{"title":"The rise of clean energy markets: Evidence from frequency-domain spillover effects between critical metals and energy markets","authors":"Yongguang Zhu, Yuna Gong, Lanyong Yang, Deyi Xu","doi":"10.1016/j.eneco.2024.108126","DOIUrl":null,"url":null,"abstract":"This study investigates the dynamic volatility spillovers among critical metals, traditional energy, and clean energy markets using a sophisticated frequency-domain approach. Leveraging the improved complete ensemble empirical mode decomposition with adaptive noise and time-varying parameter vector autoregression models, we decompose daily logarithmic returns into high, middle, and low-frequency components. Our findings reveal significant heterogeneity in spillover effects across different frequencies, industries, and commodity categories. Clean energy sectors emerge as prominent contributors to market spillovers, reflecting their increasing sensitivity to short-term market dynamics. In contrast, traditional energy markets transition from being spillover sources to net recipients as the energy transition accelerates. Critical metals, particularly lithium and platinum, play a dominant role in long-term market integration, highlighting their growing importance in the global energy transition. These results provide actionable insights for policymakers and investors seeking to manage risks and optimize strategies in the evolving energy landscape.","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"14 1","pages":""},"PeriodicalIF":13.6000,"publicationDate":"2024-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Energy Economics","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.1016/j.eneco.2024.108126","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
This study investigates the dynamic volatility spillovers among critical metals, traditional energy, and clean energy markets using a sophisticated frequency-domain approach. Leveraging the improved complete ensemble empirical mode decomposition with adaptive noise and time-varying parameter vector autoregression models, we decompose daily logarithmic returns into high, middle, and low-frequency components. Our findings reveal significant heterogeneity in spillover effects across different frequencies, industries, and commodity categories. Clean energy sectors emerge as prominent contributors to market spillovers, reflecting their increasing sensitivity to short-term market dynamics. In contrast, traditional energy markets transition from being spillover sources to net recipients as the energy transition accelerates. Critical metals, particularly lithium and platinum, play a dominant role in long-term market integration, highlighting their growing importance in the global energy transition. These results provide actionable insights for policymakers and investors seeking to manage risks and optimize strategies in the evolving energy landscape.
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.