Risk Spillover of Energy-Related Systems Under a Carbon Neutral Target
Under the background of climate change, the risk spillover within the energy system is constantly intensifying. Clarifying the coupling relationship between entities within the energy system can help policymakers propose more reasonable policy measures and strengthen risk prevention. To estimate the...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-07-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/18/13/3515 |
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| _version_ | 1849319906532655104 |
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| author | Fei Liu Honglin Yao Yanan Chen Xingbei Song Yihang Zhao Sen Guo |
| author_facet | Fei Liu Honglin Yao Yanan Chen Xingbei Song Yihang Zhao Sen Guo |
| author_sort | Fei Liu |
| collection | DOAJ |
| description | Under the background of climate change, the risk spillover within the energy system is constantly intensifying. Clarifying the coupling relationship between entities within the energy system can help policymakers propose more reasonable policy measures and strengthen risk prevention. To estimate the risk spillover of energy-related systems, this paper constructs five subsystems: the fossil fuel subsystem, the electricity subsystem, the green bond subsystem, the renewable energy subsystem, and the carbon subsystem. Then, a quantitative risk analysis is conducted on two major energy consumption/carbon emission entities, China and Europe, based on the DCC-GARCH-CoVaR method. The result shows that (1) Markets of the same type often have more significant dynamic correlations. Of these, the average dynamic correlation coefficient of GBI-CABI (the Chinese green bond subsystem) and FR-DE (the European electricity subsystem) are the largest, by 0.8552 and 0.7347. (2) The high correlation between energy markets results in serious risk contagion, and the overall risk spillover effect within the European energy system is about 2.6 times that within the Chinese energy system. Of these, EUA and CABI are the main risk connectors of each energy system. |
| format | Article |
| id | doaj-art-053cbaf351e846b2b5ceaa0bb176c596 |
| institution | Kabale University |
| issn | 1996-1073 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj-art-053cbaf351e846b2b5ceaa0bb176c5962025-08-20T03:50:17ZengMDPI AGEnergies1996-10732025-07-011813351510.3390/en18133515Risk Spillover of Energy-Related Systems Under a Carbon Neutral TargetFei Liu0Honglin Yao1Yanan Chen2Xingbei Song3Yihang Zhao4Sen Guo5State Grid Zhejiang Electric Power Co., Ltd., Construction Company, Hangzhou 310016, ChinaState Grid Zhejiang Electric Power Co., Ltd., Construction Company, Hangzhou 310016, ChinaState Grid Zhejiang Electric Power Co., Ltd., Construction Company, Hangzhou 310016, ChinaState Grid Zhejiang Electric Power Co., Ltd., Construction Company, Hangzhou 310016, ChinaCEC Technical & Economic Consulting Center of Power Construction, Electric Power Development Research Institute Co., Ltd., Beijing 100053, ChinaSchool of Economics and Management, North China Electric Power University, Beijing 102206, ChinaUnder the background of climate change, the risk spillover within the energy system is constantly intensifying. Clarifying the coupling relationship between entities within the energy system can help policymakers propose more reasonable policy measures and strengthen risk prevention. To estimate the risk spillover of energy-related systems, this paper constructs five subsystems: the fossil fuel subsystem, the electricity subsystem, the green bond subsystem, the renewable energy subsystem, and the carbon subsystem. Then, a quantitative risk analysis is conducted on two major energy consumption/carbon emission entities, China and Europe, based on the DCC-GARCH-CoVaR method. The result shows that (1) Markets of the same type often have more significant dynamic correlations. Of these, the average dynamic correlation coefficient of GBI-CABI (the Chinese green bond subsystem) and FR-DE (the European electricity subsystem) are the largest, by 0.8552 and 0.7347. (2) The high correlation between energy markets results in serious risk contagion, and the overall risk spillover effect within the European energy system is about 2.6 times that within the Chinese energy system. Of these, EUA and CABI are the main risk connectors of each energy system.https://www.mdpi.com/1996-1073/18/13/3515risk spilloverdynamic correlationenergy systemmarket price fluctuationDCC-GARCH-CoVaRcarbon neutral target |
| spellingShingle | Fei Liu Honglin Yao Yanan Chen Xingbei Song Yihang Zhao Sen Guo Risk Spillover of Energy-Related Systems Under a Carbon Neutral Target Energies risk spillover dynamic correlation energy system market price fluctuation DCC-GARCH-CoVaR carbon neutral target |
| title | Risk Spillover of Energy-Related Systems Under a Carbon Neutral Target |
| title_full | Risk Spillover of Energy-Related Systems Under a Carbon Neutral Target |
| title_fullStr | Risk Spillover of Energy-Related Systems Under a Carbon Neutral Target |
| title_full_unstemmed | Risk Spillover of Energy-Related Systems Under a Carbon Neutral Target |
| title_short | Risk Spillover of Energy-Related Systems Under a Carbon Neutral Target |
| title_sort | risk spillover of energy related systems under a carbon neutral target |
| topic | risk spillover dynamic correlation energy system market price fluctuation DCC-GARCH-CoVaR carbon neutral target |
| url | https://www.mdpi.com/1996-1073/18/13/3515 |
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