Research on the influence mechanism of carbon trading on new energy—A case study of ESER system for China

Fang, Guochang; Lu, Longxi; Li, Tian; He, Yan; Yin, Huibo

doi:10.1016/j.physa.2019.123572

Cited by 28 publications

(8 citation statements)

References 35 publications

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“…Few studies also focus on antidriving mechanism and the effect of carbon emissions and economic aggregate on the use and development of new energy in China. Fang et al (2020) discussed the impact of carbon trade on new energy with regard to the antidriving mechanism of carbon emission. The results showed that a mature carbon trading market can promote new energy development, whereas carbon trading and new energy are very sensitive to government control.…”

Section: Carbon Emissionsmentioning

confidence: 99%

“…2) Carbon Emissions (CE). At present, the global warming and environmental pollution caused by excessive emissions of greenhouse gases (e.g., carbon dioxide) have become one of the serious problems faced by humanity (Akhmat et al, 2014;Dilmore and Zhang, 2018;Zhang et al, 2020) and one of the important driving factors for the rise of new energy industry (Ren et al, 2015;Fang et al, 2020;Wang, 2020). Carbon emission data are measured by carbon dioxide emission data in China.…”

Section: Internal Energy Price Relative Indexmentioning

confidence: 99%

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Influencing Factors of New Energy Development in China: Based on ARDL Cointegration and Granger Causality Analysis

2021

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The development and competition of the new energy industry will become an important battlefield of a new round of technological and industrial competition. This study use the annual data from 1990 to 2019 to understand the factors affecting the development of new energy development in China by examining the long-run and causal relationship among the proportion of new energy consumption, energy prices, carbon emissions, industrial structure, economic growth, and new energy power generation in a multivariate model for China. The findings indicate that in the long run, new energy generation is positively linked with new energy consumption, whereas energy prices and carbon emissions have a negative and significant impact on new energy consumption. In the short run, economic growth can promote the growth of new energy consumption. However, this positive effect is gradually formed and is unlikely to happen soon. However, whether the impact of industrial structure optimization on new energy consumption is a long- or short-run estimate is not significant. Causality results suggest that a one-way Granger causality exists between each factor and new energy consumption in different lag orders, except for industrial structure. Re-examining the energy price mechanism and carbon emission mechanism policy, maintaining stable GDP growth, increasing the installed capacity of new energy power generation, and improving power generation conversion efficiency are vital for ensuring new energy development.

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Section: Carbon Emissionsmentioning

confidence: 99%

Section: Internal Energy Price Relative Indexmentioning

confidence: 99%

Influencing Factors of New Energy Development in China: Based on ARDL Cointegration and Granger Causality Analysis

2021

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“…Additionally, some argued that China’s ETS also promoted carbon intensity reduction [ 33 ], but Zhang et al (2019) [ 34 ] found that only in some pilot areas (e.g., Beijing and Guangdong) ETS decreased carbon emission intensity. Existing studies also stated that the implementation of China’s ETS can reduce energy consumption and intensity [ 31 ], boost new energy use [ 35 ], and influence technological innovation [ 36 , 37 ] and green development efficiency [ 38 ].…”

Section: Literature Reviewmentioning

confidence: 99%

Does Emission Trading Boost Carbon Productivity? Evidence from China’s Pilot Emission Trading Scheme

Zhou

Liang

Zhou

et al. 2020

IJERPH

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As the country with the largest carbon emissions globally, the effective operation of China’s carbon emissions trading scheme (ETS) is of great importance to the global community in terms of mitigating climate change. This paper considers China’s pilot ETS launched in 2013 as a quasi-natural experiment. Exploring provincial industrial-level data that are more in line with the ETS coverage, the difference-in-difference-in-difference (DDD) model is used to evaluate the impact of the ETS on carbon productivity. Considering different pilot regions and industries, we also analyze the heterogeneous effect of ETS. Moreover, the mediating effects of technical progress and capital investment are explored. We find that China’s pilot ETS boosted carbon productivity. Among pilot regions, the best policy effectiveness appeared in Beijing, while the weakest effectiveness appeared in Chongqing. Among the pilot industries, the pilot ETS had better effectiveness in petrochemical and electric power industries and weaker effectiveness in building materials and transportation industries. Additionally, the pilot ETS promoted carbon productivity through both technological progress and capital investment, and the former contributed more. Our findings can provide empirical references and policy implications for nationwide implementation of ETS to further promote low-carbon economic transformation.

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“…Fang et al studied the impact of carbon trading on new energy. The results show that under certain conditions, carbon trading can promote the development of new energy, and mature carbon trading can effectively control carbon emissions and energy intensity [11]. Woo et al investigated the impact of carbon trading on the real-time power market price in California.…”

Section: Carbon Tax and Carbon Trading Policiesmentioning

confidence: 99%

The Impact of Retailers’ Low-Carbon Investment on the Supply Chain under Carbon Tax and Carbon Trading Policies

2020

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In the current low-carbon economy, the government has adopted carbon taxes and carbon trading policies to control the carbon emissions of manufacturers. As consumers become increasingly aware of low-carbon, some retailers have also started investing in low-carbon to shape their public image and increase their competitiveness to attract more customers. In this paper, the Stackelberg game method is utilized to solve the model, and the graphs are used to analyze the benefits of retailers' low-carbon investment on the supply chain through numerical analysis. It is found that when the emission reduction cost coefficient of manufacturers is relatively low, manufacturers are willing to reduce carbon emissions. At this time, increasing carbon tax and the carbon emission permits price can effectively promote the emission reduction behavior of manufacturers, because it increases demand for products and the profit of manufacturers and retailers. However, when the emission reduction cost coefficient of the manufacturers is quite high, increasing carbon tax and carbon emission permits price cannot effectively promote the emission reduction behavior, because this situation of the emission reduction reduces the profit of manufacturers. The main contribution of this paper discovers that the green cost coefficient of retailers' low-carbon investment will adjust the impact of the carbon tax and the carbon trading price on the profits of retailers and manufacturers which proves that retailers’ low-carbon investment is beneficial to the supply chain. When the emission reduction cost coefficient is high and the green cost coefficient is low, increasing the carbon tax or carbon emission permits price can increase the profit of manufacturers and retailers. Finally, we design a supply chain coordination of comprehensive sharing contact for retailers and manufacturers. The result shows that this contract has economic and environmental benefits, and that it is beneficial for the environment and economy of sustainable development.

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Research on the influence mechanism of carbon trading on new energy—A case study of ESER system for China

Cited by 28 publications

References 35 publications

Influencing Factors of New Energy Development in China: Based on ARDL Cointegration and Granger Causality Analysis

Influencing Factors of New Energy Development in China: Based on ARDL Cointegration and Granger Causality Analysis

Does Emission Trading Boost Carbon Productivity? Evidence from China’s Pilot Emission Trading Scheme

The Impact of Retailers’ Low-Carbon Investment on the Supply Chain under Carbon Tax and Carbon Trading Policies

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