2022
DOI: 10.3390/su142113806
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Impact of Changes in Membership on Prices of a Unified Carbon Market: Case Study of the European Union Emissions Trading System

Abstract: Using the event study methodology, the paper studies the effects of 22 key events in countries’ process of entering and exiting the European Union on returns of European Union Allowance (EUA) future prices in the EU Emissions Trading System (EU ETS). The events include 17 entry events concerning the signing of relevant agreements, becoming a candidate or potential candidate country, the process of a negotiation and formally entering the EU, and five exit events including the process of Brexit and the suspensio… Show more

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Cited by 4 publications
(2 citation statements)
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“…Furthermore, the EUA price is rather volatile, with an interdependence with energy (coal, oil, natural gas, and electricity prices), economic (industrial production, economic sentiment, bank lending), and temperature variables [35]. However, the EUA price is vulnerable to unforeseen market shocks, such as the Brexit announcement, which had considerable adverse effects [36] on the market. Furthermore, when shocks occur, the EUA price shows a high responsiveness to its previous price [35].…”
Section: Key Provisions Of the Eu Legislative Frameworkmentioning
confidence: 99%
“…Furthermore, the EUA price is rather volatile, with an interdependence with energy (coal, oil, natural gas, and electricity prices), economic (industrial production, economic sentiment, bank lending), and temperature variables [35]. However, the EUA price is vulnerable to unforeseen market shocks, such as the Brexit announcement, which had considerable adverse effects [36] on the market. Furthermore, when shocks occur, the EUA price shows a high responsiveness to its previous price [35].…”
Section: Key Provisions Of the Eu Legislative Frameworkmentioning
confidence: 99%
“…With the establishment of the EU-ETS, for the first time, a carbon trading price was established in Europe. Most studies on carbon prices have focused on predicting carbon prices [15][16][17][18] and their influencing factors [19][20][21]. For example, Yan made a hybrid model of carbon price prediction based on feature selection and multi-objective optimization algorithms, setting up models with lower errors [22].…”
Section: Studies Related To Carbon Trading Pricesmentioning
confidence: 99%