote fairness and justice in the market.

Wind power investment equilibrium guided by reliability option considering electricity-carbon emission trading-trading green certificate joint market

Reliability option (RO) is a capacity adequacy mechanism and it is coupled with electricity market, carbon emission trading market and trading green certificate market. This article explores the impact of implementing the RO mechanism in a multi-market trading context on wind power investment equilibrium and user side cost, under different demand elasticities and the degrees of competition on the generation side. We introduce a novel multi-agent deep reinforcement learning algorithm, leveraging the twin delayed deep deterministic policy gradient, aimed at obtaining equilibrium. Initially, we propose a method for calculating the comprehensive income of power producers, integrating risk preferences using Conditional Value at Risk. Subsequently, we employ a decentralized partially observable Markov decision process to emulate multi-agent investment patterns. During each exploration phase, wind power output scenarios are meticulously crafted via Latin hypercube sampling. Evaluations of our algorithm underscore its superior convergence and discerning rationality. Numerical simulations reveal that in areas with high demand elasticity, the RO mechanism primarily reduces user side risk without much impact on equilibrium. Yet, in regions with low demand elasticity, its role in influencing wind power investment and user side risk hinges on the degree of market competition and the designated wind power RO sales ratio.

Does the National Carbon Emissions Trading Market Promote Corporate Environmental Protection Investment? Evidence from China

China launched the National Carbon Emissions Trading Market (NCETM) in July 2021, heralding the first nationwide implementation of carbon emissions trading since the 2011 pilot scheme in China. The NCETM serves as a vital policy instrument that employs market mechanisms to regulate and mitigate greenhouse gas emissions. Thus, this study aims to examine how the NCETM in China, as an environmental regulatory policy, impacts environmental protection investment (EPI) made by enterprises. Specifically, the research seeks to address three key questions: (1) Does the NCETM have an impact on corporate EPI? (2) What are the mechanisms underlying the effect of the NCETM on corporate EPI? (3) Additionally, does the impact of the NCETM on corporate EPI vary with the location of the firms? By utilizing financial data from listed firms from 2018 to 2022 and employing the difference-in-differences (DID) model, the empirical results suggest that: (1) NCETM significantly stimulates the increase in EPI by firms. (2) The NCETM promotes environmental investment by inducing higher R&amp;D expenditures. (3) The effects of NCETM on firms’ EPI vary across regions, with the policy only being effective for firms in non-pilot regions that did not engage in the carbon emissions trading market prior to NCETM. This study provides empirical evidence for the microeconomic effects of the NCETM and a useful reference for the implementation of carbon emissions trading policies.

Research on the Application of Blockchain Technology in the Carbon Trading Market of Substations

Abstract This study examines the entire lifecycle carbon emissions from the construction of substations, emphasizing the demand response from the carbon emission trading market. We use blockchain technology to establish an intelligent contract framework to manage and control substation configurations within digital substations’ physical environments. Based on Blockchain, a regional substation intelligent control model is developed to facilitate optimal decision-making in the carbon trading market. Simulation analyses reveal that adjustments in capacity to 150MW can enhance the peak range from 041.2% to 042.0%, indicating a 0.8% improvement in efficiency. Additionally, this research assesses the carbon emission savings, correlating the volume of carbon transactions to the verification time, particularly noting a significant increase in time cost within the first 200 transactions. This paper contributes to understanding how digital technologies can optimize carbon emissions management and energy savings in substation construction.

Does Carbon Trading Lead to Green Technology Innovation: Recent Evidence From Chinese Companies in Resource-Based Industries

The carbon emission trading scheme (ETS) is critical to China&#x0027;s ability to reach the established carbon dioxide (CO₂) emissions reduction goal by 2030 and carbon neutrality by 2060. To determine whether the pilot ETS policy promulgated in China in 2011 has induced green technological innovation, we conducted a multidimensional empirical test to assess the financial and green patent licensing data of Chinese A-share (publicly listed) enterprises in Shanghai and Shenzhen from 2004 to 2019. Using a difference-in-difference model with robustness checks, we did not find that the pilot ETS has had green innovation effects on entire industries or all manufacturing. However, we did identify significant green innovation improvements in some resource-based industrial enterprises, and the promotion effect led to more green utility models than green invention patents. Furthermore, the policy&#x0027;s greatest green-innovation effects are reflected primarily in new patents&#x002F;utility models for low-carbon, energy-saving, and alternative energy technologies, particularly among large and nonstate enterprises. The impact mechanism tests indicate that the pilot policy encourages green innovation primarily through four policy instruments: increasing benefit income for resource-based industrial enterprises, reducing financial constraints, granting subsidies, and increasing incentives for enterprise R&amp;D. Therefore, this article not only confirms the effectiveness of carbon emission trading market policy, but also provides scientific guidance for the realization of green technology innovation.

탄소배출권 거래가 전남지역 산업 생산활동에 미치는 영향

When comparing South Korea's emission trading market on a global scale, such as in Europe, the United States, and China, South Korea possesses the hardware infrastructure required for the operation of an emission trading system. However, it appears to be lacking in the software aspect, including the implementation of various carbon reduction policies to complement the carbon emission trading system. The study empirically analyzes the impact of the carbon emission trading system on industries in Jeonnam. First, the carbon emission trading system does not seem to significantly constrain short-term production activities of businesses. Second, when examining the impact of carbon emission prices (KAU, EUA) on major industries in the Jeonnam region, carbon-related variables act as information intermediaries. It is evident that the chemical and steel industries in Jeonnam play the role of information recipients. Third, concerning the connectivity network with KAU as the central variable, it is apparent that the chemical and steel industries in Jeonnam receive more influence from KAU rather than influencing it. In the case of the connectivity network with EUA as the central variable, EUA plays the role of information recipients for the chemical and steel industries. This can be attributed to the participation of these industries in the European carbon emission trading market while exporting chemical and steel products to Europe, affecting EUA demand and prices. In the future, the impact of carbon emission reduction policies is likely to increase for domestic industries and companies in the Jeonnam region in the short term. To achieve regional and national carbon neutrality, policy measures tailored to the industrial structure characteristics of the Jeonnam region must be developed.

A hybrid forecasting approach for China's national carbon emission allowance prices with balanced accuracy and interpretability

A significant milestone in China's carbon market was reached with the official launch and operation of the National Carbon Emission Trading Market. The accurate prediction of the carbon price in this market is crucial for the government to formulate scientific policies regarding the carbon market and for companies to participate effectively. Nevertheless, it remains challenging to accurately predict price fluctuations in the carbon market because of the volatility and instability caused by several complex factors. This paper proposes a new carbon price forecasting framework that considers the potential factors influencing national carbon prices, including data decomposition and reconstruction techniques, feature selection techniques, machine learning forecasting techniques for intelligent optimisation, and research on model interpretability. This comprehensive framework aims to improve the accuracy and understandability of carbon price projections to respond better to the complexity and uncertainty of carbon markets. The results indicate that (1) the hybrid forecasting framework is highly accurate in forecasting national carbon market prices and far superior to other comparative models; (2) the factors driving national carbon prices vary according to the time scale. High-frequency series are sensitive to short-term economic and energy market indicators. Medium- and low-frequency series are more susceptible to financial markets and long-term economic conditions than high-frequency series. This study provides insights into the factors affecting China's national carbon market price and serves as a reference for companies and governments to develop carbon price forecasting tools.

Allowance-based Carbon Options Pricing Strategy and Asset Management Research Progress

Under the issue of global warming and environmental protection, low-carbon development has become an unshakable responsibility for governments worldwide. In China, the national carbon emission trading market established in 2021, which promotes the economic development of carbon derivatives. In order to facilitate the trading system, carbon options pricing theory has become a centerpiece of academic attention. This paper reviews the study progress in detail in the area of allowance-based carbon options pricing strategy carbon internationally, and makes an analysis of the application and management in international carbon markets. The mainstream pricing models include the Black-Scholes and the Monte Carlo option pricing models. On this basis, the carbon option prices estimated using the GARCH model and fractal Brownian motion have a higher degree of fitted value. In addition, this paper analyzes the application and management of carbon options in the carbon market. The carbon option helps reduce the carbon trading risk and the spendings on emission reduction for enterprises. This research intends to give a reference for the subsequent theoretical exploration of carbon options and promote the growth of the derivatives market.