{"title":"政策不确定性、地缘政治风险与中国碳中和","authors":"Liping Liu, Zheng Lü","doi":"10.1080/17583004.2023.2251929","DOIUrl":null,"url":null,"abstract":"Abstract In the present study, it was explored how the volatility of the carbon neutrality concept index (CNCI) was affected by China economic policy uncertainty (CEPU) index, climate policy uncertainty (CPU) index, and geopolitical risk (GPR) index. According to the research of Amendola et al. the GARCH-MIDAS model was improved by introducing the realized kernel volatility of China stock market into the short-term volatility component. On this basis, the GARCH-RKV-MIDAS model was constructed. Meanwhile, both GARCH-MIDAS and GARCH-RKV-MIDAS models were applied to identify the influencing factors for CNCI volatility during the period between January 2018 and June 2022, with CNCI predicted. According to the research results, both the CPU index and the GPR index exert a significant effect on the long-term volatility of CNCI, despite no significant difference made by the CEPU index to the long-term volatility of CNCI. As for the prediction of CNCI volatility, the GARCH-RKV-MIDAS model clearly outperforms the GARCH-MIDAS model. Moreover, the CPU index outperforms the GPR index and the CEPU index in predicting the volatility of the CNCI.","PeriodicalId":48941,"journal":{"name":"Carbon Management","volume":" ","pages":""},"PeriodicalIF":2.8000,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Policy uncertainty, geopolitical risks and China’s carbon neutralization\",\"authors\":\"Liping Liu, Zheng Lü\",\"doi\":\"10.1080/17583004.2023.2251929\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract In the present study, it was explored how the volatility of the carbon neutrality concept index (CNCI) was affected by China economic policy uncertainty (CEPU) index, climate policy uncertainty (CPU) index, and geopolitical risk (GPR) index. According to the research of Amendola et al. the GARCH-MIDAS model was improved by introducing the realized kernel volatility of China stock market into the short-term volatility component. On this basis, the GARCH-RKV-MIDAS model was constructed. Meanwhile, both GARCH-MIDAS and GARCH-RKV-MIDAS models were applied to identify the influencing factors for CNCI volatility during the period between January 2018 and June 2022, with CNCI predicted. According to the research results, both the CPU index and the GPR index exert a significant effect on the long-term volatility of CNCI, despite no significant difference made by the CEPU index to the long-term volatility of CNCI. As for the prediction of CNCI volatility, the GARCH-RKV-MIDAS model clearly outperforms the GARCH-MIDAS model. Moreover, the CPU index outperforms the GPR index and the CEPU index in predicting the volatility of the CNCI.\",\"PeriodicalId\":48941,\"journal\":{\"name\":\"Carbon Management\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":2.8000,\"publicationDate\":\"2023-08-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Carbon Management\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://doi.org/10.1080/17583004.2023.2251929\",\"RegionNum\":4,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Carbon Management","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.1080/17583004.2023.2251929","RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Policy uncertainty, geopolitical risks and China’s carbon neutralization
Abstract In the present study, it was explored how the volatility of the carbon neutrality concept index (CNCI) was affected by China economic policy uncertainty (CEPU) index, climate policy uncertainty (CPU) index, and geopolitical risk (GPR) index. According to the research of Amendola et al. the GARCH-MIDAS model was improved by introducing the realized kernel volatility of China stock market into the short-term volatility component. On this basis, the GARCH-RKV-MIDAS model was constructed. Meanwhile, both GARCH-MIDAS and GARCH-RKV-MIDAS models were applied to identify the influencing factors for CNCI volatility during the period between January 2018 and June 2022, with CNCI predicted. According to the research results, both the CPU index and the GPR index exert a significant effect on the long-term volatility of CNCI, despite no significant difference made by the CEPU index to the long-term volatility of CNCI. As for the prediction of CNCI volatility, the GARCH-RKV-MIDAS model clearly outperforms the GARCH-MIDAS model. Moreover, the CPU index outperforms the GPR index and the CEPU index in predicting the volatility of the CNCI.
期刊介绍:
Carbon Management is a scholarly peer-reviewed forum for insights from the diverse array of disciplines that enhance our understanding of carbon dioxide and other GHG interactions – from biology, ecology, chemistry and engineering to law, policy, economics and sociology.
The core aim of Carbon Management is it to examine the options and mechanisms for mitigating the causes and impacts of climate change, which includes mechanisms for reducing emissions and enhancing the removal of GHGs from the atmosphere, as well as metrics used to measure performance of options and mechanisms resulting from international treaties, domestic policies, local regulations, environmental markets, technologies, industrial efforts and consumer choices.
One key aim of the journal is to catalyse intellectual debate in an inclusive and scientific manner on the practical work of policy implementation related to the long-term effort of managing our global GHG emissions and impacts. Decisions made in the near future will have profound impacts on the global climate and biosphere. Carbon Management delivers research findings in an accessible format to inform decisions in the fields of research, education, management and environmental policy.