Price and scale effects of China's carbon emission trading system pilots on emission reduction

Carbon Abatement and Leakage in China's Regional Carbon Emission Trading

Emission trading schemes (ETS) are increasingly becoming a popular policy instrument to balance carbon abatement and economic growth. As a globally unified carbon pricing system has not yet been established, whether regionally operated ETSs cause carbon leakage remains a major concern. Taking China's regional pilot ETSs as a quasi-natural experiment, the study uses the spatial difference-in-differences method to examine how regional ETSs affect carbon emissions in and outside cities of policy implementation. Our analysis finds that China's regional ETS policy contributes to a 6.1% reduction in urban CO2 emissions and a 6.6% decline in emissions intensity in regulated cities, causing carbon leakages that increase CO2 emissions in neighboring cities by 1.7% on average. Our finding further suggests that regional ETSs mitigate local CO2 emissions through outsourcing production, improving energy efficiency and decarbonizing energy structure, whereas the outsourcing of industrial production drives up CO2 emissions in adjacent cities. Moreover, the performances of regional ETSs vary largely by socioeconomic context and mechanism design. China's regional ETSs reduce CO2 emissions more effectively in central and industrial cities but with more severe carbon leakage, while rigorous compliance mechanisms and active market trading help deepen carbon abatement and alleviate carbon leakage.

Is carbon emission trading a green blessing or a curse for firm performance in China? A quasi-experiment design and exploring the spatial spillover effect

This paper conducts quasi-experiment design with Chinese listed companies microdata to investigate the effect and mechanism of corporate participation in carbon emission trading market on firm financial performance by using the staggered difference-in-differences method. We show that: a) corporate participation in carbon emission trading market can enhance firm financial performance; b) an increase in green innovation ability and a decrease in strategic choice variance both partially mediate the relationship between carbon emission trading and firm performance; c) executive background heterogeneity and external environmental uncertainty moderate the relationship between carbon emission trading and firm performance in different directions; d) our further study indicates that carbon emission trading pilot policy has a spatial spillover effect on firm financial performance in the neighboring provinces. Therefore, we recommend that the government and enterprises make an effort to further stimulate the vitality of corporate participation in carbon emission trading market.

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.

Dual-circulation: influence mechanism of ETS's carbon reduction and its spatiotemporal characteristics based on intensity modified SDID model

Traditional DID models overlook variations in policy intensity, causing estimation deviations from the actual situation and a limited understanding of the influence mechanism. In response, the Intensity Modified SDID Model is built to examine the influence mechanism of ETS's carbon reductions. Moreover, through model extensions, the study explores the spatiotemporal characteristics and heterogeneities of ETS's effects. Results show that: (1) "Dual-circulation" influence mechanism is confirmed, where ETS directly contributes to carbon reductions (2.70% to 10.0% impact) through external pathways, and internal pathways continuously strengthen reduction effects, comprehensive mechanisms are thereby formed and enhanced based on interaction among internal and external pathways. (2) Reasonable ETS levels are estimated and proposed to achieve "Dual Carbon Target", constraining nationwide carbon quotas by 20 billion tons/year, increasing carbon trading volumes by 80 thousand tons/year, and elevating the carbon trading prices by 100 RMB (14 USD) per ton. (3) ETS's carbon reduction effects are identified with temporal and spatial characteristics, temporally, effects peak in the 4th period (Event+4) but diminish in the 5th period (Event+5), spatially, effects peak in areas distancing around 1000 km but disappear beyond 1500 km. (4) ETS also has synergistic effects with atmospheric pollution reduction, including industrial emissions of sulfur dioxide and smoke (dust), but are insignificant to industrial emissions of wastewater and solid waste.

The impact of the carbon trading market on urban coordinated development in China

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.

A CNN-LSTM based deep learning model with high accuracy and robustness for carbon price forecasting: A case of Shenzhen's carbon market in China

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.

Does the low carbon transition impact urban resilience? Evidence from China's pilot cities for carbon emission trading

The low-carbon transition is a systemic economic and social change that will inevitably have an impact on many areas of the urban system. Has China's ongoing low-carbon transition impacted urban resilience (UR) systems while achieving urban energy saving and carbon emission reduction goals? This paper uses the implementation of the carbon emissions trading pilot policy (CETPP) as a "quasi-natural experiment." It evaluates the impact of the policy on UR using a difference-in-differences model based on the data of prefecture-level cities from 2008 to 2020. The study shows that pilot carbon trading policies favor UR, and the market mechanism of carbon emissions has a heterogeneous cause influence on UR. The impact of pilot carbon trading policies on UR varies according to the respective moderating effects of institutional factors, green technology innovation, industrial structure rationalization, and output effects.

Predicting regional carbon price in China based on multi-factor HKELM by combining secondary decomposition and ensemble learning

Accurately predicting carbon price is crucial for risk avoidance in the carbon financial market. In light of the complex characteristics of the regional carbon price in China, this paper proposes a model to forecast carbon price based on the multi-factor hybrid kernel-based extreme learning machine (HKELM) by combining secondary decomposition and ensemble learning. Variational mode decomposition (VMD) is first used to decompose the carbon price into several modes, and range entropy is then used to reconstruct these modes. The multi-factor HKELM optimized by the sparrow search algorithm is used to forecast the reconstructed subsequences, where the main external factors innovatively selected by maximum information coefficient and historical time-series data on carbon prices are both considered as input variables to the forecasting model. Following this, the improved complete ensemble-based empirical mode decomposition with adaptive noise and range entropy are respectively used to decompose and reconstruct the residual term generated by VMD. Finally, the nonlinear ensemble learning method is introduced to determine the predictions of residual term and final carbon price. In the empirical analysis of Guangzhou market, the root mean square error(RMSE), mean absolute error (MAE) and mean absolute percentage error (MAPE) of the model are 0.1716, 0.1218 and 0.0026, respectively. The proposed model outperforms other comparative models in predicting accuracy. The work here extends the research on forecasting theory and methods of predicting the carbon price.

Can carbon emission trading improve carbon emission performance? Evidence from a quasi-natural experiment in China

Carbon emission trading policies play a key role in reducing carbon emissions through market-based mechanisms. In the context of China's carbon neutrality goals and carbon peaking targets, it is important to predict and evaluate the effectiveness of such policies. The combined impact of carbon trading policies on carbon emission reduction and economic output has not been well investigated in previous studies. In this study, the impact of carbon emission trading policies on regional carbon emission performance was assessed through mechanism analysis and empirical tests. The mechanism analysis showed that carbon emission intensity reduction relied on three mediating effects: technological innovation incentives, industrial structure optimization, and energy substitution. For the empirical test, the multi-time difference-in-differences (DID) method was adopted to study the impact using panel data from 30 provinces in China between 2005 and 2019. Moreover, the specific impact mechanism was further tested using mediating effects. The results showed that China's carbon trading policy has significantly affected the carbon emission performance of the pilot regions, and factors such as GDP per capita, urbanization level, and capital-labor ratio have notably contributed to the reduction of carbon emission intensity. The proportions of the three mediating effects in the total effect were estimated to be 60.98%, 23.17%, and 10.14%, respectively. This study provides an empirical approach to the study of the impact of carbon trading policy on carbon emission reduction and economic output and can serve as a reference for addressing climate change and alleviating conflicts between the environment and economic growth in similar regions.

The impact of carbon emission trading policy on energy efficiency-evidence from China

Energy efficiency (EE) plays an important role in achieving the dual-carbon goal, and improving EE is thus indispensable. This paper evaluates the impact of carbon emission trading policy (CETP) on EE based on a difference-in-difference (DID) method, using 16-year data of 30 provinces and cities from 2005 to 2020. Conclusions are as follows: (1) CETP significantly promotes EE, and this conclusion still appears valid after robustness tests. (2) The positive impact of CETP on EE is more effective in regions of high foreign direct investment (FDI) and high government intervention (GOVI). (3) The positive impact of CETP on EE is through impact mechanisms of energy structure adjustment (ESA), green innovation (GI), and industrial structure upgrading (ISU). The findings in this paper may enrich current research in CETP and offer more pragmatic suggestions for policy advancement as well.

How does civil aviation achieve sustainable low-carbon development? - An abatement-cost perspective

With the rapid development of civil aviation, carbon emissions have brought severe environmental problems. Realizing efficient and sustainable carbon emission reduction is of great significance for achieving green development in civil aviation sector. Therefore, in the process of pursuing civil aviation carbon emission reduction goals, it is necessary to further consider how to achieve emission reduction at the lowest cost. Based on the accurate carbon emission performance evaluation, the carbon abatement cost among different representative airlines have been systematically compared. The main work and findings of this study can be summarized in the following three aspects. Firstly, a new nonparametric shadow price measurement method was constructed based on the Slacks-Based Measurement Data Envelopment Analysis (SBM-DEA). This can better reflect the essence of efficiency evaluation and the calculated shadow price results are more consistent with the real market. Secondly, the average value of carbon emission efficiency has experienced a fluctuating downward trend from 2011 to 2017, indicating that the carbon emission efficiency of global airlines has decreased. Thirdly, the average value of the shadow price is generally between 313.4 and 398.4 dollars/ton, showing an "up-down-up" trend, and reaching a peak of 398.4 dollars/ton in 2014. This can provide a basis for low-carbon policy makers in the civil aviation sector, and also provide reference for different types of airlines to achieve low-cost emission reduction.

The impact of electricity-carbon market coupling on system marginal clearing price and power supply cost

In this study, we assessed the impacts of the benchmark designs of emissions allowance allocation in China's national carbon emissions trading system with plant-level data and further estimated the marginal clearing price and power supply cost in Guangdong power market under electricity-carbon market coupling with unit commitment and economic dispatch model. We find that the existing allowances benchmark would result in a considerable surplus of allowances at about 222 Mt. But the benchmarking and exemplary levels on the heat rate of power supply would motivate thermal power units to reduce CO2 emissions. Under a tight balance of supply and demand in Guangdong, peaking thermal power plants will become the marginal clearing units and higher clearing prices will add to the revenue of lower cost inframarginal renewable energy power units. However, the combined impact of electricity-carbon market coupling would cause the marginal clearing price fluctuates obviously from 0 to 1159 CNY/MWh. Compared to the baseline scenario with free CO2 allowances allocation, the efficiency of thermal power utilization would decrease by 23%-59% and the net revenue per MWh power supply of coal-fired power units would decrease by 275%-325% under the stress scenario. Our study suggests that setting a more stringent allowances allocation benchmark for carbon price discovery is necessary. As electricity-carbon market coupling changes the role of coal-fired power plants to provide flexibility service and decrease their revenues, it calls for further market designs on proper reimbursement of flexible resources, under which the electricity market can effectively achieve the synergy among accommodating new energy, ensuring resource adequacy, and delivering cost efficiency. In addition, the synergy can be enhanced by formulating a tax program, which can promote renewable energy investment.

Will emission trading promote enterprise diversification? Evidence from China

This study examines the impact of the Chinese regional emission trading system (ETS) pilots on enterprise transformation from the perspective of diversification. We use data on Chinese A-share listed companies from 2004 to 2021, and adopt the staggered difference-in-differences (DID) and difference-in-difference-in-differences (DDD) models. The empirical results show that first, the ETS significantly increases the product quantity and revenue diversification of regulated firms. Second, the ETS promotes enterprise diversification through three channels: emission cost, emission risk, and market efficiency. Third, the ETS has a greater impact on the diversification of state-owned enterprises, firms with high business concentration, and firms with low innovation investment. Fourth, the ETS-driven diversification has not been successful as it has increased firms' costs and reduced their profitability. We recommend introducing industrial policies to guide the transformation of enterprises, encourage them to improve their innovation capabilities, and choose appropriate transformation strategies.

How can China achieve its goal of peaking carbon emissions at minimal cost? A research perspective from shadow price and optimal allocation of carbon emissions

The Chinese government has declared a determination at the 75th United Nations General Assembly that China will improve its independent contribution and adopt more powerful measures to peak the carbon emissions before 2030. However, such strict implementation of carbon reduction policies is bound to bring the cost of sacrificing economic development. In such a context, this paper tries to use shadow price to measure the average social cost of emission reduction, marginal abatement cost to depict the pressure to reduce carbon emissions based on non-radial distance function, and provides an optimal scheme for provincial emission reduction to minimize the national cost of emission reduction based on variable-coefficient model. Results show that: First, the average value of shadow price is 15.91 and varies widely among regions, which means on average reducing one unit of carbon emissions will sacrifice 15.914 yuan RMB of economic output, and there exists possibility of carbon transactions across regions; Second, on the one hand, marginal abatement cost of carbon emission for most regions presents an upward tendency over time, which means greater economic costs have to be sacrificed with economic development in the future; On the other hand, marginal abatement cost is much higher in regions with high economic level than that in the economically undeveloped areas, which indicates reducing carbon emissions is becoming increasingly difficult and would pay more economical cost in economically developed regions; Third, the optional allocation scheme of CO2 reduction derived from this research is better than administrative ways of Grandfathering and Benchmarking in terms of minimizing emission reduction cost. Results of this paper indicate that larger carbon trading market can be implemented in China to economically fulfill the commitment of peaking carbon emissions.