Ruo-Yang Pu , Qiao-Mei Liang , Yi-Ming Wei , Song-Yang Yan , Xiang-Yu Wang , De-Hua Li , Chen Yi , Chang-Jing Ji
{"title":"中国新能源市场对碳价格波动风险的影响:来自七个试点碳市场的证据","authors":"Ruo-Yang Pu , Qiao-Mei Liang , Yi-Ming Wei , Song-Yang Yan , Xiang-Yu Wang , De-Hua Li , Chen Yi , Chang-Jing Ji","doi":"10.1016/j.esr.2025.101718","DOIUrl":null,"url":null,"abstract":"<div><div>Since China implemented its carbon trading mechanism, trading risks arising from unstable carbon prices have significantly reduced its emission-reduction efficiency. Unlike traditional research, which focuses on the impact of fossil fuels on carbon prices, this study emphasises risk spillovers from new energy markets amidst large-scale renewable energy deployment. Moreover, to address subjectivity in variable selection and overfitting issues in carbon price determinants, the LASSO algorithm is integrated with the multivariate GARCH model. Using daily carbon quota prices from seven Chinese pilot markets (2014–2022), factors driving carbon price volatility are systematically identified, and the heterogeneous influence of new energy markets on carbon market risks is rigorously analysed. The results indicate that new energy market volatility significantly contributes to carbon price fluctuations. A 1 % increase in the CNI New Energy Index induces co-movement in carbon prices: Hubei (+0.08 %), Beijing (+0.01 %) and Shenzhen (+0.06 %), while Shanghai exhibits inverse sensitivity (−0.19 %). Prices in Guangdong, Tianjin and Chongqing show minimal responsiveness. Additionally, the correlation between new energy markets and carbon markets exhibits temporal heterogeneity. Furthermore, the asymmetric leverage effect suggests that negative news in new energy markets has a more significant impact on carbon markets than positive news. This study advances theoretical understanding of carbon price dynamics and offers practical insights for enhancing risk management frameworks in emissions trading systems.</div></div>","PeriodicalId":11546,"journal":{"name":"Energy Strategy Reviews","volume":"59 ","pages":"Article 101718"},"PeriodicalIF":7.9000,"publicationDate":"2025-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Impact of the China's new energy market on carbon price fluctuation risk: Evidence from seven pilot carbon markets\",\"authors\":\"Ruo-Yang Pu , Qiao-Mei Liang , Yi-Ming Wei , Song-Yang Yan , Xiang-Yu Wang , De-Hua Li , Chen Yi , Chang-Jing Ji\",\"doi\":\"10.1016/j.esr.2025.101718\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Since China implemented its carbon trading mechanism, trading risks arising from unstable carbon prices have significantly reduced its emission-reduction efficiency. Unlike traditional research, which focuses on the impact of fossil fuels on carbon prices, this study emphasises risk spillovers from new energy markets amidst large-scale renewable energy deployment. Moreover, to address subjectivity in variable selection and overfitting issues in carbon price determinants, the LASSO algorithm is integrated with the multivariate GARCH model. Using daily carbon quota prices from seven Chinese pilot markets (2014–2022), factors driving carbon price volatility are systematically identified, and the heterogeneous influence of new energy markets on carbon market risks is rigorously analysed. The results indicate that new energy market volatility significantly contributes to carbon price fluctuations. A 1 % increase in the CNI New Energy Index induces co-movement in carbon prices: Hubei (+0.08 %), Beijing (+0.01 %) and Shenzhen (+0.06 %), while Shanghai exhibits inverse sensitivity (−0.19 %). Prices in Guangdong, Tianjin and Chongqing show minimal responsiveness. Additionally, the correlation between new energy markets and carbon markets exhibits temporal heterogeneity. Furthermore, the asymmetric leverage effect suggests that negative news in new energy markets has a more significant impact on carbon markets than positive news. This study advances theoretical understanding of carbon price dynamics and offers practical insights for enhancing risk management frameworks in emissions trading systems.</div></div>\",\"PeriodicalId\":11546,\"journal\":{\"name\":\"Energy Strategy Reviews\",\"volume\":\"59 \",\"pages\":\"Article 101718\"},\"PeriodicalIF\":7.9000,\"publicationDate\":\"2025-04-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Energy Strategy Reviews\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2211467X25000811\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENERGY & FUELS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Energy Strategy Reviews","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2211467X25000811","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
Impact of the China's new energy market on carbon price fluctuation risk: Evidence from seven pilot carbon markets
Since China implemented its carbon trading mechanism, trading risks arising from unstable carbon prices have significantly reduced its emission-reduction efficiency. Unlike traditional research, which focuses on the impact of fossil fuels on carbon prices, this study emphasises risk spillovers from new energy markets amidst large-scale renewable energy deployment. Moreover, to address subjectivity in variable selection and overfitting issues in carbon price determinants, the LASSO algorithm is integrated with the multivariate GARCH model. Using daily carbon quota prices from seven Chinese pilot markets (2014–2022), factors driving carbon price volatility are systematically identified, and the heterogeneous influence of new energy markets on carbon market risks is rigorously analysed. The results indicate that new energy market volatility significantly contributes to carbon price fluctuations. A 1 % increase in the CNI New Energy Index induces co-movement in carbon prices: Hubei (+0.08 %), Beijing (+0.01 %) and Shenzhen (+0.06 %), while Shanghai exhibits inverse sensitivity (−0.19 %). Prices in Guangdong, Tianjin and Chongqing show minimal responsiveness. Additionally, the correlation between new energy markets and carbon markets exhibits temporal heterogeneity. Furthermore, the asymmetric leverage effect suggests that negative news in new energy markets has a more significant impact on carbon markets than positive news. This study advances theoretical understanding of carbon price dynamics and offers practical insights for enhancing risk management frameworks in emissions trading systems.
期刊介绍:
Energy Strategy Reviews is a gold open access journal that provides authoritative content on strategic decision-making and vision-sharing related to society''s energy needs.
Energy Strategy Reviews publishes:
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And by invitation:
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