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Regime-aware conditional neural processes with multi-criteria decision support for operational electricity price forecasting 基于多准则决策支持的状态感知条件神经过程的运行电价预测
IF 12.8 2区 经济学 Q1 ECONOMICS Pub Date : 2026-02-28 DOI: 10.1016/j.eneco.2026.109233
Abhinav Das, Stephan Schlüter, Lorenz Schneider
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引用次数: 0
Decomposing return and volatility connectedness in Northwest European natural gas markets: Evidence from the R2 connectedness approach 西北欧天然气市场回报率和波动性的关联分析:来自r2关联方法的证据
IF 14.2 2区 经济学 Q1 ECONOMICS Pub Date : 2026-02-01 Epub Date: 2025-12-30 DOI: 10.1016/j.eneco.2025.109115
Markos Farag , Oliver Ruhnau
Regulatory reforms by the European Commission have facilitated the integration of European natural gas markets, thereby increasing their mutual interdependence in terms of prices and associated risks. Recent external shocks, including the COVID-19 pandemic and the Russian invasion of Ukraine, have disrupted market interconnectedness, as documented in the literature. However, the nature of shock transmission, whether contemporaneous or delayed, during periods of market instability, the subsequent speed of recovery in price and volatility connectedness, and the potential differences between spot and futures prices have not yet been investigated. This paper addresses these issues in two steps. First, it quantifies the dynamics of return and volatility connectedness among Northwest European gas hubs using the R2 decomposition connectedness method. Second, it explains these dynamics by linking fluctuations in connectedness to physical, policy, and macroeconomic factors using a regression-based framework. Our findings show that contemporaneous spillovers dominate lagged spillovers, even during external shocks, indicating rapid market adjustments. Moreover, while market connectedness declined significantly during major disruptions, it promptly returned to pre-crisis levels once these disruptions subsided. Futures markets showed higher connectedness than spot markets during tight conditions, suggesting greater alignment with broader market expectations and reduced susceptibility to physical constraints. Furthermore, regression analysis indicates that return and volatility connectedness decline significantly when certain pipelines are congested, whereas congestion on other links has no clear effect.
欧洲委员会的管制改革促进了欧洲天然气市场的一体化,从而增加了它们在价格和相关风险方面的相互依存关系。正如文献所记载的那样,最近的外部冲击,包括COVID-19大流行和俄罗斯入侵乌克兰,已经破坏了市场的互联性。然而,在市场不稳定时期,冲击传导的性质(无论是同步的还是延迟的)、随后的价格恢复速度和波动性连通性,以及现货和期货价格之间的潜在差异尚未得到调查。本文分两个步骤解决这些问题。首先,利用R2分解连通性方法量化了西北欧天然气枢纽的收益和波动连通性动态。其次,它通过使用基于回归的框架将连通性的波动与物理、政策和宏观经济因素联系起来,解释了这些动态。我们的研究结果表明,即使在外部冲击期间,同期溢出效应主导滞后溢出效应,表明市场调整迅速。此外,虽然市场连通性在重大中断期间显著下降,但一旦这些中断消退,它就会迅速恢复到危机前的水平。在紧张形势下,期货市场比现货市场表现出更高的连通性,这表明期货市场与更广泛的市场预期更加一致,对实物约束的敏感性降低。此外,回归分析表明,当某些管道阻塞时,回报率和波动率连通性显著下降,而其他链路阻塞则没有明显影响。
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引用次数: 0
Measuring energy resilience via risk absorption: High-frequency evidence from China 通过风险吸收衡量能量弹性:来自中国的高频证据
IF 14.2 2区 经济学 Q1 ECONOMICS Pub Date : 2026-02-01 Epub Date: 2025-12-31 DOI: 10.1016/j.eneco.2025.109117
Liangpeng Wu , Xinlei Feng , Xiaoyong Zhou , Qingyuan Zhu , Dequn Zhou
Energy markets face intensifying shocks, making a real-time measure of energy resilience essential. Conventional low-frequency metrics miss short-run dynamics and the risk-absorption capacity of the energy system. This study proposes a methodological framework to assess energy resilience through risk-absorption by (i) integrating mixed-frequency indicators into an energy system index (ESI) via a dynamic factor model, (ii) proxying systemic financial stress with marginal expected shortfall, and (iii) tracing the ESI's impulse response to risk shocks using a time-varying parameter VAR with stochastic volatility. This approach captures high-frequency dynamics, accommodates evolving transmission mechanisms, and yields two interpretable risk-absorption measures: energy resilience intensity (ERi) and energy resilience duration (ERd). For China during 2009–2022, the results show that energy resilience stabilized overall and was shaped mainly by risks stemming from external financing dependence (international financial markets) and capital-price transmission (stock markets). ERd and ERi display a clear dual-regime pattern, with both regimes exhibiting strong self-sustaining persistence. Four pronounced fluctuations—2010–2011, 2014–2015, 2017–2018, and 2020–2022—correspond to surges in geopolitical risk (GPR), trade policy uncertainty (TPU), and climate risks. Empirically, TPU exerts a dual effect on energy resilience by shortening ERd while reducing ERi, whereas geopolitical and climate risks mainly prolong recovery processes (increasing ERd) without significantly weakening systemic stability (ERi). In addition, domestic emergencies such as campaign-based decarbonization also exert an impact on ERd. This study provides a dynamic, high-frequency measurement framework and clarifies the differential roles of geopolitical, trade, and climate risks in shaping energy resilience across risk-absorption intensity and duration.
能源市场面临着日益加剧的冲击,因此实时衡量能源弹性至关重要。传统的低频指标忽略了能源系统的短期动态和风险吸收能力。本研究提出了一个方法框架,通过风险吸收来评估能源弹性,方法包括:(i)通过动态因子模型将混合频率指标整合到能源系统指数(ESI)中,(ii)用边际预期不足来代理系统性金融压力,以及(iii)使用具有随机波动率的时变参数VAR来跟踪ESI对风险冲击的脉冲响应。该方法捕捉高频动态,适应不断变化的传递机制,并产生两种可解释的风险吸收指标:能量恢复强度(ERi)和能量恢复持续时间(ERd)。2009-2022年,中国能源弹性总体趋于稳定,主要受外部融资依赖(国际金融市场)和资本价格传导(股票市场)风险的影响。ERd和ERi表现出明显的双体制模式,两种体制都表现出很强的自我维持持久性。2010 - 2011年、2014-2015年、2017-2018年和2020 - 2022年四次显著波动对应于地缘政治风险(GPR)、贸易政策不确定性(TPU)和气候风险的激增。经验表明,TPU通过缩短ERd和降低ERi对能源弹性产生双重影响,而地缘政治和气候风险主要是延长恢复过程(增加ERd),而不会显著削弱系统稳定性(ERi)。此外,国内紧急情况,如以运动为基础的脱碳也对ERd产生影响。本研究提供了一个动态的高频测量框架,并阐明了地缘政治、贸易和气候风险在影响能源弹性的风险吸收强度和持续时间中的不同作用。
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引用次数: 0
Assessing the effect of climate policy uncertainty on corporate carbon cost leadership strategy: Evidence from China 评估气候政策不确定性对企业碳成本领先战略的影响:来自中国的证据
IF 14.2 2区 经济学 Q1 ECONOMICS Pub Date : 2026-02-01 Epub Date: 2026-01-04 DOI: 10.1016/j.eneco.2025.109118
Zhongzhu Chu , Weijie Tan , Boru Ren , Zhiyi Xia
Frequent extreme climate events have heightened climate policy uncertainty (CPU) and incorporating the social cost of carbon has become a key element for countries seeking to improve their institutions in response to climate risks. Focusing on corporate efforts, this study innovatively constructs a carbon cost leadership strategy (CCLS) index for Chinese listed companies from 2010 to 2024 using a text-based machine learning approach. Drawing on institutional theory, we examine the relationship between CPU and firms' adoption of CCLS. Our findings indicate that CPU significantly inhibits the implementation of CCLS, primarily because CPU increases firms' operational risks and undermines firms' capacity to respond to climate regulations. Heterogeneity analysis reveals that this negative effect is more pronounced for state-owned enterprises, firms with low climate risk perception, those in low carbon-exposure and non-technology-intensive industries, and firms located in regions with weak public–government climate engagement. This study enriches the understanding of the social impacts of climate policy from the perspective of corporate carbon cost management and provides new insights for emerging economies to improve their social cost of carbon assessment systems and enhance firms' climate response capabilities.
频繁的极端气候事件加剧了气候政策的不确定性(CPU),纳入碳的社会成本已成为寻求改善其应对气候风险制度的国家的关键因素。本研究以企业为研究对象,采用基于文本的机器学习方法,创新性地构建了2010 - 2024年中国上市公司碳成本领先战略(CCLS)指数。利用制度理论,我们考察了中央集权与企业采用CCLS之间的关系。我们的研究结果表明,CPU显著抑制了CCLS的实施,主要是因为CPU增加了企业的运营风险,削弱了企业应对气候法规的能力。异质性分析表明,国有企业、低气候风险认知企业、低碳暴露和非技术密集型行业企业以及公共政府气候参与较弱地区的企业的负面影响更为明显。本研究从企业碳成本管理的角度丰富了对气候政策社会影响的认识,为新兴经济体完善碳社会成本评估体系、提高企业应对气候变化能力提供了新的思路。
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引用次数: 0
Effects of basin ecological compensation policies in China: Insights from policy design differences 中国流域生态补偿政策的效果:来自政策设计差异的洞察
IF 14.2 2区 经济学 Q1 ECONOMICS Pub Date : 2026-02-01 Epub Date: 2026-01-05 DOI: 10.1016/j.eneco.2026.109132
Lei Zhou , Shaoxin Hong , Siyan Su
There are two types of Basin Ecological Compensation Policies (BECP) in China: a formal policy initiated by the central government in the Xin'an River Basin and an informal policy organized by local governments in the Wei River Basin. We use a difference-in-differences (DID) approach to identify and compare the effects of these two policy types. We find that the BECP in the Xin'an River Basin significantly reduces enterprises' water pollutant emissions but also decreases Total Factor Productivity (TFP), whereas the BECP in the Wei River Basin has no significant effect. In addition, enterprises in the Xin'an River Basin experience reduced output and increased investment in cleaner production practices, which serve as the main channels through which water pollutant emissions decline. We further show that the economic losses borne by upstream regions exceed the compensation they receive, indicating that the compensation funds are insufficient. Finally, heterogeneity analyses reveal that the effectiveness of the BECP depends on factors such as adjacency to provincial boundaries, river length within a county, the number of industrial enterprises, and enterprise tax levels. These findings provide useful insights for the broader application of BECPs and for negotiations over compensation funding.
中国的流域生态补偿政策主要有两种类型:一种是中央政府在新安江流域发起的正式政策,另一种是渭河流域地方政府组织的非正式政策。我们使用差异中的差异(DID)方法来识别和比较这两种策略类型的效果。研究发现,新安河流域的BECP显著降低了企业的水污染物排放,但也降低了全要素生产率(TFP),而渭河流域的BECP没有显著影响。此外,新安河流域企业在清洁生产实践方面的产出减少,投资增加,这是水污染物排放下降的主要渠道。研究进一步表明,上游地区所遭受的经济损失超过了所获得的补偿,表明补偿资金不足。最后,异质性分析表明,省际边界邻近程度、县域河流长度、工业企业数量和企业税收水平等因素对城市经济效益的影响显著。这些发现为becp的更广泛应用和赔偿资金的谈判提供了有用的见解。
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引用次数: 0
The power of storytelling: How green narratives shape urban green innovation 讲故事的力量:绿色叙事如何塑造城市绿色创新
IF 14.2 2区 经济学 Q1 ECONOMICS Pub Date : 2026-02-01 Epub Date: 2026-01-03 DOI: 10.1016/j.eneco.2025.109122
Yajing Chen , Gaoxiang Xu , Yutian Shan , Yushan Wei , Saiquan Hu , Jie She
Promoting green innovation is strategically essential for sustainable development, requiring enhanced expected returns among innovation actors. As economic expectations are shaped by narratives, government-disseminated green narratives may serve as powerful policy levers for advancing green innovation. This study employs large language models and LDA topic modeling to extract green narrative-related variables from Chinese provincial Party newspapers, combining these measures with panel data from 288 Chinese cities spanning 2011–2022 to examine how green narratives influence urban green innovation and through what mechanisms. The findings reveal that green narrative exposure significantly promotes urban green innovation through two pathways: facilitating green finance development and enhancing public environmental concern. Both the economic relevance of narrative topics and the narrativity of formats positively moderate this relationship. Further analyses confirm that narrative effects extend to firm-level green innovation quality measured by patent citations. This study demonstrates narratives as effective policy instruments for green innovation, extends green narrative research from individual to regional outcomes, and provides insights for leveraging narratives to promote substantive technological progress.
促进绿色创新对可持续发展具有重要战略意义,这需要提高创新行为体的预期回报。由于经济预期是由叙事塑造的,政府传播的绿色叙事可以作为推动绿色创新的有力政策杠杆。本研究采用大型语言模型和LDA主题模型,从中国省党报中提取绿色叙事相关变量,并结合2011-2022年288个中国城市的面板数据,研究绿色叙事如何影响城市绿色创新,以及通过何种机制影响城市绿色创新。研究发现,绿色叙事曝光通过促进绿色金融发展和增强公众环境关注度两种途径显著促进城市绿色创新。叙事主题的经济相关性和格式的叙事性都对这种关系起到正向调节作用。进一步的分析证实,叙事效应延伸到企业层面的绿色创新质量衡量专利引用。本研究证明了叙事作为绿色创新的有效政策工具,将绿色叙事研究从个体结果扩展到区域结果,并为利用叙事促进实质性技术进步提供了见解。
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引用次数: 0
A data-driven merit order: Learning a fundamental electricity price model 数据驱动的价值排序:学习基本电价模型
IF 14.2 2区 经济学 Q1 ECONOMICS Pub Date : 2026-02-01 Epub Date: 2025-12-30 DOI: 10.1016/j.eneco.2025.109114
Paul Ghelasi, Florian Ziel
Electricity price forecasting approaches generally fall into two categories: data-driven models, which learn from historical patterns, or fundamental models, which simulate market mechanisms. We propose a novel and highly efficient data-driven merit order model that integrates both paradigms. The resulting supply stack framework embeds the classical expert-based merit order as a nested special case, allowing all key parameters, such as plant efficiencies, bidding behavior, and available capacities, to be estimated directly from historical data, rather than assumed. We further enhance the model with critical embedded extensions such as hydro power, cross-border flows and corrections for underreported capacities, which considerably improve forecasting accuracy. Applied to the German day-ahead market, our model outperforms both classic fundamental and state-of-the-art machine learning models. It retains the interpretability of fundamental models, offering insights into marginal technologies, fuel switches, and dispatch patterns, elements which are typically inaccessible to black-box machine learning approaches. This transparency and high computational efficiency make it a promising new direction for electricity price modeling.
电价预测方法一般分为两类:从历史模式中学习的数据驱动模型,或模拟市场机制的基本模型。我们提出了一种新颖且高效的数据驱动的绩效排序模型,该模型集成了这两种范式。由此产生的供应堆栈框架将经典的基于专家的绩效排序嵌入为嵌套的特殊情况,允许所有关键参数,如工厂效率、投标行为和可用容量,直接从历史数据中进行估计,而不是假设。我们通过关键的嵌入式扩展,如水电、跨境流量和对低报容量的修正,进一步增强了模型,这大大提高了预测的准确性。应用于德国日前市场,我们的模型优于经典的基本模型和最先进的机器学习模型。它保留了基本模型的可解释性,提供了对边缘技术、燃料开关和调度模式的见解,这些元素通常是黑盒机器学习方法无法访问的。这种透明性和较高的计算效率使其成为电价建模的一个有前景的新方向。
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引用次数: 0
Strategic sector coupling? Market power in heat and power markets 战略部门耦合?供热和电力市场的市场力量
IF 14.2 2区 经济学 Q1 ECONOMICS Pub Date : 2026-02-01 Epub Date: 2025-12-30 DOI: 10.1016/j.eneco.2025.109106
Afzal S. Siddiqui , Sebastian Maier
Power-sector decarbonisation envisages extensive uptake of variable renewable energy (VRE) technologies. Although VRE output is intermittent, coupling between heat and power sectors via combined heat and power (CHP) plants could provide the requisite flexibility. However, strategic CHP plants could use the link between the two energy sectors to manipulate electricity prices. We use a bi-level model to investigate the incentives for the exercise of such market power. At the upper level, a firm with both heat-only and CHP plants is a Stackelberg leader when determining its heat output and is constrained by power-market operations at the lower level. Such a strategic firm produces more (less) heat from its CHP (heat-only) plant vis-à-vis the social optimum to constrain its power output, thereby boosting the electricity price. Additional market power at the lower level from power-only generation induces the strategic heat producer to reduce distortions to its operations as long as the electricity market is relatively large. In order to attenuate welfare losses from such strategic behaviour, we devise an incentive-based regulatory mechanism consisting of a subsidy to or a tax on CHP heat output. Numerical examples illustrate the properties of our analytical results, which can inform future negotiations over CHP cost allocations between regulators and producers.
电力部门的脱碳设想了可变可再生能源(VRE)技术的广泛采用。尽管VRE的输出是间歇性的,但通过热电联产(CHP)工厂实现热电部门之间的耦合可以提供必要的灵活性。然而,战略性的热电联产电厂可以利用这两个能源部门之间的联系来操纵电价。我们使用一个双层模型来研究这种市场力量的激励机制。在上层,同时拥有供热和热电联产电厂的公司在确定其热量输出时是Stackelberg的领导者,而在下层则受到电力市场运作的限制。这样的战略企业通过其热电联产(仅供热)工厂生产更多(更少)的热量,从而达到-à-vis社会最优,以限制其电力输出,从而提高电价。只要电力市场规模相对较大,仅发电所产生的较低水平的额外市场力量,就会促使战略产热企业减少对其运营的扭曲。为了减少这种战略行为造成的福利损失,我们设计了一种基于激励的监管机制,包括对热电联产的热输出进行补贴或征税。数值例子说明了我们分析结果的性质,这可以为未来监管机构和生产商之间关于热电联产成本分配的谈判提供信息。
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引用次数: 0
Research on the impact of ultra-high voltage transmission on urban carbon neutral technology innovation: An empirical test based on double machine learning method 超高压输电对城市碳中和技术创新的影响研究——基于双机器学习方法的实证检验
IF 14.2 2区 经济学 Q1 ECONOMICS Pub Date : 2026-02-01 Epub Date: 2025-12-30 DOI: 10.1016/j.eneco.2025.109120
Dongri Han , Ruiqi Wang , Yijia Yuan , Deheng Xiao
Energy infrastructure is a pivotal driver in reshaping the development trajectory of low-carbon technology as global carbon neutrality and the significant alteration of energy systems. Its innovation-driven efficacy has not been thoroughly investigated. This paper examines the “ultra-high voltage (UHV) transmission project,” which encompasses 270 Chinese cities at the prefecture level and above, as a quasi-natural experiment from 2006 to 2023. The difference-in-differences model and double machine learning are integrated to provide a causal inference framework that systematically reveals the multifaceted mechanism of energy infrastructure's impact on carbon neutral technology innovation. The findings indicate that UHV transmission project significantly increased carbon neutral technology innovation in pilot cities, enabling the optimal allocation of energy across regions. This supports the hypothesis of a network effect-innovation response mechanism driven by the dynamic adaptation of energy infrastructure. Further mechanism tests identify three transmission paths: government green development attention, informal environmental regulation, and energy consumption structure. Heterogeneity analysis reveals that these effects vary by region: energy-rich areas utilize UHV networks to break the resource curse; old industrial bases utilize it for green transitions; and small and medium-sized cities benefit from collaborative innovation. UHV transmission project reduces regional development gaps and weakens conventional geographic advantages. The paper provides precise policy targets for the energy revolution and regional coordination to support carbon neutrality, while providing practical guidance for infrastructure investment decisions.
随着全球碳中和和能源系统的重大变革,能源基础设施是重塑低碳技术发展轨迹的关键驱动力。其创新驱动的功效尚未得到彻底调查。本文将“特高压(UHV)输电项目”作为2006年至2023年的准自然实验进行研究,该项目涵盖了中国270个地级及以上城市。将差中差模型和双机器学习相结合,提供了一个因果推理框架,系统地揭示了能源基础设施对碳中和技术创新影响的多方面机制。研究结果表明,特高压输电项目显著促进了试点城市的碳中和技术创新,实现了区域间能源的优化配置。这支持了能源基础设施动态适应驱动的网络效应-创新响应机制假说。进一步的机制检验确定了三条传导路径:政府绿色发展关注度、非正式环境规制和能源消费结构。异质性分析表明,这些效应因地区而异:能源丰富地区利用特高压网络打破资源诅咒;老工业基地利用它进行绿色转型;中小城市从协同创新中受益。特高压输电工程缩小了区域发展差距,削弱了传统的地理优势。本文为能源革命和支持碳中和的区域协调提供了精确的政策目标,同时为基础设施投资决策提供了实用指导。
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引用次数: 0
Retraction notice to “Alleviating the rural household energy poverty in China: The role of digital economy” [Energy Economics 142 (2025) 108160] 关于《缓解中国农村家庭能源贫困:数字经济的作用》的撤稿通知[能源经济142 (2025)108160]
IF 14.2 2区 经济学 Q1 ECONOMICS Pub Date : 2026-02-01 Epub Date: 2026-01-16 DOI: 10.1016/j.eneco.2026.109143
Haijie Wang , Tong Yan , Rongbing Huang , Junsong Gao
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引用次数: 0
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Energy Economics
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