Does China’s carbon emissions trading scheme really work? A case study of the hubei pilot

The carbon emission trading scheme (ETS), tradable green certificate (TGC) and green power trading (GPT) policies are vital for promoting energy transformation and carbon reduction under the dual carbon goals. However, the effects of and relationships among multiple policies urgently need to be studied. In this work, the panel data of 30 provinces in China from 2010 to 2023 are used. First, through the multiperiod difference-in-differences (DID) method, fixed effect models and mediating effect models, the carbon reduction effects of the pilot and national ETS policies, the renewable energy development effects of the TGC and GPT policies, and the multipolicy synergy effect are examined. A dual machine learning model is innovatively introduced to test the robustness of the results. Second, the slack-based measure–directional distance function–global Malmquist–Luenberger (SBM–DDF–GML) method is used to calculate the GTFP and investigate its transmission effect on policies. Finally, the impacts of the ETS, TGC and GPT policies on fossil fuel consumption are further analysed. The results indicate the following. (1) The pilot ETS policy reduces carbon emissions and carbon intensity, whereas the national ETS policy increases carbon emissions and carbon intensity in the short term. The TGC and GPT policies increase renewable energy generation and its proportion. (2) The synergy of the pilot ETS and GPT policies is the best for reducing carbon emissions and carbon intensity. The synergy among national ETS, TGC and GPT policies is optimal for developing renewable energy. In addition, there is redundancy between the TGC and GPT policies. (3) The pilot ETS policy inhibits GTFP, whereas the national ETS, TGC and GPT policies promote GTFP. The GTFP significantly reduces carbon emissions and carbon intensity and increases renewable energy generation and its proportion. (4) Both the pilot ETS and national ETS policies reduce the intensity of fossil fuel consumption. The GPT policy reduces the total level of fossil fuel consumption, whereas the TGC policy increases this level. In this work, innovative decarbonisation policies synergy pathways and insights into achieving green and low-carbon transitions in China and other developing countries are provided.

Since carbon price volatility is critical to the risk management of the CO2 emissions trading market, research has focused on energy prices and macroeconomic drivers which cause changes in carbon prices and make the carbon market more volatile than other markets. However, they have ignored whether the impact of carbon price determinants changes when the carbon price is at different levels. To fill this gap, this paper applies a semiparametric quantile regression model to explore the effects of energy prices and macroeconomic drivers on carbon prices at different quantiles. The model combines the advantages of parameter estimation, nonparametric estimation and quantile regression to describe the nonlinear relationship between carbon price and its fundamentals, which do not need to make any assumptions about the random error. Carbon prices are high–tailed and exhibit higher kurtosis, the traditional models which tend to assume that data are normally distributed can’t perform well. Furthermore, the semiparametric model doesn’t need to assume that the data are normally distributed. Therefore, the semiparametric model can effectively model the data. Some new evidence from China’s emission trading scheme (ETS) pilots shows that energy prices and macroeconomic drivers have different effects on carbon prices at high or low quantiles. First, the negative impact of coal prices on carbon prices was greater at the lower quantile of carbon prices in the Shenzhen ETS pilot. However, the effects of coal prices were positive in the Beijing ETS pilot, which may be attributed to great demand for coal. Second, oil prices had greater negative effects on carbon prices at higher quantiles in Beijing and Hubei ETS pilots. This can be attributed to the fact that businesses use less oil when carbon prices are high. For the Shenzhen ETS pilot, the effects of oil prices were positive. Third, natural gas prices have a stronger effect on carbon prices as quantiles increased in the Beijing and Hubei ETS pilots. Lastly, the effects of macroeconomic drivers on carbon prices at low quantiles were stronger in the Shenzhen ETS pilots and higher at the medium quantiles in Beijing and Hubei ETS pilots. These findings suggest that the impact of determinants on the carbon prices at different levels is not constant. Ignoring this issue will lead to a missed warning about the risks of the carbon market. This study will be of positive significance for China’s emission trading scheme (ETS) pilots, in order to accurately monitor the effects of carbon prices determinants and effectively avoid carbon market risks.

Based on the panel data of 277 cities between 2003 and 2017 and a unique city-level dataset of green patent applications, this study employs the difference-in-differences (DID) method to evaluate the effect of China’s carbon emission trading scheme (ETS) pilots on urban green innovation. The findings indicate that China’s ETS pilots have a positive impact on urban green innovation, and that impact is more significant for municipalities than for prefecture-level cities. Furthermore, the impact on different categories of urban green innovation is heterogeneous. More specifically, China’s ETS pilots have significantly spurred urban green innovation that is closely related to energy conservation and emission reduction, including alternative energy production, transportation, energy conservation and so forth. Moreover, the facilitating effect of China’s ETS pilots on urban green innovation suffers from a lagging effect, which began to show a significant positive effect in 2016. Overall, this paper identifies the effect of China’s ETS pilots on urban green innovation, and suggests that the government should consider the heterogeneity of urban green innovation when designing national ETS policies.

Some developed economies have run emission trading scheme (ETS) to mitigate carbon emissions. However, we know little about the effectiveness and heterogeneity of ETS in a context of developing economy. This paper evaluates the effectiveness and heterogeneity of China's pilot ETS, the first ETS run in a developing economy. Difference-in-difference (DID) and difference-in-difference-in-difference (DDD) methods are employed to analyze provincial industrial-level data. The heterogeneity of ETS effects is also explored from regional and industrial perspectives. The empirical results show that the pilot ETS can effectively reduce pilot industries' carbon emissions. The reduction effect of the pilot ETS has a substantial heterogeneity for different pilot provinces and industries. Carbon emissions are reduced by the pilot ETS through technological innovation and the adjustment of industrial structure. The empirical results suggest that policymakers may consider establishing a national ETS and differentiating carbon quota allowance in covered regions and industries in the current pilot ETS.

China's ETS pilots: Program design, industry risk, and long-term investment

Ex-post cap adjustment for China’s ETS: an applicable indexation rule, simulating the Hubei ETS, and implications for a national scheme

This paper explores the effect of China’s emission trading scheme (ETS) pilot policy implemented during 2013-2014 on carbon emission performance. Adopting the Difference-in-Difference (DID) model, we find that: 1) China’s ETS pilot policy can significantly improve the carbon emission performance of listed companies in the pilot provinces. 2) The heterogeneity analysis shows that the carbon emission performance of listed companies in the eastern coastal pilot areas has improved significantly, which is not significant in the central and western pilot areas. 3) We find that China’s ETS pilot policy can significantly improve innovation capabilities of listed companies, suggesting that innovation is a channel for the impact of the China’s ETS pilot policy on carbon emission performance in the pilot provinces. Overall, our study shows that ETS pilot policy has played a governance role in China and improved carbon emission performance. We further highlight some important policy implications with respect to helping companies save energy and reduce emissions, and promoting the further improvement of China’s ETS pilot policy.

Understanding of the influencing factors of industrial sector carbon dioxide emissions is essential to reduce natural and anthropogenic greenhouse gas emissions. In this paper, we applied the Logarithmic Mean Divisia Index (LMDI) decomposition method based on the extended Kaya identity to analyze the changes in industrial carbon dioxide emissions resulting from 39 industrial sectors in Inner Mongolia northeast of China over the period 2003–2012. The factors were divided into five types of effects i.e., industrial growth effect, industrial structure effect, energy effect, energy intensity effect, population effect and comparative analysis of differential influences of various factors on industrial sector. Our results clearly show that (1) Industrial sector carbon dioxide emissions have increased from 134.00 million ton in 2003 to 513.46 million ton in 2012, with an annual average growth rate of 16.097%. The industrial carbon dioxide emissions intensity has decreased from 0.99 million ton/billion yuan to 0.28 million ton/billion yuan. Also, the energy structure has been dominated by coal; (2) Production and supply of electric power, steam and hot water, coal mining and dressing, smelting and pressing of ferrous metals, petroleum processing, coking and nuclear fuel processing, and raw chemical materials and chemical products account for 89.74% of total increased industrial carbon dioxide emissions; (3) The industrial growth effect and population effect are found to be a critical driving force for increasing industrial sector carbon dioxide emissions over the research period. The energy intensity effect is the crucial drivers of the decrease of carbon dioxide emissions. However, the energy structure effect and industrial structure effect have considerably varied over the study years without displaying any clear trend.

This paper considers the nature and role of measures in China's Emissions Trading Scheme (ETS) pilots specifically designed to constrain market price fluctuation. These are primarily banking and borrowing of credits, permit reserves combined with direct market intervention, variations of trading bands/corridors, price ceilings and floors, market ‘safety valves’ and adjustment of emissions caps in defined circumstances. To provide realistic context, the setting of emissions caps, methods to allocate permits and the broad range of other factors impacting on Chinese ETS prices are considered. Key aspects of the market performance of the Chinese ETS pilots, focusing on price levels and volatility, are then addressed. It is argued that elements of scheme design regarding emissions cap setting and allocation of permits have the most fundamental impact on price levels. Compliance measures, rules regarding international investment and secondary markets and transitional provisions from the pilots to a national ETS have also been significant. Price volatility measures can nonetheless play a significant role in providing adequate price stability to moderate investment uncertainty. Price floors and ceilings can also play a role in incentivizing investment, to implement emissions reduction goals. To be effective, however, scheme design needs to demonstrate a credible commitment to scarcity of permits through adequately ambitious emissions caps and allocation methods.

Review of recent progress of emission trading policy in China

Carbon markets devolve governance to external institutions and displace power from sovereign states. Major producers in these markets, notably China, have expressed concern about the adverse implications for national interests and sovereignty associated with selling off the rights to emit carbon emissions abroad. This article suggests that such concern has shaped the discursive context in which emission trading schemes have gained popularity in the country. Our discourse analysis shows that notions of market power are made manifest as a powerful storyline. In the Chinese language, “power,” “sovereignty,” and “rights” all use the same character. The storyline captures all these expressions and allows for a positive view about active engagement in carbon trading as a way to protect development rights and redeem carbon sovereignty. Thus, the contested policy of emissions trading becomes embedded in the more appealing narrative of national development and made politically attractive, despite unfavorable realities against it.

Environmental and economic performance of China’s ETS pilots: New evidence from an expanded synthetic control method

Impact of economic policy uncertainty on the volatility of China's emission trading scheme pilots

Aligning emissions trading and feed-in tariffs in China

ABSTRACTChina launched its national carbon emissions trading scheme (ETS) in 2017. The choice of allowance allocation methods can strongly influence the political acceptance of an ETS by enterprises/sectors that are covered by it. This article builds a computable general equilibrium model to conduct a quantitative analysis of the effects of nine common allowance allocation methods on both the macro-economy and the industries covered by the ETS. The results of the model show that national gross domestic product (GDP) decreases by 0.37–0.44% during the 13th Five-Year Plan period against a backdrop of a 2% annual reduction in carbon emissions from the sectors covered by the ETS compared with the business-as-usual scenario. China's total emissions drop by 1.71–1.76%. When auctioning and allocation approaches without ex-post adjustment are used, the allowance price is 40–45 yuan/tCO2. When the dynamic allocation methods are used, the allowance price increases to 70–75 yuan/tCO2. Auctioning and allocation approaches without ex-post adjustment exert the same influence on macroscopic indicators (such as GDP and total emissions) and industry indicators (such as output and price). The dynamic allocation methods have a subsidy effect, which can significantly reduce the effect of the ETS on GDP and industry output while significantly increasing the allowance price and decreasing the economic efficiency of the ETS. The cement and steel industries are the most sensitive to the output subsidy effect of the dynamic allocation methods. This article suggests a limit on the use of dynamic allocation approaches to avoid excessively high allowance prices and excessive subsidies for overcapacity industries.Key policy insightsAuctioning and one-off allocation purely based on historical data are most economically efficient; dynamic allocation based on updated or actual output data could reduce the impact of the ETS on enterprises’ output, but will increase the allowance price and thus reduce the economic efficiency of the ETS.Implementing a national ETS will have limited impact on China's GDP, but could promote emissions abatement of the whole economy in an efficient way.Different allocation methods have almost the same impact on GDP, but the impacts on different sectors are significantly different.