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Unraveling environmental threads: Bitcoin prices, energy consumption, and crypto market volatility 解开环境线索：比特币价格，能源消耗和加密市场波动

IF 14.2 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2026-03-01 Epub Date: 2026-02-24 DOI: 10.1016/j.eneco.2026.109216

Nishant Sapra , Imlak Shaikh , David Roubaud

Bitcoin has evolved into a major decentralized asset, yet its escalating electricity consumption has raised concerns. Because mining is profit-driven, higher prices intensify computational activity and energy demand, directly linking market dynamics to electricity use. This study empirically investigates the dynamic relationships among Bitcoin electricity consumption, Bitcoin prices, and cryptocurrency market volatility across time and frequency domains, complemented by nonlinear causal assessment. The study applies Biwavelet Coherence, Partial-Wavelet Transform Coherence, and Diks & Panchenko techniques to 1761 daily observations from March 2020 to January 2025. The frequency-domain analysis indicates that electricity consumption leads Bitcoin prices in the long run, whereas the nonlinear causality results reveal bidirectional feedback between the two variables. Collectively, these findings suggest that Bitcoin's energy use and its price influence each other over time, forming a feedback loop rather than operating in isolation. Further, Bitcoin's electricity consumption has bidirectional nonlinear causality with cryptocurrency volatility. The findings suggest that Bitcoin's electricity consumption is more sensitive to cryptocurrency market sentiment and geopolitical risk than to traditional economic and trade policy uncertainties, implying that behavioural and geopolitical indicators may offer more informative signals for monitoring fluctuations in energy consumed within the Bitcoin network. Given the linkage between Bitcoin prices and electricity consumption, policymakers may consider upper and lower trading circuits on cryptocurrency exchanges to moderate price-driven surges in mining-related energy demand. Policymakers may also consider cryptocurrency market volatility, investor sentiment, and geopolitical risk indicators for monitoring fluctuations in Bitcoin's electricity consumption, given its observed sensitivity to these factors.

比特币已经发展成为一种主要的去中心化资产，但其不断上升的用电量引发了人们的担忧。由于采矿是利润驱动的，较高的价格加剧了计算活动和能源需求，将市场动态与用电量直接联系起来。本研究对比特币用电量、比特币价格和加密货币市场波动之间的动态关系进行了实证研究，并辅以非线性因果评估。该研究将双小波相干性、部分小波变换相干性和Diks & Panchenko技术应用于2020年3月至2025年1月的1761次日常观测。频域分析表明，长期来看，电力消耗主导比特币价格，而非线性因果关系结果揭示了两个变量之间的双向反馈。总的来说，这些发现表明，随着时间的推移，比特币的能源使用和价格会相互影响，形成一个反馈循环，而不是孤立地运行。此外，比特币的用电量与加密货币波动具有双向非线性因果关系。研究结果表明，与传统的经济和贸易政策不确定性相比，比特币的电力消耗对加密货币市场情绪和地缘政治风险更敏感，这意味着行为和地缘政治指标可能为监测比特币网络内能源消耗的波动提供更多信息信号。鉴于比特币价格与电力消耗之间的联系，政策制定者可能会考虑加密货币交易所的上下交易电路，以缓和价格驱动的挖矿相关能源需求激增。考虑到比特币对这些因素的敏感性，政策制定者还可以考虑加密货币市场波动、投资者情绪和地缘政治风险指标，以监测比特币用电量的波动。

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引用次数: 0

Corrigendum to ‘Comparison between inclusive finance and green finance in alleviating energy poverty and the mediating role of energy structure’ [Energy Economics Volume 147 June 2025 108597] “普惠金融与绿色金融缓解能源贫困的比较及能源结构的中介作用”的勘误表[能源经济学第147卷，2025年6月108597]

IF 14.2 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2026-03-01 Epub Date: 2026-02-09 DOI: 10.1016/j.eneco.2026.109188

Meirui Zhong , Ti Zhou , Qingtian Wu

引用次数: 0

Artificial intelligence and green development: Evidence from China on efficiency and equity 人工智能与绿色发展：来自中国的效率与公平证据

IF 14.2 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2026-03-01 Epub Date: 2026-02-12 DOI: 10.1016/j.eneco.2026.109201

Tielong Wu

This study investigates the impact of Artificial Intelligence (AI) policy on urban green development, focusing on both efficiency and equity perspectives. We first apply a green growth model to analyze the green development. Then, using panel data from 286 cities in China between 2000 and 2023, we assess the Green Development Efficiency (GDE) of cities through Data Envelopment Analysis and analyze the impact of AI policy on efficiency with a Difference-in-Differences model. Finally, we do convergence analysis to explore the equity of green development across cities. The results show that AI policies lead to a “dividend” in the form of enhanced overall GDE, driven by improvements in technical and scale efficiency, increased patent outputs, and urban agglomeration. However, the study also reveals a “divide”, as the benefits are not equally distributed across cities. Convergence analysis reveals no global convergence across cities but identifies six convergent clubs and one divergent club. Ordered probit analysis shows that AI policies do not significantly affect a city's likelihood of transitioning between clubs. In the meantime, regional heterogeneity is observed, with the positive impact of AI policy being more pronounced in eastern regions, while smaller improvements are observed in central and western regions. Negative spillover effects are also found in cities within a 50 km radius of AI policy, where GDE decreases due to resource competition. While AI policies improve efficiency, they do not promote equitable green development. Future AI policies should focus on a more equitable green transition.

本文从效率和公平两个角度探讨了人工智能（AI）政策对城市绿色发展的影响。首先运用绿色增长模型对绿色发展进行分析。然后，利用2000 - 2023年中国286个城市的面板数据，通过数据包络分析对城市绿色发展效率（GDE）进行评估，并利用差中差模型分析人工智能政策对效率的影响。最后，通过收敛性分析来探讨城市间绿色发展的公平性。研究结果表明，人工智能政策在技术效率和规模效率提高、专利产出增加和城市群的驱动下，以提高总体gdp的形式带来了“红利”。然而，该研究也揭示了一个“鸿沟”，因为城市之间的利益分配并不平均。趋同分析显示，各个城市之间没有全球趋同，但确定了六个趋同俱乐部和一个发散俱乐部。有序概率分析表明，人工智能政策不会显著影响城市在俱乐部之间过渡的可能性。与此同时，人工智能政策的积极影响在东部地区更为明显，而在中西部地区的改善幅度较小。在人工智能政策半径50公里以内的城市，由于资源竞争，GDE下降，也出现了负外溢效应。虽然人工智能政策提高了效率，但它们并没有促进公平的绿色发展。未来的人工智能政策应侧重于更公平的绿色转型。

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引用次数: 0

Price competition and market dynamics under asymmetric costs: Evidence from discount gas station policy 非对称成本下的价格竞争与市场动态：来自折扣加油站政策的证据

IF 14.2 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2026-03-01 Epub Date: 2026-01-21 DOI: 10.1016/j.eneco.2026.109144

Yenjae Chang , Junyeol Ryu

This paper examines the market impact of a government-led intervention in South Korea’s retail fuel industry: the introduction of “thrifty” gas stations. These stations were supplied with fuel at reduced wholesale costs, thereby entering local markets with a cost advantage over incumbent stations. Drawing on a panel dataset covering approximately 22,000 gasoline stations from 2010 to 2019, we estimate the effects of this policy on fuel prices, market structure, and service quality. Using fixed effects and two-stage least squares (2SLS) models, we find that the entry of thrifty stations significantly lowered average retail gasoline prices through both direct cost-based pricing and intensified local competition. However, these short-run gains diminished over time as high-cost stations exited the market, leading to increased market concentration and weakened price competition. In addition, we document a shift toward self-service formats in treated markets, suggesting that service quality declined as firms adjusted to cost pressures. Taken together, the results indicate that while the policy effectively reduced prices in the short run, its long-run efficacy was undermined by structural and behavioral market adjustments, raising concerns about the dynamic consequences of asymmetric-cost competition under government intervention.

本文考察了政府主导的对韩国零售燃料行业的干预：引入“节俭”加油站的市场影响。这些加油站以较低的批发成本供应燃料，因此进入当地市场时比现有加油站具有成本优势。根据2010年至2019年覆盖约22,000个加油站的面板数据集，我们估计了这一政策对燃料价格、市场结构和服务质量的影响。利用固定效应和两阶段最小二乘（2SLS）模型，我们发现节俭加油站的进入通过直接基于成本的定价和加剧的地方竞争显著降低了平均零售汽油价格。然而，随着高成本加油站退出市场，这些短期收益随着时间的推移而减少，导致市场集中度增加，价格竞争减弱。此外，我们记录了在接受治疗的市场中向自助服务模式的转变，这表明随着公司适应成本压力，服务质量下降。综上所述，研究结果表明，虽然政策在短期内有效降低了价格，但其长期效果受到结构性和行为性市场调整的影响，这引起了人们对政府干预下不对称成本竞争的动态后果的担忧。

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引用次数: 0

Carbon pricing effects on renewables: Evidence from California's electricity market 碳定价对可再生能源的影响：来自加州电力市场的证据

IF 14.2 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2026-03-01 Epub Date: 2026-02-02 DOI: 10.1016/j.eneco.2026.109174

Gökhan Dilek , Jordi J. Teixidó , Mònica Serrano

California's electricity market is remarkable due to its distinctive regulatory framework, which incorporates a cap-and-trade system and a carbon border adjustment mechanism (CBAM). However, our understanding of the effects of these carbon pricing policies on renewables deployment in California and its neighboring states is limited. Here we show that California's cap-and-trade policy has a positive effect on renewable electricity capacity at a county level, with an additional 148.9 MW on average compared to the counterfactual scenario with no carbon pricing; this equates to a 6.71 percentage point increase in the share of statewide renewable electricity capacity. Regarding the CBAM, we show novel ex-post evidence on the effects of the CBAM on California's main trading partners in terms of new renewable capacity. We find that the CBAM positively impacts renewable capacity in California's neighboring states if their electricity exports are not already from renewable sources (Arizona and Nevada, but not Oregon, which has major exports from hydroelectric plants). A thorough discussion of complementary policies (such as the role played by Renewable Portfolio Standards) is presented and the results are robust to them. These results are relevant in terms of the effects of carbon pricing on the adoption of zero‑carbon technology.

加州的电力市场因其独特的监管框架而引人注目，该框架结合了限额与交易体系和碳边界调整机制（CBAM）。然而，我们对这些碳定价政策对加州及其邻近州可再生能源部署的影响的理解是有限的。本文表明，加州的限额与交易政策对县一级的可再生电力容量有积极影响，与没有碳定价的反事实情景相比，平均增加了148.9兆瓦；这相当于全州可再生电力容量的份额增加了6.71个百分点。关于CBAM，我们展示了CBAM对加州主要贸易伙伴在新增可再生能源容量方面的影响的新颖事后证据。我们发现，如果加州邻近州的电力出口不是来自可再生能源（亚利桑那州和内华达州，但不包括俄勒冈州，其主要出口来自水力发电厂），那么CBAM将对可再生能源发电能力产生积极影响。对补充政策（如可再生能源投资组合标准所起的作用）进行了深入的讨论，结果对他们来说是强有力的。就碳定价对采用零碳技术的影响而言，这些结果具有相关性。

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引用次数: 0

Impact of climate vulnerability on fiscal risk: Do religious tensions and financial development matter? 气候脆弱性对财政风险的影响：宗教紧张和金融发展重要吗？

IF 14.2 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2026-03-01 Epub Date: 2026-02-06 DOI: 10.1016/j.eneco.2026.109180

Jamel Saadaoui , John Beirne , Donghyun Park , Gazi Salah Uddin

Using data from around 100 countries between 1995 and 2019, we examine the impact of climate vulnerability on fiscal risk. We also explore the transmission channels that are important for the relationship between climate vulnerability and fiscal risk. Our results show that in highly climate-vulnerable economies, increased vulnerability leads to higher government bond yields by 0.5 to 1.5 percentage point and lower sovereign debt ratings by up to one notch over two years. These effects are exacerbated by religious tensions as a form of political instability but mitigated by well-developed financial markets. Therefore, even though fiscal consolidation is crucial for containing fiscal risks in the case of climate vulnerability, political stability and financial development also matter.

我们利用1995年至2019年约100个国家的数据，研究了气候脆弱性对财政风险的影响。我们还探讨了气候脆弱性与财政风险之间关系的重要传导渠道。我们的研究结果表明，在高度易受气候影响的经济体中，脆弱性的增加导致政府债券收益率在两年内上升0.5至1.5个百分点，主权债务评级最高下降一个等级。作为政治不稳定的一种形式，宗教紧张加剧了这些影响，但发达的金融市场减轻了这些影响。因此，尽管在气候脆弱性的情况下，财政整顿对于遏制财政风险至关重要，但政治稳定和金融发展也很重要。

引用次数: 0

Improvement of carbon price prediction with social factors and mixed-frequency unstructured data 基于社会因素和混合频率非结构化数据的碳价格预测改进

IF 14.2 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2026-03-01 Epub Date: 2026-02-05 DOI: 10.1016/j.eneco.2026.109190

Jinghao Kang , Fengyu Yang , Sicheng Li , Wanbo Lu , Muhammad Shahbaz , Kaiyang Zhong

Carbon emissions trading right is one of core financial instruments for climate risk management, and carbon trading price prediction can be an effective tool. China's carbon emissions trading prices fluctuate greatly on account of many exogenous factors. However, (i) scholars just consider one or several factors, and few take the comprehensive influencing factors into consideration in study; (ii) very little attention has been paid to employ the unstructured data to research the impact of policies on the carbon market; (iii) This sample frequency approach not only result in factors information loss but cannot depict non-stationary, non-parameters, complexed nonlinear and multi-frequency features of the time series of variables in carbon market. The introduction of social factor data, effective processing of high-dimensional data, and prediction methods improvement are still in great need. To address these gaps, with the examples of carbon emission rights trading prices in China's markets, this paper proposes a mixed frequency method with unstructured data for carbon price prediction: (1) First, we intrude the social policy of sentiment index and Baidu search index as influencing factors, and effectively deal with such unstructured data. The results show that they act as important factors in four carbon trading markets. (2) Second, by screening key indicators and combining the mixed frequency dynamic factor model (MF-DFM), we explore the overall influence of the typical external factors on carbon prices and forecast the volatility of carbon prices. (3) Third, deep neural network (DNN) models are added to predict diligently the residual, and the effect of deep learning model and method on improving the forecasting accuracy is discussed. Our study has further improved the factor system that affects carbon trading prices and proposed more predictive methods, which can have certain reference value for carbon emission trading management.

碳排放权是气候风险管理的核心金融工具之一，碳交易价格预测可以成为一种有效的工具。受诸多外生因素影响，中国碳排放交易价格波动较大。然而，(1)学者在研究中只考虑一个或几个因素，很少考虑综合影响因素；（二）利用非结构化数据研究政策对碳市场影响的研究很少；（iii）这种样本频率方法不仅导致因素信息丢失，而且不能描述碳市场中变量时间序列的非平稳、非参数、复杂非线性和多频特征。社会因素数据的引入、高维数据的有效处理以及预测方法的改进仍是亟待解决的问题。针对这些不足，本文以中国市场碳排放权交易价格为例，提出了一种基于非结构化数据的混合频率方法进行碳价格预测：(1)首先引入社会政策的情绪指数和百度搜索指数作为影响因素，有效处理非结构化数据。结果表明，它们在四个碳交易市场中都是重要的影响因素。(2)其次，通过筛选关键指标，结合混合频率动态因子模型（MF-DFM），探讨典型外部因素对碳价格的整体影响，预测碳价格波动。(3)第三，加入深度神经网络（DNN）模型对残差进行勤奋预测，讨论深度学习模型和方法对提高预测精度的影响。本研究进一步完善了影响碳交易价格的因素体系，提出了更多的预测方法，对碳排放交易管理具有一定的参考价值。

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引用次数: 0

Ambiguity about volatility in the commodity futures market 商品期货市场波动的模糊性

IF 14.2 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2026-03-01 Epub Date: 2026-02-11 DOI: 10.1016/j.eneco.2026.109199

Thanos Verousis , Kai Wang , Zhiping Zhou

This study offers the first comprehensive evidence of the impact of ambiguity about volatility on commodity futures. We demonstrate that ambiguity about volatility is a significant determinant of commodity futures returns and volatility. Building on Bianchi et al. (2018), we argue that ambiguity is a priced factor that is distinct from risk but moves with risk. In line with this argument, we show that volatility provides an amplification mechanism for ambiguity volatility shocks. Economically, this amplification effect is very important: the impact of an ambiguity volatility shock to commodity futures returns (volatility) during a less volatile period is 6 (1.8) times smaller than that when markets are least stable. We also document evidence of a heterogeneous influence of ambiguity about volatility on commodity asset classes. Economically, during stress periods, the impact of ambiguity on energy returns is approximately 200% larger than that of the commodity index. Our results survive a range of robustness tests.

本研究首次提供了波动性模糊性对商品期货影响的综合证据。我们证明了波动性的模糊性是商品期货收益和波动性的重要决定因素。在Bianchi等人（2018）的基础上，我们认为模糊性是一种定价因素，与风险不同，但会随着风险而变化。根据这一论点，我们表明波动性为模糊性波动冲击提供了一种放大机制。从经济上讲，这种放大效应非常重要：在波动较小的时期，模糊性波动冲击对商品期货回报（波动率）的影响比市场最不稳定时小6（1.8）倍。我们还记录了对商品资产类别波动的模糊性的异质影响的证据。在经济上，在压力时期，模糊性对能源回报的影响大约比商品指数的影响大200%。我们的结果经受住了一系列稳健性测试。

引用次数: 0

Diffusion of electric vehicles – The spillover effect of charging facilities and government demonstrations for neighbouring and peer regions 电动汽车的扩散——充电设施和政府示范对邻近和同行地区的溢出效应

IF 14.2 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2026-03-01 Epub Date: 2026-01-23 DOI: 10.1016/j.eneco.2026.109164

Ronghui Zhu , Tieju Ma , Jingbing Feng

Promoting the adoption of electric vehicles (EVs) is important for the decarbonisation of the transportation sector. Existing research indicates that the diffusion of new technologies tends to be highly spatially correlated. This study explores whether a region's adoption of EVs is positively related with the availability of charging facilities and government demonstrations promoting EVs in peer regions. This study develops a dynamic spatial panel data model based on the Spatial Dubin Model to explore this question using panel data from 28 provinces in China from 2013 to 2020. The main findings of this study include the following: 1) Not surprisingly, the high availability of charging facilities in a region and its local government's demonstration effort contribute to the adoption of EVs in the region; 2) the adoption of EVs in one region can contribute to EV adoption in its peer regions – so-called spillover effect; in particular, the government's demonstration effort contributes significantly to this effect, but the high availability of charging facilities does not; and 3) such spillover effects are more significant in regions with higher economic levels or regions with warm temperatures. Our study provides implications for EV makers to identify further potential markets for EVs.

推动电动汽车（ev）的采用对交通运输部门的脱碳至关重要。现有研究表明，新技术的扩散往往具有高度的空间相关性。本研究探讨了一个地区对电动汽车的采用是否与充电设施的可用性和政府在同行地区推广电动汽车的示范呈正相关。本文利用2013 - 2020年中国28个省份的面板数据，建立了基于空间杜宾模型的动态空间面板数据模型来探讨这一问题。本研究的主要发现包括：1)毫无疑问，充电设施的高可用性以及当地政府的示范努力有助于该地区采用电动汽车；2)一个地区对电动汽车的采用可以促进其同级地区对电动汽车的采用，即所谓的溢出效应；特别是，政府的示范努力对这种效果有很大贡献，但充电设施的高可用性却没有；③这种溢出效应在经济水平较高的地区和气温较高的地区更为显著。我们的研究为电动汽车制造商确定电动汽车的进一步潜在市场提供了启示。

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引用次数: 0

The adoption of blockchain technology by green duopolistic firms: From Cournot to Bertrand competition 绿色双寡头企业对区块链技术的采用：从古诺到贝特朗竞争

IF 14.2 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2026-03-01 Epub Date: 2026-01-23 DOI: 10.1016/j.eneco.2026.109157

Xiaoyang Lei, Donghui Yang

Although firms have increasingly applied blockchain technology to facilitate consumers realizing the green investments of their products, the related literature is still rare. We investigate the blockchain adoption strategies of duopolistic firms that both exert green investments before engaging in Cournot competition or Bertrand competition. The findings are summarized as follows. First, when neither firm adopts blockchain technology under both competition models, the firms increase green investments with consumer green perception, which, however, does not inevitably lead to an increase in their profits. Second, the blockchain adoption strategies for both Cournot firms and Bertrand firms are closely correlated with the intensity of market competition and the unit cost of blockchain operation. For weak market competition, both firms (neither firm) will adopt blockchain technology when this unit cost remains rather low (high). Interestingly, one firm applies blockchain technology while the other abandons when the unit cost of blockchain operation is moderate even though these firms are symmetric. However, this asymmetric blockchain adoption strategy disappears for the fierce market competition. Finally, we reveal that Cournot firms are more (less) likely to adopt blockchain technology for the weak (fierce) market competition. These findings provide fresh managerial implications on blockchain adoption strategies for competitive firms under different competition models.

虽然企业越来越多地应用区块链技术来促进消费者实现其产品的绿色投资，但相关文献仍然很少。本文研究了双寡头企业在古诺竞争和贝特朗竞争中都进行绿色投资的区块链采用策略。研究结果总结如下。首先，在两种竞争模式下，当企业都不采用区块链技术时，企业增加绿色投资与消费者的绿色感知，但这并不必然导致企业利润的增加。其次，古诺公司和贝特朗公司的bbb采用策略与市场竞争强度和bbb运营的单位成本密切相关。在弱市场竞争条件下，当单位成本保持在较低（较高）水平时，两家企业（两家企业）都将采用区块链技术。有趣的是，即使这些公司是对称的，当区块链操作的单位成本适中时，一家公司使用区块链技术而另一家公司放弃。然而，这种不对称的区块链采用策略在激烈的市场竞争中消失了。最后，我们发现古诺企业在弱（激烈）市场竞争中更倾向于（不太）采用区块链技术。这些发现为不同竞争模式下竞争性企业采用区块链策略提供了新的管理启示。

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引用次数: 0