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(searched for: doi:10.3390/su8111195)
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Tatsiana Savitskaya, , Yin Lu, Dzmitry Hrynshpan, Valentin Sarkisov, Jie Yu, Nabo Sun, Shilei Wang, Wei Ke, Li Wang
Published: 18 July 2021
Green Chemistry pp 107-123; https://doi.org/10.1007/978-981-16-3746-9_5

The publisher has not yet granted permission to display this abstract.
Rongting Sun, Kaiqi Wang, ,
Emerging Markets Finance and Trade pp 1-15; https://doi.org/10.1080/1540496x.2021.1925535

Abstract:
We empirically investigate the effect of emissions trading scheme (ETS) on the corporate performance of Chinese listed firms from 2010 to 2016, treating China’s pilot ETS as a quasi-natural experiment. Our difference-in-differences analysis shows that the ETS is significantly correlated with corporate performance of high-energy-consuming firms. While the policy effect strengthens in the first few years and then weakens by 2016. This indicates that ETS cannot sustainably and steadily affect the corporate performance. Finally, we find that ETS has a stronger impact on the performance of high-energy-consuming firms in regions with high governmental intervention and an underdeveloped legal system.
, Mohd Zaini Abd Karim,
Journal of Environmental Planning and Management, Volume 64, pp 581-610; https://doi.org/10.1080/09640568.2020.1776691

Abstract:
Today, China is the second-largest, fastest-growing economy in the world. This study analyzes asymmetric and time-varying impact of world energy prices (including world energy prices index, world coal prices, world crude oil prices and world natural gas prices) on China’s CO2 emissions. We used a non-linear ARDL (NARDL) model and wavelet analysis using monthly data from 1992 to 2017. The results based on the NARDL estimate show that world energy prices have an asymmetric impact on CO2 emissions. However, the results of wavelet pairwise correlation and wavelet-transform coherence suggest that the relationship between world energy prices and CO2 emissions differs over time and across sectors (i.e. short-term, medium-term, long-term and very long-term). Evidence suggests that ignoring fundamental non-linearities can lead to misleading outcomes. Such empirical results are expected to have a high importance for the efficient design and implementation of world energy prices and Chinese environmental policies.
Published: 10 July 2020
by MDPI
Sustainability, Volume 12; https://doi.org/10.3390/su12145581

Abstract:
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.
Published: 2 April 2020
by MDPI
Sustainability, Volume 12; https://doi.org/10.3390/su12072823

Abstract:
This paper aims to examine whether there is inherent dynamic connectedness among coal market prices, new energy stock prices and carbon emission trading (CET) prices in China under time- and frequency-varying perspectives. For this purpose, we apply a novel wavelet method proposed by Aguiar-Conraria et al. (2018). Specifically, utilizing the single wavelet power spectrum, the multiple wavelet coherency, the partial wavelet coherency, also combined with the partial phase difference and the partial wavelet gains, this paper discovers the time-frequency interaction between three markets. The empirical results show that the connectedness between the CET market price and the coal price is frequency-varying and mainly occur in the lower and higher frequency bands, while the connectedness between the CET market price and the new energy stock price mainly happen in the middle and lower frequency bands. In the high-frequency domain, the CET market price is mainly affected by the coal price, while the CET market price is dominated by the new energy stock price in the middle frequency. These uncovered frequency-varying characteristics among these markets in this study could provide several implications. Main participants in these markets, such as polluting industries, governments and financial actors, should pay close attention to the connectedness under different frequencies, in order to realize their goal of the production, the policymaking, and the investment.
Xiaojian Su,
Published: 13 August 2019
Abstract:
This paper studies the heterogeneous effects of exchange rate and stock market on carbon emission allowance price in four emissions trading scheme pilots in China. We employ a panel quantile regression model, which can describe both individual and distributional heterogeneity. The empirical results illustrate that the effects of explanatory variables on carbon emission allowance price is heterogeneous along the whole quantiles. Specifically, exchange rate has a negative effect on carbon emission allowance price at lower quantiles, while becomes a positive effect at higher quantiles. In addition, a negative effect exists between domestic stock market and carbon emission allowance price, and the intensity decreasing along with the increase of quantile. By contrast, an increasing positive effect is discovered between European stock market and domestic carbon emission allowance prices. Finally, heterogeneous effects on carbon emission allowance price can also be proved in European Union Emission Trading Scheme (EU-ETS).
Published: 1 February 2019
Applied Energy, Volume 239, pp 157-170; https://doi.org/10.1016/j.apenergy.2019.01.194

The publisher has not yet granted permission to display this abstract.
Published: 12 September 2018
by MDPI
Sustainability, Volume 10; https://doi.org/10.3390/su10093255

Abstract:
Verified emissions announcements are the most influential events in the European Union emissions trading scheme (EU ETS); they reveal demand information and have a significant impact on the carbon market. The extant literature tends to focus on examining the impacts of these verification events on the prices of carbon allowances, while scholars barely discuss how trading behaviors react to the announcements. Moreover, most of the studies are carried out from a macroeconomic perspective. This paper fills this gap by analyzing the impacts of the verified emissions announcements on the comoves of trading behaviors and carbon prices in Phase I (2005–2007) and Phase II (2008–2012). Specifically, we construct GARCH models to investigate the events’ heterogeneous influences in different periods, i.e., the complete periods, the announcement periods, the pre- and post-announcement periods. We observe that the verified emissions announcements boost the volume of compliance trading, particularly in Phase I. Furthermore, we show that the over-allocation of carbon allowances can be even more influential in disturbing the comoves than the verification events. Our microeconomic findings confirm the maturity of EU ETS in Phase II, exhibiting good agreement with the extant macroeconomic literature.
Published: 12 May 2018
by MDPI
Sustainability, Volume 10; https://doi.org/10.3390/su10051543

Abstract:
In this paper, provincial panel data for China during 1995–2015 and the time substitution data envelopment analysis (DEA) model were used to measure the influences of China’s carbon emissions reduction policy on economic growth under various reduction targets and to determine optimal economic growth and optimal carbon emissions of each province. In addition, this paper empirically examines the factors that influence the optimal economic growth and carbon emissions. The results indicate that not all provinces will suffer from a loss in gross domestic product (GDP) when confronted by the constraints of carbon emissions reductions. Certain provinces can achieve a win-win situation between economic growth and carbon emissions reductions if they are allowed to reallocate production decisions over time. Provinces with higher environmental efficiency, higher per capita GDP, smaller populations, and lower energy intensity might suffer from a larger loss in GDP. Therefore, they should set lower carbon emissions reduction targets.
Published: 2 September 2017
by MDPI
Abstract:
Given the growing evidence and scientific consensus on global climate change, carbon emission trading schemes (ETS) have been deemed crucial in mitigating the problem. Therefore, this study compares the mechanisms of ETS in the European Union with those in China. The results indicate similarities in cap determination, the coverage and calculation method of allowance allocation, trading participants and allowance category, offset credit, and MRV. On the other hand, the allocation method and supervision of allowance allocation, allowance formats and trading methods, market risk management, market linkage mechanism, and legislation security evidently appear to vary. However, the results were unable to identify which ETS is absolutely good or bad due to the political, economic, and institutional contexts and the varying developmental phases. Eventually, drawing on these findings, we conclude with implications for the promotion of ETS.
Published: 6 July 2017
by MDPI
Sustainability, Volume 9; https://doi.org/10.3390/su9071185

Abstract:
Due to various factors of uncertainty within production, the key performance indicators connected to production plans are difficult to fulfil. This problem becomes especially serious as emission regulations are enforced, which discourage manufacturers from high emission output and high energy consumption. Thus, this paper proposes a feedback control method for the production scheduling problem by considering energy consumption and makespan to help manufacturers keep production implementations in pace with production plans. The proposed method works in a rolling horizon framework, which establishes planned energy consumption and makespan, and adjusts the weights of the multiple scheduling optimization objectives for the next period, based on the feedback of the actual energy consumption and makespan in previous periods. A job shop scheduling case study is provided to illustrate the proposed method. The experiment results demonstrate the effectiveness of the proposed feedback control method.
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