Pricing climate risk: policy signals and carbon emissions
気候リスクの価格付け：政策シグナルと炭素排出 (AI 翻訳)
Marina Albanese, Ida Colella
🤖 gxceed AI 要約
日本語
本研究は、気候政策、CO2排出量、欧州株式市場リターンの動的関係を検証する。28カ国（2007-2024年）のパネルデータを用い、局所投影法と閾値モデルにより、排出量と株式リターンの関係が政策の厳格性に依存することを示す。低政策環境では排出量とリターンは正の関係、高政策環境では負の関係となる。気候政策の変化は概ね正の株式市場反応と関連する。
English
This study examines the dynamic association between climate policy, CO2 emissions, and European stock returns using a panel of 28 countries (2007-2024) with local projections and a threshold model. It finds that CO2 emissions are positively associated with stock returns in low-policy regimes but negatively in high-policy regimes, while changes in climate policy are generally positively associated with stock returns. The findings highlight regime-dependent pricing of climate risk.
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
欧州のデータに基づくが、政策の厳格性に応じて排出権価格が株式リターンに与える影響が異なることを示しており、日本のカーボンプライシングや移行リスク評価にも示唆を与える。投資家や政策立案者は、排出強度と規制の厳格性の相互作用を考慮すべきである。
In the global GX context
This paper contributes to the global understanding of transition risk pricing by showing that the relationship between emissions and stock returns is regime-dependent on policy stringency. It reinforces the importance of credible climate policy for financial stability, relevant for ISSB and TCFD frameworks.
👥 読者別の含意
🔬研究者:Provides novel evidence of regime-dependent climate risk pricing using a threshold local projections framework.
🏢実務担当者:Inform portfolio construction by considering how policy regimes affect the relationship between emission exposure and stock returns.
🏛政策担当者:Highlights that the credibility and stringency of climate policy shape how markets price transition risks.
📄 Abstract（原文）
Purpose This study examines the dynamic association between Climate Policy, CO2 Emissions and European stock market returns. While the existing literature offers mixed evidence regarding the pricing of climate risk, we investigate whether these associations are regime-dependent and differ across levels of climate exposure. Design/methodology/approach Using an annual panel of 28 European countries spanning 2007–2024, we estimate dynamic conditional associations using a local projections framework (Jordà, 2005, 2023) to assess the dynamic responses of stock returns to changes in climate-related variables. We then combine the threshold model of Seo and Shin (2016) with the local projection framework by estimating the benchmark model within each regime, to capture endogenous regime shifts in climate risk exposure. Finally, we conduct robustness checks on the baseline specification adding alternative macroeconomic controls and sample restrictions. Findings The threshold estimation provides strong evidence of regime dependence. In particular, the pricing of CO2 emissions in stock returns depends critically on the level of climate policy stringency. Emissions are positively associated with stock returns in low-policy environments but are negatively associated in high-policy regimes. In contrast, changes in climate policy are generally associated with positive stock market responses. Research limitations/implications The reliance on aggregate market indices limits our ability to assess how firm-level characteristics shape exposure to transition risk. A more granular analysis based on individual stock data could yield deeper insights, particularly with respect to portfolio diversification. Practical implications The findings highlight that the pricing of climate risk is shaped by policy credibility. Investors and policymakers should account for the interaction between emission intensity and regulatory stringency when assessing financial stability and transition risks. Originality/value This study provides novel evidence of regime-dependent and dynamic associations between climate risks and European stock markets by integrating local projections with an endogenous dynamic panel threshold framework.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1108/jes-03-2026-0251first seen 2026-07-15 05:10:51
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