{"title":"Heterogeneity of regional carbon emission markets in China: Evidence from multidimensional determinants","authors":"Xiyong Dong , John F. Zhang","doi":"10.1016/j.eneco.2024.107835","DOIUrl":null,"url":null,"abstract":"<div><p>The Chinese carbon markets are heterogeneously distributed with different regional economies and natural resource endowments. This paper examines how carbon prices behave across regional emission markets in China using the dynamic model averaging (DMA) approach. The results show that the Beijing, Guangdong, and Hubei markets are increasingly affected by various factors. In contrast, the Shanghai market gradually becomes less affected after 2020, both in the current and forecast periods. Moreover, geopolitical risk and new energy price are important variables for the concurrent relation, and domestic oil price and geopolitical risk are important variables for predicting carbon prices. Nevertheless, there are significant differences in intensity and signs among the four carbon markets affected by various factors, as well as large differences between the results for the current and forecast periods. These results indicate the heterogeneity of regional carbon markets; therefore, caution should be taken when using a single carbon market to represent the entire Chinese market.</p></div>","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"138 ","pages":"Article 107835"},"PeriodicalIF":13.6000,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Energy Economics","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0140988324005437","RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0
Abstract
The Chinese carbon markets are heterogeneously distributed with different regional economies and natural resource endowments. This paper examines how carbon prices behave across regional emission markets in China using the dynamic model averaging (DMA) approach. The results show that the Beijing, Guangdong, and Hubei markets are increasingly affected by various factors. In contrast, the Shanghai market gradually becomes less affected after 2020, both in the current and forecast periods. Moreover, geopolitical risk and new energy price are important variables for the concurrent relation, and domestic oil price and geopolitical risk are important variables for predicting carbon prices. Nevertheless, there are significant differences in intensity and signs among the four carbon markets affected by various factors, as well as large differences between the results for the current and forecast periods. These results indicate the heterogeneity of regional carbon markets; therefore, caution should be taken when using a single carbon market to represent the entire Chinese market.
期刊介绍:
Energy Economics is a field journal that focuses on energy economics and energy finance. It covers various themes including the exploitation, conversion, and use of energy, markets for energy commodities and derivatives, regulation and taxation, forecasting, environment and climate, international trade, development, and monetary policy. The journal welcomes contributions that utilize diverse methods such as experiments, surveys, econometrics, decomposition, simulation models, equilibrium models, optimization models, and analytical models. It publishes a combination of papers employing different methods to explore a wide range of topics. The journal's replication policy encourages the submission of replication studies, wherein researchers reproduce and extend the key results of original studies while explaining any differences. Energy Economics is indexed and abstracted in several databases including Environmental Abstracts, Fuel and Energy Abstracts, Social Sciences Citation Index, GEOBASE, Social & Behavioral Sciences, Journal of Economic Literature, INSPEC, and more.