Carbon Trading Pilots Research Articles

Study on the effect of carbon trading regulation on green innovation and heterogeneity analysis from China

China launched seven pilot areas for climate change mitigation before establishing a unified carbon emissions trading system in 2014. To explore the heterogeneous effect of carbon trading regulation on green innovation in China, we constructed evolutionary games with players of governments and enterprises. We then conducted empirical studies with the difference-in-difference model. With the data of listed Chinese A-share companies from 2008 to 2018, we found that implementing carbon trading pilot projects in China significantly increases the green innovation output of enterprises in the pilot regions. Additionally, the sensitivity to carbon trading policies varies across industries and property rights. Regarding the quality of green innovation triggered by the pilot project, firms in the pilot regions prefer high-quality green invention patent innovations over low-quality green utility model patent innovations. In addition, state-owned enterprises tend to apply for high-quality green invention patents, while firms in high-pollution industries prefer to apply for lower-quality green utility model patents. Finally, we put forward policy suggestions. First, China should accelerate the pilot carbon trading regulation and expand its scope. Second, there should be regional and industrial differences in constricting carbon trading regulations. Third, the government should avoid unreasonable regulatory intensity design.

Market incentives, carbon quota allocation and carbon emission reduction: Evidence from China's carbon trading pilot policy.

As a major carbon dioxide-emitting country, China set carbon trading market to reduce enterprise carbon emissions through the rational allocation of carbon quotas among different enterprises and regions. The market has also conducted a preliminary exploration for the country to achieve carbon dioxide emissions peak in 2030 and carbon neutrality in 2060 while actively addressing the challenges of global climate change. This study analysed the emission reduction effect of China's carbon trading pilot policy, especially the role of carbon quota and carbon trading price. The analysis used county-level panel data from 1997 to 2017, regarded the implementation of the carbon trading pilot policy as a quasi-natural experiment, and used the difference-in-differences method. The results showed that, first, the policy implementation not only reduced regional carbon emissions but also inhibited carbon dioxide emissions per capita, with long-term effects. Second, the carbon emission reduction effect brought by the carbon pilot policy showed significant heterogeneous results with the different degrees of regional carbon emissions and environmental supervision. The effect was greater in areas with higher carbon emission density and stronger legal supervision. Third, the difference in carbon quota allocations resulted in different emission reduction effects, among which the historical method had the strongest effect. The carbon quota price and number of enterprises participating carbon trading market were the key factors affecting carbon emission reduction.

Air quality improvement effect and future contributions of carbon trading pilot programs in China

The carbon trading policy is a market-based tool aimed at reducing carbon emissions and may simultaneously yield a combined air quality improvement effect. This study employs a two-way fixed-effect model to estimate the causal relationship between daily carbon trading volumes and air pollution from 2015 to 2020. Results show that a one percent increase in daily carbon trading volumes leads to a reduction of 0.23% in PM2.5 and 0.26% in PM10. In addition to particulate matter, the carbon market can significantly reduce SO2 and air quality index. We also examine provincial and regional heterogeneities and find an apparent reduction effect in Beijing, Guangdong, Hubei, Tianjin, and cities in the more economically developed eastern region. Notably, our estimations indicate that the carbon market’s impact on reducing air pollution is most significant annually during the carbon quota compliance period and tends to intensify over the years. Furthermore, we predict the carbon trading scale to meet China’s stringent future air quality improvement target, indicating that the carbon trading volumes are projected to be 450 million tons in 2035 under the high contribution scenarios. These findings can provide insightful policy implications for China and other countries to establish more flexible and well-rounded carbon trading policies.

Reduction effect of carbon markets: A case study of the Beijing-Tianjin-Hebei region of China

The carbon market is a crucial market-oriented tool in achieving carbon neutrality and has been adopted by many countries and regions. China has established a policy system covering eight carbon trading pilots since 2013 and has implemented effective practices. Despite the evaluation of the carbon markets at the national level, few studies identified the carbon emission reduction effect for a specific region or assessed the differentiated characteristics that may significantly impact the development of the carbon market. This study took the Beijing-Tianjin-Hebei (BTH) region as the research sample and aimed to estimate the carbon emission reduction effect of the carbon market by using a difference-in-differences approach. Our findings suggested that the carbon market in the BTH region effectively reduced its carbon intensity by 14.04%. Our estimations were robust after using a winsorization panel or establishing a new control group. Furthermore, the results also indicated that the carbon market’s effect on reducing carbon intensity differs across cities and shows an increasing trend yearly. Relevant recommendations for promoting carbon trading policies were proposed.

Impact of Carbon Emission Trading Market on Regional Urbanization: an Empirical Study Based on a Difference-In-Differences Model

<p><big>China's carbon emission trading market has been formally established, but few studies have been conducted to analyze the impact of this policy on the regional urbanization level. Therefore, this paper evaluates whether the carbon trading pilot policy can enhance the regional urbanization level in China through the difference-in-differences method and analyzes the mediating role of industrial structure upgrading in this process. The results prove that the carbon trading market policy can accelerate the transformation and upgrading of industrial structure in the region so that it promotes the development of regional urbanization. Moreover, the effects of the policy are concentratedly manifested in the eastern region of China.</big></p>

Has the pilot carbon trading policy improved China's green total factor energy efficiency?

This work empirically studies the effect of a carbon trading pilot policy (CTPP) on green total-factor energy efficiency (GTFEE) by using 280 China’ prefecture-level cities from 2006 to 2017 as sample and adopting a difference-in-difference (DID) method. Results show that CTPP can significantly improve GTFEE after using an instrumental variable to overcome the endogenous problem. The impact mechanism test shows that CTPP can improve GTFEE by increasing the technological innovation level of enterprises. A heterogeneity test shows that the effect of CTPP on improving GTFEE in non-old industrial-based cities and non-resource-based cities is less than that in old industrial-based cities and resource-based cities. Compared with other carbon trading pilot areas, the Beijing carbon market is more prominent in improving GTFEE. The pilot areas' economic penalty exerts a positive effect on GTFEE in the pilot areas, if the pilot areas are strict in their reward and punishment systems for performance, then the situation will be conducive to the improvement of GTFEE.

Effect of China's carbon market on the promotion of green technological innovation

The carbon trading system has been identified as an effective policy for reducing carbon emissions and a crucial environmental tool for achieving the carbon neutrality target. This study employed a two-way fixed-effects model to investigate the possible impacts of China's carbon trading policy on green technological innovation in the carbon trading pilot cities. Our results indicate that the carbon trading policy considerably promotes the green technological innovations of enterprises. One million CNY increases in carbon trading turnover will increase the number of granted green invention patents by 119.4 when the city and year fixed-effects are controlled. We conducted a series of tests, such as changing the dependent variable, shortening the sample period, and testing the non-linear relationship, to support the robustness of the main findings. Moreover, our heterogeneous tests demonstrate that the effects of the carbon trading policy on green technological innovation vary across cities with different dimensions: municipalities that are directly under the central government, cities with high GDP, cities in the eastern region, and cities with high market vitality have seen higher green technological innovation effects. Finally, we recommend strategies for increasing the vitality of the carbon market, i.e., facilitating the linkage between carbon trading pilots and the national carbon market.

A comparison of the operation of China's carbon trading market and energy market and their spillover effects

This study measures the liquidity and volatility of the operation of the carbon trading and energy markets using liquidity ratio indicators and log return indicators. It adopts China's carbon trading and energy markets as the research objects, and evaluates the mean spillover effects and volatility spillover effects between the two using the vector autoregression (VAR) model and the BEKK-MGARCH model. The findings indicate that: (1) The liquidity of China's carbon trading market is better than that of the energy market. The average liquidity ratio of the Hubei and Shenzhen carbon trading markets is much lower than that of the coal market, 43016.131. It may be attributed to the fact that China's carbon trading market is currently small and easy to regulate. (2) The volatility of both the Chinese carbon trading market and energy market is small, and the absolute values of the mean log return rate are close to 0. It could be because China's carbon trading market is mainly distributed through free quota allocation, while the energy market has been mature and stable for many years. (3) There is a spillover effect between the carbon trading and energy markets in some parts of China, but the direction and degree of spillover effect vary, which may be due to differences in the economic development level, energy consumption structure, and environmental policies of each pilot carbon trading region. (4) The spillover effect between the two markets is stronger, perhaps due to China's current model of using coal as the main fuel.

Impact of government subsidies on the innovation performance of the photovoltaic industry: Based on the moderating effect of carbon trading prices

Currently, there is much concern about traditional energy transition owing to the exacerbation of various environmental issues. As a highly developed industry in terms of renewable energy, the photovoltaic (PV) industry has played a significant part in achieving the goal of low carbon development. This study examines Chinese-listed PV enterprises from 2014 to 2020 to explore not only the impact of government subsidies on innovation performance but also the moderating effect of carbon trading prices. The results are as follows. First, government subsidies have a promoting effect on innovation performance and R&D input plays a mediating role on a continued basis. Second, this promoting effect is more pronounced in zones designated for carbon trading pilot. Finally, carbon trading prices exert a positive moderating effect between government subsidies and innovation performance. Therefore, while increasing government subsidies, the state should also create a carbon trading market with more realistic trading prices for PV enterprises and give full play to the price discovery process in the carbon market.

Has the Carbon Trading Pilot Market Improved Enterprises’ Export Green-Sophistication in China?

This study empirically examined the effect of a carbon trading pilot market on export green-sophistication of Chinese listed enterprises by adopting a difference-in-difference method. Findings show that a carbon trading pilot market can improve enterprises’ export green-sophistication after using robustness tests to overcome endogeneity. The impact mechanism test shows that a carbon trading pilot market can improve export green-sophistication by increasing green technology innovation. Further research on the system design of carbon trading pilot markets shows that the greater the total carbon quota allocation, the larger the reduction in the trading volume of Chinese certified emissions. Furthermore, the weaker the punishment for an enterprise’s default in the pilot areas, the less favorable it is for enterprises to improve their export green-sophistication. Compared with the grandfather and historical intensity methods, benchmarking used in the allocation of carbon quotas is conducive to the improvement of the export green-sophistication of enterprises.

Study on the influence of carbon trading pilot policy on energy efficiency in power industry

PurposeTo cope with climate change and achieve the dual carbon goal, China has actively promoted the implementation of carbon trading pilot policy, among which the power industry plays an important role in China’s carbon emission reduction work. The purpose of this paper is to study the influence of carbon trading policy on the energy efficiency of power industry and achieve the comprehensive goal of carbon emission reduction, carbon peak and carbon neutralization.Design/methodology/approachThis paper constructs the difference-in-differences model based on 2012–2019 provincial data to study the impact of carbon trading policy on energy efficiency in the power industry and its effect path. Heterogeneity analysis was conducted to compare the effects of carbon trading policy in eastern, central and western regions as well as at different levels of power structures.FindingsCarbon trading policy can significantly improve the energy efficiency of the power industry, and the policy effect is more significant in eastern and western regions and areas with high power structure. Mechanism analysis shows that carbon trading policy mainly influences the energy efficiency of power industry by environmental protection investment, power consumption demand and industrial structure.Originality/valueThis paper uses provincial panel data to deeply study the influence of carbon trading policy on energy efficiency of the power industry and its effect path. By constructing the difference-in-differences model, this paper empirically analyzes the governance effect of carbon trading policy. Meanwhile, it controls individual and time effects to solve the endogeneity problem prevalent in previous literature.

Impact of Carbon Trading System on Green Economic Growth in China

Whether China’s economy can maintain sustainable growth has been debated both in China and internationally, and the most representative critique has been summarized in the “Krugman Query”. Faced with such doubts, how to achieve a “win-win” for economic growth and environmental protection has become one of the central objectives of local government work while striving for the new vision of development. Taking China’s carbon trading pilot policy as an example, and based on panel data of 30 provincial administrative regions in China from 2001 to 2018, this paper uses the Data Envelopment Analysis-Malmquist index model and the Propensity Score Matching-Difference in Difference method to measure the level of green economic growth from two aspects: green development mode and economic growth effect, and further explore the impact of China’s carbon trading system on green economic growth. The results show that the implementation of the carbon trading system promoted both the green development level and economic growth of pilot cities, and positively affected green total factor productivity, refuting the “Krugman Query”. Finally, the study puts forward a series of recommendations in strengthening environmental regulation, improving green technology innovation, and developing low-carbon industries.

The Energy Saving and Emission Reduction Effect of Carbon Trading Pilot Policy in China: Evidence from a Quasi-Natural Experiment.

Promoting the carbon emission trading system has been a crucial measure for China to fulfill its carbon neutrality commitment. Taking the carbon emission trading system implemented in China in 2013 as a quasi-natural experiment, based on the provincial panel data of China from 2005 to 2019, this paper adopts the difference-in-difference (DID) method and the synthetic control method (SCM) to evaluate the impact of the carbon emission trading system on energy conservation and emission reduction in pilot provinces and cities. The research findings reveal that, on the whole, the carbon emission trading system has significantly promoted the process of energy conservation and emission reduction in pilot provinces and cities. Other robustness tests, including the parallel trend test, PSM–DID stationarity test and placebo test have also been passed. Heterogeneity analysis shows that the most significant policy effects occur in Tianjin and Shanghai, followed by Hubei. The emission reduction effect of Guangdong displays a trend of first decreasing and then increasing. The test results demonstrate that the carbon emission trading system can strengthen the process of energy conservation and emission reduction by optimizing the industrial structure and energy structure. In conclusion, policy makers should coordinate the relationship between the government and the market and speed up the transformation of environmental policy from command control type to market incentive type. Meanwhile, improve the property right system and accelerate the promotion of carbon emission trading pilot policies in China according to local conditions. By encouraging technological innovation, a new market-oriented path of energy conservation and emission reduction guided by the enhancement of energy efficiency and the optimization of energy and industrial structures ought to be formed.

An optimized decomposition integration framework for carbon price prediction based on multi-factor two-stage feature dimension reduction.

The carbon trading market is an effective tool to combat greenhouse gas emissions, and as the core issue of carbon market, carbon price can stimulate the market for technological innovation and industrial transformation. However, the complex characteristics of carbon price such as nonlinearity and nonstationarity bring great challenges to carbon price prediction research. In this study, potential influencing factors of carbon price are introduced into carbon price forecasting, and a novel hybrid carbon price forecasting framework is developed, which contains data decomposition and reconstruction techniques, two-stage feature dimension reduction methods, intelligent and optimized deep learning forecasting with nonlinear integrated models and interval forecasting. Firstly, the carbon price series is decomposed into several simple and smooth subsequences using variational modal decomposition. The stacked autoencoder is then used to extract its effective features and reconstruct them into several new subsequences. A two-stage feature dimension reduction method is utilized for feature selection and extraction of exogenous variables. A bidirectional long and short-term memory model optimized based on the cuckoo search algorithm was used for prediction and nonlinear integration. Finally, Gaussian process regression based on a hybrid kernel function is applied to carbon price interval forecasting. The validity of the model was verified on seven real carbon trading pilot datasets in China. The methodology outperforms all benchmark models in the final simulation results, providing a novel and efficient forecasting method for the carbon trading industry.

Impact of carbon trading on agricultural green total factor productivity in China

The implementation of the carbon trading system has a great impact on all aspects of the economy and society. Agriculture, which accounts for 34% of global carbon emissions, has also been hit hard as a high carbon emitting industry (Crippa M, 2021). This study uses agricultural green total factor productivity as an important indicator of agricultural green sustainable development, and analyzes the impact of China's carbon trading system on agricultural green total factor productivity, which can provide a reference for other countries that want to improve agricultural sustainable development and implement carbon trading. In this paper, the producer theory is used to build the basic model, and the differences-in-differences (DID) method is used to analyze the provincial data samples in China from 2000 to 2020. It is found that: the implementation of carbon trading pilot policy has a significant promotion effect on agricultural green total factor productivity; and after the implementation of carbon trading policy, with the advancement of time, under the constraint of reducing carbon quota, the promotion effect of agricultural green total factor productivity becomes stronger and stronger. Even in the regions without carbon trading pilot program, the policy spillover effect will also be obvious and promote the development of green total factor productivity of agriculture in this area.

Blockchain solutions for carbon markets are nearing maturity

Blockchain solutions for carbon markets are nearing maturity

A Study of the Influencing Factors on the Carbon Emission Trading Price in China Based on the Improved Gray Relational Analysis Model

Carbon emission trading market construction is an important policy tool to promote the realization of China’s “double carbon” goal. However, problems still exist, such as the lack of market trading vitality, the large difference in carbon trading prices between the eight pilot markets and the instability of the prices. In order to explore the key influencing factors on carbon trading prices, 15 factors were selected to study in detail according to the policy, green industry, economy and environment. Taking China’s eight pilot carbon trading markets as research subjects, we explored the correlation degree of each factor by using the improved gray relational analysis model (GRAM) from the two dimensions of space and time. The research results show that from the space dimension, the industrial development level, development degree of low-carbon industries, air pollution degree and green technology maturity are the main factors that affect the carbon trading price in the eight pilot areas. Meanwhile, from the time dimension, the correlation degree between various factors and carbon trading price both showed a downward trend as a whole, and the fluctuation of the correlation degree of individual factors was different from the overall trend. In conclusion, we can put forward recommendations on the pricing mechanism of the carbon trading market after this comprehensive study.

Spillover effects and nonlinear correlations between carbon emissions and stock markets: An empirical analysis of China's carbon-intensive industries

This study analyzes the correlations between carbon emissions and related industry stock markets in China. We propose a carbon-intensive industry index firstly. According to the Spillover Index, the two markets interact and the carbon-intensive stock market acts as an information receiver in most cases. We apply the Multifractal Cross-Correlation Analysis, Detrended Cross-Correlation Coefficient, and the modified Time-lagged Detrended Cross-Correlation to characterize the nonlinear correlations between carbon allowance price returns and the stock returns of carbon-intensive industries. The carbon emission trading market is found to be more volatile and inefficient than the stock market; the properties of the carbon trading pilot explain the direction and magnitude of the nonlinear correlations. The level of intervention by the government authority affects the magnitude of correlations; the strongest dynamic return spillovers and the most persistent time-lag cross-correlations were observed in the Shenzhen pilot—the most market-oriented carbon emission trading pilot in China. The allowance allocation method plays an important role in deciding the direction of the nonlinear correlations. Our empirical results show the stock returns of carbon-intensive industries and the carbon allowance price returns were positively cross-correlated in Shenzhen and Shanghai pilots, while the cross-correlations were negative in Beijing, Guangdong, and Hubei pilots.

Air pollution and innovation performance of Chinese cities: human capital and labour cost perspective.

Environmental protection and innovation performance are key issues that affect the sustainable development and value growth of cities. Using data of 272 prefecture-level cities during 2002-2016 and 2,169 listed companies, and the air ventilation coefficient and government environmental regulations, as the instrumental variables for PM2.5 concentrations, this paper applies two-stage OLS (2SLS) to investigate how air pollution affects China's technological innovation and its realization mechanism. The results indicate that the rise in air pollution significantly inhibits the technological innovation level of regions as a whole as well as individual enterprises. When considering the spatial effect of the spread of PM2.5 concentrations, due to positive spillover effects on innovation activities, the spread of air pollution has negative impacts on technological innovation activities in surrounding cities. Human capital and labour costs are important channels through which air pollution influences China's technological innovation. The implementation of pilot carbon trading policies can effectively reduce air pollution and then contribute to the achievement of the goals of the green growth strategy.

Agricultural Ecological Efficiency under the Carbon Emissions Trading System in China: A Spatial Difference-in-Difference Approach

The agriculture sector plays a significant role in the development of the national economy and providing raw materials to the industrial sector. Trying to get more agricultural productivity, most farmers ignored the adverse effects of agricultural chemicals or pesticides that have a negative impact on the environment. So, the importance of agricultural ecological efficiency needs to be understood. This study attempts to explore whether agriculture, as an important source of carbon dioxide production, can have an effective impact on the agricultural ecological efficiency of carbon trading pilot policies in the context of the global implementation of carbon trading. This study evaluated the agricultural ecological efficiency (AEE) and its spatial distribution characteristics of 31 provinces in China, the data period was from 2000 to 2018. By applying the spatial difference-in-difference (SDID) approach, the study investigates the effects of low-carbon policies on agricultural ecological efficiency in pilot areas. The results demonstrate that low-carbon trading pilot policies have a significant impact on agricultural ecological efficiency. At the same time, the effects of regional economic development, population growth, urbanization, and urban innovation on efficiency are also significant. The improvement of agricultural ecological efficiency requires not only the full implementation of low-carbon trading pilot policies but also the development of regional economy and high-quality agriculture. The findings provide further policy recommendations for high-quality agricultural development.