Energy Economics最新文献

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Nonlinear temperature sensitivity of residential electricity demand: Evidence from a distributional regression approach 住宅用电需求的非线性温度敏感性：来自分布回归方法的证据

IF 14.2 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2025-11-29 DOI: 10.1016/j.eneco.2025.109076

Kyungsik Nam , Won-Ki Seo

We estimate the temperature sensitivity of residential electricity demand during extreme temperature events using the distribution-to-scalar regression model. Rather than relying on simple averages or individual quantile statistics of raw temperature data, we construct distributional summaries — such as probability density, hazard rate, and quantile functions — to retain a more comprehensive representation of temperature variation. This approach not only utilizes richer information from the underlying temperature distribution but also enables the examination of extreme temperature effects that conventional models fail to capture. Additionally, recognizing that distribution functions are typically estimated from limited discrete observations and may be subject to measurement errors, our econometric framework explicitly addresses this issue. Empirical findings from the hazard-to-demand model indicate that residential electricity demand exhibits a stronger nonlinear response to cold waves than to heat waves, while heat wave shocks demonstrate a more pronounced incremental effect. Moreover, the temperature quantile-to-demand model produces largely insignificant demand response estimates, attributed to the offsetting influence of two counteracting forces.

利用分布-标量回归模型估计了极端温度事件中居民用电需求的温度敏感性。我们没有依赖于原始温度数据的简单平均值或单个分位数统计，而是构建了分布摘要——例如概率密度、危险率和分位数函数——以保留更全面的温度变化表示。这种方法不仅利用了来自底层温度分布的更丰富的信息，而且还能够检查常规模式无法捕获的极端温度效应。此外，认识到分布函数通常是从有限的离散观察中估计的，并且可能受到测量误差的影响，我们的计量经济学框架明确地解决了这个问题。危害-需求模型的实证结果表明，居民用电需求对寒潮的非线性响应强于对热浪的非线性响应，而热浪冲击的增量效应更为明显。此外，温度分位数-需求模型产生的需求响应估计在很大程度上是微不足道的，这归因于两种抵消力的抵消影响。

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引用次数: 0

Trading characteristics of emissions trading scheme and carbon emission reduction efficiency: Evidence from China 排放权交易机制的交易特征与碳减排效率：来自中国的证据

IF 14.2 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2025-11-29 DOI: 10.1016/j.eneco.2025.109072

Jiangyuan Li , Tao Ding , Ruipeng Tan , Liang Liang

Emissions Trading Scheme (ETS) has been widely implemented as a key measure to address climate challenges, yet its efficiency in reducing carbon emissions (CEs) still faces numerous challenges. To promote the development of the global carbon market and enhance CEs reduction efficiency, this study examines the impact of the trading characteristics of China's ETS on its CEs reduction efficiency using sample data from Chinese prefecture-level cities between 2007 and 2019. The baseline regression results indicate that the carbon reduction effect of ETS is associated with trading scale: each million tons of carbon trading volume (CTV) reduces CEs by an average of 1.69 million tons, and each million yuan of carbon trading turnover (CTT) reduces CEs by an average of 0.103 million tons. These findings remain robust across various tests. Mechanism analysis reveals that the ETS drives corporate CEs reduction by increasing liquidity pressure on enterprises and raising their awareness of emission reduction. Further analysis of trading characteristics shows that increased volatility or illiquidity in carbon trading diminishes the carbon reduction effect per unit of CTV and CTT. Additionally, this study identifies a non-trading carbon reduction effect of ETS, with the deterrence effect being a significant source. Further analysis reveals that the CEs reduction effect of CTV and CTT steadily rises over time, with a spillover effect and a hysteresis effect lasting one year. Finally, based on the findings, this study proposes several recommendations to enhance the CEs reduction efficiency of ETS.

碳排放交易体系（ETS）作为应对气候变化的一项重要措施已得到广泛实施，但其在减少碳排放方面的效率仍面临诸多挑战。为了促进全球碳市场的发展，提高碳排放减排效率，本研究利用2007 - 2019年中国地级市的样本数据，考察了中国碳排放交易特征对碳排放减排效率的影响。基线回归结果表明，碳交易体系的碳减排效果与交易规模相关，每百万吨碳交易量（CTV）平均减少碳排放169万吨，每百万元碳交易交易额（CTT）平均减少碳排放10.3万吨。这些发现在各种测试中仍然是强有力的。机制分析表明，ETS通过增加企业的流动性压力和提高企业的减排意识来推动企业碳排放的减少。对碳交易特征的进一步分析表明，碳交易波动性增加或流动性不足会降低单位CTV和CTT的碳减排效果。此外，本研究还发现了碳排放交易体系的非交易性碳减排效应，其中威慑效应是一个重要来源。进一步分析发现，随着时间的推移，CTV和CTT的CEs降低效应稳步上升，并存在持续一年的溢出效应和滞后效应。最后，基于研究结果，本研究提出了提高碳排放交易体系减排效率的几点建议。

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引用次数: 0

Corrigendum to “Transition risk beyond carbon intensity” [Energy Economics Volume 151, (2025), 108913]. “超越碳强度的转型风险”的勘误表[能源经济，（2025），108913]。

IF 14.2 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2025-11-29 DOI: 10.1016/j.eneco.2025.109044

Tatiana Evdokimova, Laurent Millischer

引用次数: 0

Investing in carbon transportation under volume uncertainty and scaling flexibility 在容量不确定性和规模灵活性下投资碳运输

IF 14.2 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2025-11-29 DOI: 10.1016/j.eneco.2025.109064

Sveinung Andersen , Verena Hagspiel , Carlos Oliveira , Jan Magnus Røsbjørgen

The transition to climate neutrality requires significant expansion of carbon capture and storage (CCS) infrastructure. However, uncertainty in CO

_{2}

volumes and prices creates challenges for transport and storage (T&S) operators in determining optimal investment strategies. This study develops a real options analysis (ROA) framework to evaluate investment decisions in large-scale, open-access T&S infrastructure, comparing flexible ship-based transport with cost-effective trunklines. Our results show that, while net present value analysis favors trunklines, ROA demonstrates that ship-based solutions provide greater value due to scalability and shorter lead times. Investment thresholds remain high (400–600 € /tCO

_{2}

), underscoring the need for targeted policy measures to reduce uncertainty and accelerate CCS deployment.

向气候中和的过渡需要大幅扩大碳捕获与封存（CCS）基础设施。然而，二氧化碳量和价格的不确定性给运输和储存运营商在确定最佳投资策略方面带来了挑战。本研究开发了一个实物期权分析（ROA）框架来评估大型开放式运输基础设施的投资决策，并将灵活的船舶运输与具有成本效益的干线进行比较。我们的研究结果表明，虽然净现值分析倾向于干线，但ROA表明，由于可扩展性和更短的交货时间，基于船舶的解决方案提供了更大的价值。投资门槛仍然很高（400-600欧元/吨二氧化碳），强调需要有针对性的政策措施来减少不确定性并加速CCS的部署。

引用次数: 0

Estimating the impact of PM2.5 on solar power with machine learning: Evidence from South Korea 用机器学习估计PM2.5对太阳能发电的影响：来自韩国的证据

IF 14.2 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2025-11-28 DOI: 10.1016/j.eneco.2025.109071

Gordon Euhyun Moon , Moon Joon Kim

This study examines the effect of air pollution on solar photovoltaic (PV) power generation in South Korea, utilizing hourly provincial data from 2017 to 2023. We apply a double/debiased machine learning (DDML) framework to estimate the impact of PM2.5 on solar PV output, addressing potential endogeneity by using wind direction as an instrumental variable. Our results reveal that increased PM2.5 concentrations significantly reduce solar PV generation, with the DDML model showing a larger marginal impact compared to conventional ordinary least squares (OLS) and instrumental variable (IV) methods. Specifically, a 10 % increase in PM2.5 leads to a 4.4 % decline in solar PV output, far exceeding the 0.4 % reduction estimated with OLS and the 3.2 % decline with IV. These findings highlight the limitations of OLS and IV methods in capturing the complex, potentially non-linear relationship between air pollution and PV performance. To address this critical methodological gap, the DDML approach leverages the flexibility of machine learning techniques to offer more robust causal estimates, mitigating biases from functional form misspecification and high-dimensional confounding. Our results indicate that a 1

μ

m^{3}

increase in hourly average PM2.5 leads to substantial economic losses in the solar sector, estimated at 0.53 million USD per year. These findings highlight the significant economic benefits of policies aimed at reducing air pollution, as cleaner air can enhance the efficiency of renewable energy systems and support the transition to a sustainable energy future.

本研究利用2017年至2023年的每小时省级数据，考察了空气污染对韩国太阳能光伏发电的影响。我们采用双/去偏机器学习（DDML）框架来估计PM2.5对太阳能光伏输出的影响，通过使用风向作为工具变量来解决潜在的内生性问题。我们的研究结果表明，PM2.5浓度的增加显著减少了太阳能光伏发电，与传统的普通最小二乘（OLS）和工具变量（IV）方法相比，DDML模型显示出更大的边际影响。具体来说，PM2.5增加10%导致太阳能光伏产量下降4.4%，远远超过OLS估计的0.4%和IV估计的3.2%。这些发现突出了OLS和IV方法在捕捉空气污染与光伏性能之间复杂的、潜在的非线性关系方面的局限性。为了解决这一关键的方法差距，DDML方法利用机器学习技术的灵活性来提供更稳健的因果估计，减轻功能形式规格错误和高维混淆带来的偏差。我们的研究结果表明，每小时平均PM2.5增加1μg/m3，就会给太阳能行业带来巨大的经济损失，估计每年损失53万美元。这些发现强调了旨在减少空气污染的政策的重大经济效益，因为更清洁的空气可以提高可再生能源系统的效率，并支持向可持续能源未来的过渡。

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引用次数: 0

Beyond the linear: Green technology innovation, moderators, and global value chain upgrading 超越线性：绿色技术创新、调节因子与全球价值链升级

IF 14.2 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2025-11-28 DOI: 10.1016/j.eneco.2025.109074

Jihong Duan , Yan Li , Wenming Shi , Kaiyao Wu

This study examines the non-linear impact of green technology innovation (GTI) on the global value chain (GVC) position of China's manufacturing industry. To this end, the moderating roles of environmental regulation and absorptive capacity are considered. Using innovative indicators based on Patent Cooperation Treaty data for the GTI and Wang-Wei-Yu-Zhu-Koopman-Wang-Wei framework for the GVC position, this study analyzes data from the Organization for Economic Co-operation and Development (2004–2018) and Asian Development Bank (2019–2023). The study finds that while GTI positively impacted GVC upgrading pre-2018, this effect reversed post-2018. The moderation analysis further reveals that the inverted U-shaped effect of environmental regulation weakened after 2018, whereas the positive linear moderating effect of absorptive capacity reversed entirely. These results highlight the critical influence of industry heterogeneity and contextual factors, demonstrating the need for resilience-focused policies to navigate the evolving GTI-GVC relationship.

本文研究了绿色技术创新（GTI）对中国制造业全球价值链地位的非线性影响。为此，考虑了环境调节和吸收能力的调节作用。本研究使用基于专利合作条约数据的创新指标来分析GTI和基于Wang-Wei-Yu-Zhu-Koopman-Wang-Wei框架的全球价值链位置，分析了经济合作与发展组织（2004-2018）和亚洲开发银行（2019-2023）的数据。研究发现，虽然GTI在2018年前对全球价值链升级产生了积极影响，但这种影响在2018年后发生了逆转。调节效应分析进一步表明，2018年后环境规制的“倒u”型调节效应减弱，而吸收能力的正线性调节效应则完全逆转。这些结果突出了行业异质性和环境因素的关键影响，表明需要制定以弹性为重点的政策来引导不断发展的GTI-GVC关系。

引用次数: 0

Informed trading and the fossil fuel industry's influence over UN climate meetings 知情交易和化石燃料行业对联合国气候会议的影响

IF 14.2 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2025-11-28 DOI: 10.1016/j.eneco.2025.109065

Xiaoyan Chen , Xin Ling , Martina Linnenluecke , Mona Mashhadi Rajabi , Tom Smith

This study develops a novel methodology to estimate the probability of informed trading around United Nations COP climate meetings. Analyzing data from a sample of 87 U.S.-listed fossil fuel firms between 2006 and 2023, we find that informed trading rises significantly during the [−9, 9] window. This activity generated abnormal returns of 17.565 %, or up to $25.064 billion in profit for informed traders over the relevant period. Our analysis shows that compared to fossil fuel stocks, the change in the probability of informed trading in industrials, healthcare, finance and utilities was relatively flat during COP meetings and the accumulated profit obtained by informed traders in these markets was at most $8.719 billion. Following Adler et al. (2025) who classify COP meetings by positive and negative climate policy shocks, we find that the change in the probability of informed trading around meetings with positive signals is 70.237 %, while it is 62.721 % for meetings with negative signals. We also find that the change in the probability of informed trading around COP21 (at which the Paris Agreement was adopted) was 3.544 times higher than the average across all other COP meetings, while the associated CAR was 2.118 times higher. Given the fossil fuel industry's substantial presence at COP meetings, our findings suggest that these events offer not only policy signals but also informational advantages to select market participants.

本研究开发了一种新的方法来估计联合国缔约方会议期间知情交易的可能性。分析了2006年至2023年间87家美国上市化石燃料公司的样本数据，我们发现，在[- 9,9]窗口期间，知情交易显著增加。这一活动在相关期间为知情交易者创造了17.565%的异常回报，或高达250.64亿美元的利润。我们的分析表明，与化石燃料股票相比，在缔约方会议期间，工业、医疗保健、金融和公用事业领域知情交易的概率变化相对平稳，这些市场中知情交易者获得的累计利润最多为87.19亿美元。根据Adler等人（2025）根据积极和消极的气候政策冲击对缔约方会议进行分类，我们发现，在带有积极信号的会议周围，知情交易的概率变化为70.237 %，而在带有消极信号的会议周围，知情交易的概率变化为62.721%。我们还发现，COP21（通过《巴黎协定》）前后知情交易概率的变化比所有其他COP会议的平均值高3.544倍，而相关的CAR高2.118倍。鉴于化石燃料行业在缔约方会议上的大量存在，我们的研究结果表明，这些活动不仅提供了政策信号，而且为选择的市场参与者提供了信息优势。

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引用次数: 0

Subsidies and rebound effect with incomplete carbon pricing: An application to biogas and livestock 不完全碳定价下的补贴与反弹效应——以沼气和牲畜为例

IF 14.2 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2025-11-27 DOI: 10.1016/j.eneco.2025.109070

Guy Meunier, Victor Besnier

Bioenergies from dedicated crops or wood have faced substantial criticisms due to their significant land requirements. Certain bioenergy pathways, such as biogas generated from crop residues, manure, or food waste, appear to be exempt from this criticism. However, these feedstocks are byproducts of agricultural activities that generate emissions not covered by current climate policies in most countries. We analyze the optimal biogas subsidy in a second-best framework featuring food–energy market interactions and incomplete pricing of emissions from food production and fossil natural gas. We show analytically how the indirect effect of the biogas subsidy on food production should be taken into account, as well as the welfare implications. We provide numerical simulations calibrated on the French dairy market and anaerobic digestion of livestock manure. We compare a second-best situation in which dairy emissions are not taxed with a first-best situation in which they are taxed. This illustration indicates that for a small Social Cost of Carbon, the rebound effect on milk production is moderate, and the optimal subsidy departs from the Pigouvian one accordingly. The second-best quantity of biogas is slightly larger than the first-best one. For a large Social Cost of Carbon, the rebound effect is important, and the gap between the first-best and second-best widens considerably.

来自专用作物或木材的生物能源由于其巨大的土地需求而面临大量批评。某些生物能源途径，如从作物残留物、粪便或食物垃圾中产生的沼气，似乎不受这种批评的影响。然而，这些原料是农业活动的副产品，产生的排放在大多数国家目前的气候政策中没有包括在内。我们在一个次优框架中分析了最优沼气补贴，该框架具有粮食-能源市场相互作用和粮食生产和化石天然气排放的不完全定价。我们分析了沼气补贴对粮食生产的间接影响应该如何考虑，以及福利影响。我们提供在法国乳制品市场校准的数值模拟和牲畜粪便的厌氧消化。我们比较了乳制品排放不征税的次优情况和征税的第一优情况。由图可知，当碳社会成本较小时，对牛奶生产的反弹效应适中，最优补贴偏离庇古模型。次优沼气量略大于第一优沼气量。对于碳的巨大社会成本来说，反弹效应很重要，第一最佳和第二最佳之间的差距大大扩大。

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引用次数: 0

Product life cycle environmental regulation and corporate carbon emissions: Quasi-natural experiment from extended producer responsibility system 产品全生命周期环境规制与企业碳排放：生产者责任延伸制度下的准自然实验

IF 14.2 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2025-11-27 DOI: 10.1016/j.eneco.2025.109066

Yaohui Jiang , Xuanhao Zhang

Extended Producer Responsibility (EPR), which requires producers to take responsibility for the entire life cycle of their products, is a key policy tool for promoting the development of a circular economy and achieving carbon neutrality goals. By examining China's EPR policy practices, this study establishes a quasi-natural experiment based on its mandatory implementation in sectors such as appliances, batteries, automobiles, and paper packaging. Using data from China's listed companies from 2012 to 2022, we employ Propensity Score Matching Difference-in-Differences (PSM-DID) and Synthetic Difference-in-Differences (Synthetic-DID) models to examine its impact on the carbon emissions of regulated enterprises. The findings reveal that EPR reduces the carbon emissions of regulated enterprises by approximately 10.3 % on average, with the carbon reduction effect strengthening over time. Mechanism analysis indicates that EPR influences corporate carbon emissions by promoting green strategies, optimizing green information disclosure mechanisms, enhancing the quantity and quality of green low-carbon technological innovations, and reducing energy consumption during production. Heterogeneity tests indicate that the EPR-driven carbon reduction effect is more pronounced among firms in technology-intensive industries.

生产者延伸责任（Extended Producer Responsibility， EPR）要求生产者对其产品的整个生命周期负责，是促进循环经济发展和实现碳中和目标的关键政策工具。本研究通过对中国EPR政策实践的考察，建立了一个基于其在家电、电池、汽车和纸包装等行业强制实施的准自然实验。本文利用2012 - 2022年中国上市公司的数据，采用倾向得分匹配差分差分（PSM-DID）和合成差分差分（Synthetic- did）模型，考察了其对被监管企业碳排放的影响。研究结果表明，EPR使被监管企业的碳排放量平均减少约10.3%，并且随着时间的推移，碳减排效果不断增强。机制分析表明，EPR通过推进绿色战略、优化绿色信息披露机制、提高绿色低碳技术创新的数量和质量、降低生产过程中的能耗对企业碳排放产生影响。异质性检验表明，在技术密集型企业中，epr驱动的碳减排效应更为显著。

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引用次数: 0

How do two-way contracts-for-difference affect futures markets? A novel modelling approach of futures market liquidity 双向差价合约如何影响期货市场？一种新的期货市场流动性建模方法

IF 14.2 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2025-11-27 DOI: 10.1016/j.eneco.2025.109069

Fabian Wagner , Malte Jansen , Lena Kitzing

In the wake of the energy crisis, EU governing bodies agreed on a reform of the European electricity market. The new regulation stipulates that direct price support must be given to new renewable energy installations in the form of two-way contracts-for-differences (CfDs) (or equivalent). This has raised concerns about potential negative effects on liquidity in long-term electricity markets, but the scientific literature has yet to conduct corresponding analyses. To address this gap, we developed a modelling approach to quantify expected futures market volumes and evaluate resulting churn rates. We demonstrated it for the German electricity futures market and found that in the beginning of the considered period, general market characteristics dictated liquidity developments. Yet, CfDs became increasingly more decisive for the market outcome. We found that the impact of CfDs on liquidity can largely be altered through specific design decisions, such as duration, share, and reference price design. While some measures were more suitable for addressing either minimum or average churn rates, different combinations emerged to be able to reach similar liquidity targets. Lastly, we demonstrate the importance of selecting an appropriate counterfactual for evaluating modelling results and drawing conclusions.

在能源危机之后，欧盟管理机构同意对欧洲电力市场进行改革。新法规规定，必须以双向差价合约（cfd）（或同等形式）的形式，对新的可再生能源装置提供直接价格支持。这引起了人们对长期电力市场流动性潜在负面影响的担忧，但科学文献尚未进行相应的分析。为了解决这一差距，我们开发了一种建模方法来量化预期的期货市场交易量并评估由此产生的流失率。我们对德国电力期货市场进行了证明，发现在考虑期的开始，一般市场特征决定了流动性的发展。然而，差价合约对市场结果的影响越来越大。我们发现差价合约对流动性的影响在很大程度上可以通过特定的设计决策来改变，比如期限、份额和参考价格设计。虽然有些措施更适合处理最低流失率或平均流失率，但出现了不同的组合，能够达到类似的流动性目标。最后，我们证明了选择适当的反事实来评估建模结果和得出结论的重要性。

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引用次数: 0

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