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<span class="word">The <span class="word">Minimum <span class="word">Effective <span class="word">Carbon <span class="word">Price: <span class="word">Threshold <span class="word">Effects <span class="word">in <span class="word">the <span class="word allCaps">EU <span class="word allCaps">ETS–<span class="word">Renewable <span class="word">Energy <span class="word">Nexus

最低有効炭素価格:EU ETSと再生可能エネルギーの関係における閾値効果 (AI 翻訳)

Tomasz Wolowieс, Oksana Liashenko, Kostiantyn Pavlov, Olena Pavlova, Sylwester Bogacki, Sylwia Skrzypek-Ahmed, Andrii Dukhnevych

Crossrefプレプリント2026-02-09#炭素価格Origin: EU
DOI: 10.20944/preprints202602.0551.v1
原典: https://doi.org/10.20944/preprints202602.0551.v1

🤖 gxceed AI 要約

日本語

本研究は2005-2024年のEU ETSデータを用い、炭素価格と再エネ消費の閾値効果を分析。€20.71/tCO2の統計的有意な閾値を発見し、それを下回ると炭素価格は再エネ促進効果を持たず、上回ると1ユーロ増加ごとに7.20TWhの追加消費が生じることを示した。太陽光発電が特に敏感で、市場安定化準備制度の有効性を裏付ける。

English

This study applies Hansen threshold regression to EU ETS carbon prices and renewable energy consumption (2005-2024), identifying a significant threshold at €20.71/tCO2. Below this, carbon prices have no positive effect on renewables; above it, each additional euro is associated with 7.20 TWh more renewable consumption. Solar electricity shows the strongest response, supporting carbon price floor mechanisms.

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

📝 gxceed 編集解説 — Why this matters

日本のGX文脈において

欧州の経験は日本が導入を検討するカーボンプライシングの設計に示唆を与える。閾値の存在は、十分な水準を設定しないと効果が乏しいことを示し、日本における炭素価格の水準設定や市場安定化策の重要性を示唆する。

In the global GX context

This paper provides empirical evidence for carbon price thresholds in the EU ETS, supporting the case for price floors and market stability reserves. It informs global carbon market design, particularly for emerging ETS systems, by demonstrating the minimum price needed to drive renewable investment.

👥 読者別の含意

🔬研究者:Threshold regression method and empirical findings on carbon price effectiveness contribute to carbon pricing literature.

🏢実務担当者:Corporate sustainability teams can use the identified threshold to assess when carbon costs may materially impact renewable energy investment decisions.

🏛政策担当者:Regulators designing carbon markets should consider implementing price floor mechanisms above the identified threshold to ensure emissions trading drives renewable energy deployment.

📄 Abstract(原文)

The European Union Emissions Trading System (EU ETS) has experienced dramatic price fluctuations since its 2005 inception, raising questions about whether carbon pricing effectiveness exhibits threshold behaviour—specifically, whether there exists a minimum carbon price level below which market signals fail to stimulate renewable energy investment. This study applies the Hansen threshold regression methodology to investigate regime-dependent dynamics in the relationship between EU ETS carbon prices and renewable energy consumption over 2005–2024. We identify a statistically significant threshold at €20.71/tCO2 (bootstrap p = 0.048), which partitions the sample into distinct low- and high-price regimes. Below this threshold, carbon prices exhibit no significant positive effect on renewable deployment (β1 = −36.16, p = 0.246); above the threshold, a positive relationship emerges (β2 = +7.20, p = 0.081), with each additional euro associated with 7.20 TWh of additional renewable consumption. Technol-ogy-specific analysis reveals that solar electricity exhibits particularly strong respon-siveness to above-threshold carbon prices (β2 = +1.71, p = 0.019). The threshold estimate is robust to alternative trimming specifications, functional forms, and outlier exclusion. These findings suggest that the EU ETS achieved effectiveness as a driver of renewable energy only after carbon prices exceeded approximately €21/tCO2—a transformation that coincided with the implementation of the Market Stability Reserve. The results provide empirical support for carbon price floor mechanisms and validate structural reforms aimed at strengthening the credibility of the carbon market.

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gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。