Energy Economics最新文献_第5页

Intellectual property protection, green technology innovation, and energy transition: An evolutionary game analysis 知识产权保护、绿色技术创新与能源转型：一个演化博弈分析

IF 14.2 2区经济学

Energy Economics Pub Date : 2025-09-18 DOI: 10.1016/j.eneco.2025.108901

Wenhao Du , Qizhi He , Junjun Wu

{"title":"Intellectual property protection, green technology innovation, and energy transition: An evolutionary game analysis","authors":"Wenhao Du , Qizhi He , Junjun Wu","doi":"10.1016/j.eneco.2025.108901","DOIUrl":"10.1016/j.eneco.2025.108901","url":null,"abstract":"<div><div>This paper develops an evolutionary game model of heterogeneous firms operating under an intellectual property (IP) protection regime to analyze the co-evolutionary mechanisms and micro-level decision thresholds through which IP protection facilitates green technological innovation and energy transition. The results indicate that achieving a desirable equilibrium of effective protection, active innovation, and accelerated transition relies on the coordinated implementation of three policy instruments: IP protection, innovation subsidies, and environmental regulation. The absence or misalignment of any policy tool may lead the system to an undesirable equilibrium marked by transition stagnation. An optimal threshold for IP enforcement intensity is identified. This threshold is negatively correlated with enforcement costs at the institutional level but positively correlated with the economic benefits and life cycle of green technologies at the technological level. The follower firm exhibits the slowest innovation response, and its sustained innovation depends on a compensatory policy mix that combines IP enforcement with innovation subsidies. While higher prices for green technologies incentivize R&D, they also hinder diffusion. This study fills a theoretical gap in the literature concerning the multi-agent interaction mechanisms guiding energy transition through innovation institutions and provides a theoretical foundation for constructing a green-oriented IP policy system.</div></div>","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"151 ","pages":"Article 108901"},"PeriodicalIF":14.2,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145156503","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Mapping the impact of artificial intelligence on energy poverty: New evidence from spatial panel models 绘制人工智能对能源贫困的影响：来自空间面板模型的新证据

IF 14.2 2区经济学

Energy Economics Pub Date : 2025-09-18 DOI: 10.1016/j.eneco.2025.108909

Manuel A. Zambrano-Monserrate

{"title":"Mapping the impact of artificial intelligence on energy poverty: New evidence from spatial panel models","authors":"Manuel A. Zambrano-Monserrate","doi":"10.1016/j.eneco.2025.108909","DOIUrl":"10.1016/j.eneco.2025.108909","url":null,"abstract":"<div><div>Energy poverty remains a critical challenge for sustainable development, particularly in low- and middle-income countries. As countries seek innovative solutions to expand energy access, artificial intelligence (AI) has emerged as a promising tool. While recent studies have explored the role of AI in improving energy access, few have considered its spatial effects. Therefore, this paper investigates how AI adoption affects energy poverty using a spatial panel dataset of 64 countries from 2010 to 2019. Spatial econometric models reveal that higher AI adoption is significantly associated with reductions in energy poverty and that these benefits extend beyond national borders through regional spillovers. Mediation analysis shows that technological innovation, proxied by patent activity, partially transmits the impact of AI, while moderation analysis reveals that the effect of AI is stronger in less urbanized settings and where public spending is relatively low. These findings provide the first empirical evidence of spatial dependence in the AI–energy poverty nexus and highlight the importance of designing targeted, regionally coordinated policies. Thus, promoting AI-enabled off-grid solutions and strengthening innovation systems could help reduce spatial disparities in energy access, especially when embedded within broader international partnerships and adaptive national energy policies.</div></div>","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"151 ","pages":"Article 108909"},"PeriodicalIF":14.2,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145110057","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The impact of corporate taxes on (renewable) power generation capacity 公司税对（可再生）发电能力的影响

IF 14.2 2区经济学

Energy Economics Pub Date : 2025-09-18 DOI: 10.1016/j.eneco.2025.108910

Niklas Meyer , Thorben Wulff

{"title":"The impact of corporate taxes on (renewable) power generation capacity","authors":"Niklas Meyer , Thorben Wulff","doi":"10.1016/j.eneco.2025.108910","DOIUrl":"10.1016/j.eneco.2025.108910","url":null,"abstract":"<div><div>Using granular data on power-generating assets and rich variation in local business tax rates in Germany, we find that corporate taxes decrease the installed power generation gross capacity in a given municipality. A one standard deviation increase in local business tax rates is associated with a 3 % decrease in renewable power generation and an 11 % decrease in non-renewable power generation in the respective municipality vis-à-vis other municipalities in the same district without a tax increase. Non-taxable entities and state-owned enterprises do not show such investment response. In conservative political environments, this effect is more (less) pronounced for renewable (non-renewable) energy capacity. Our results suggest that increases in corporate tax rates may have unintended consequences for the green transition, hampering the <em>absolute</em> expansion of renewable energy. At the same time, our results suggest that corporate taxes decrease investment in non-renewable energy <em>relatively</em> more, highlighting the importance of examining differential investment effects of corporate taxes and their implications for tax policy in the energy transition.</div></div>","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"151 ","pages":"Article 108910"},"PeriodicalIF":14.2,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145156505","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Investment in new oil & gas assets: The effect of energy-related uncertainty and climate policy 新油气资产投资：能源不确定性和气候政策的影响

IF 14.2 2区经济学

Energy Economics Pub Date : 2025-09-18 DOI: 10.1016/j.eneco.2025.108917

Christian Wilson, Gireesh Shrimali, Ben Caldecott

引用次数: 0

The coal phase-out in Germany and Central Western Europe under new framework conditions 在新的框架条件下，德国和中欧西欧逐步淘汰煤炭

IF 14.2 2区经济学

Energy Economics Pub Date : 2025-09-18 DOI: 10.1016/j.eneco.2025.108886

Jonas Egerer, Veronika Grimm, Lukas Maximilian Lang, Ulrike Pfefferer

{"title":"The coal phase-out in Germany and Central Western Europe under new framework conditions","authors":"Jonas Egerer, Veronika Grimm, Lukas Maximilian Lang, Ulrike Pfefferer","doi":"10.1016/j.eneco.2025.108886","DOIUrl":"10.1016/j.eneco.2025.108886","url":null,"abstract":"<div><div>Emission reduction targets require a transformation of the European electricity system. In particular, emission-intensive conventional power plants have to be phased out. How far the transformation can succeed already by 2030 remains unclear and depends on multiple framework conditions. To shed light on this in some detail, we analyze the Market driven coal phase-out in Central Western Europe and the role of gas-fired power plants as well as electrolysis and battery capacity in the year 2030 in an electricity market model. Our model approach allows endogenous decisions on investment and decommissioning for fossil power plants, electrolysis capacity and batteries according to short-term market results with decisions on generation levels, short- and long-term storage operation and hydrogen production. We consider various scenarios with regard to CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> prices and the expected increase of electricity demand in Europe with a focus on Germany, for which a regulatory forced coal phase-out as early as 2030 is also considered. The results illustrate how the expansion of renewable energy sources reduces the capacity of fossil power plants needed in 2030 and, depending on the assumptions regarding electricity demand and the emission price, investments in gas-fired power plants and battery capacity lead to additional decommissioning of coal-fired power plants. National plans for the phase-out of coal-fired power generation as early as 2030 in Germany lead to some cross-border effects in capacity, but production levels and market prices are not significantly affected.</div></div>","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"151 ","pages":"Article 108886"},"PeriodicalIF":14.2,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145242026","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Energy commodities and calendar spread options 能源大宗商品和日历价差期权

IF 14.2 2区经济学

Energy Economics Pub Date : 2025-09-17 DOI: 10.1016/j.eneco.2025.108809

Carme Frau , Gianluca Fusai , Ioannis Kyriakou

引用次数: 0

Greener for greater security? The role of green finance in energy security amid rising geopolitical risks 更环保更安全？地缘政治风险上升背景下绿色金融在能源安全中的作用

IF 14.2 2区经济学

Energy Economics Pub Date : 2025-09-15 DOI: 10.1016/j.eneco.2025.108902

Duc Hong Vo , Chi Minh Ho , Ngoc Duc Lang

{"title":"Greener for greater security? The role of green finance in energy security amid rising geopolitical risks","authors":"Duc Hong Vo , Chi Minh Ho , Ngoc Duc Lang","doi":"10.1016/j.eneco.2025.108902","DOIUrl":"10.1016/j.eneco.2025.108902","url":null,"abstract":"<div><div>Energy security is an undeniably crucial factor in economies' stable functioning and societies' well-being. However, global energy security has been continuously threatened by adverse geopolitical events. This study is conducted to examine if green finance can be an effective tool to improve energy security and, if so, whether green finance can act as a shield against geopolitical risk using a sample of 37 countries from 2013 to 2018. Our analysis is also extended to use another proxy of energy security for 36 countries in an extended and updated period from 2013 to 2022. Our results show that green finance can significantly reduce energy security risks worldwide. Furthermore, our heterogeneity analysis shows that the impact of green finance on energy security risks is also more substantial in the OECD (IEA) countries than in non-OECD (non-IEA) countries. Results from the panel quantile regression also show that the impact of green finance is heterogeneous and significant across different quantiles of energy security. This finding suggests a V-shaped pattern from the effect of green finance, indicating that countries with either very high or very low levels of energy security risk benefit the most from green finance. Interestingly, when green finance is considered a moderator in the effect of geopolitical risk on energy security, we find that green finance acts as a shield against the adverse impacts of increasing geopolitical risk. Our results are robust against endogeneity and largely unchanged across different estimations. Important policy implications have emerged from our findings.</div></div>","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"151 ","pages":"Article 108902"},"PeriodicalIF":14.2,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145110056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Modeling the economic and environmental effects of ESG preferences: A general equilibrium approach ESG偏好的经济和环境影响建模：一般均衡方法

IF 14.2 2区经济学

Energy Economics Pub Date : 2025-09-15 DOI: 10.1016/j.eneco.2025.108897

Mingke Wang, Weixian Wei

{"title":"Modeling the economic and environmental effects of ESG preferences: A general equilibrium approach","authors":"Mingke Wang, Weixian Wei","doi":"10.1016/j.eneco.2025.108897","DOIUrl":"10.1016/j.eneco.2025.108897","url":null,"abstract":"<div><div>This study develops a multi-sector Dynamic Stochastic General Equilibrium (DSGE) model encompassing households, intermediate goods producers (brown and green firms), final goods producers, a central bank, and a central government. It systematically examines the dynamic transmission mechanisms through which ESG preferences influence firm-level input-output relationships and carbon emissions. The model incorporates three innovative elements: the disutility of carbon emissions on social welfare, explicit differentiation of transmission pathways between brown and green firms, and reconceptualized firm-level ESG incentives. Simulation analyses of four distinct shocks—household green investment preference, brown firm collateral ratio, emission reduction effort, and emission tax—reveal several key dynamics. Notably, while increased household green investment preference leads to a short-term decline in brown firms’ brown investment, such investment gradually recovers in the long term, and emission stocks still see a reduction. Although heightened market expectations regarding brown firms’ ESG performance can boost their output, they may weaken their motivation to reduce emissions and exacerbate pollution. Meanwhile, while enhanced emission reduction efforts improve the environment in the short term, they exert a sustained dampening effect on investment in green firms. Furthermore, emission tax increases yield long-term benefits for green firms and the environment, despite exerting persistent negative impacts on brown firms. This research establishes a dynamic analytical framework for assessing the economic and environmental impacts of ESG investment, providing significant theoretical insights for advancing sustainable finance and optimizing emission reduction policies.</div></div>","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"151 ","pages":"Article 108897"},"PeriodicalIF":14.2,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145093857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Effect of grid expansion on interregional power dispatch towards carbon neutrality based on market equilibrium model 基于市场均衡模型的电网扩张对区域间碳中和电力调度的影响

IF 14.2 2区经济学

Energy Economics Pub Date : 2025-09-14 DOI: 10.1016/j.eneco.2025.108900

Bai-Chen Xie , Yan-Shen Yang , Xian-Peng Chen

{"title":"Effect of grid expansion on interregional power dispatch towards carbon neutrality based on market equilibrium model","authors":"Bai-Chen Xie , Yan-Shen Yang , Xian-Peng Chen","doi":"10.1016/j.eneco.2025.108900","DOIUrl":"10.1016/j.eneco.2025.108900","url":null,"abstract":"<div><div>China has introduced a national interconnected power market to achieve carbon neutrality. It can effectively enhance the variable renewable energy integration by promoting power sharing mechanism. However, grid expansion to transmit more power from resource-rich regions increases the difficulty of maintaining a stable power supply. In this study, we employed a high-resolution power market equilibrium model to explore the interaction between grid expansion and interregional power dispatch to examine the impacts of grid expansion on the transmission volume, power supply, and price changes. We get several important insights from this study. First, a positive correlation exists between the transmission capacity and interregional power dispatch. Enhanced transmission line expansion increases interregional power transactions by approximately 90 %. Second, grid extension enables a broader power supply source. It has a prominent role in maintaining the power supply and enhancing renewable power absorption, especially in the case of power shortages. Third, the grid extension and interregional power transactions narrow the price gap among provinces. The economically developed provinces have experienced power price reductions of up to around 6 %, whereas local prices increase by up to around 4 % in resource-rich provinces. These results can give references for the power market design and transmission line planning, which provide valuable implications for policymakers.</div></div>","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"151 ","pages":"Article 108900"},"PeriodicalIF":14.2,"publicationDate":"2025-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145218050","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

AI-driven hypergraph neural network for predicting gasoline price trends 用于预测汽油价格趋势的人工智能驱动超图神经网络

IF 14.2 2区经济学

Energy Economics Pub Date : 2025-09-13 DOI: 10.1016/j.eneco.2025.108895

Peng Zhu, Xiaotian Chen, Ziyi Zhang, Peishan Li, Xi Cheng, Yucheng Dai

{"title":"AI-driven hypergraph neural network for predicting gasoline price trends","authors":"Peng Zhu, Xiaotian Chen, Ziyi Zhang, Peishan Li, Xi Cheng, Yucheng Dai","doi":"10.1016/j.eneco.2025.108895","DOIUrl":"10.1016/j.eneco.2025.108895","url":null,"abstract":"<div><div>Accurate gasoline price trend forecasting is crucial for policymaking, risk management, and maintaining international trade balances. Despite advances, existing artificial intelligence (AI) deep learning models often fail to fully address the complex multifactor interactions behind gasoline price fluctuation and lack interpretability. This study introduces a hypergraph neural network (TADHGCN) model with temporal attention embedding to examine these higher-order interactions and extract time-dependent information effectively. We also integrate SHAP (SHapley Additive exPlanations) for interpretability to enable the exploration of how various factors influence gasoline price predictions. We validate the proposed model using gasoline price data from the United States. Energy Information Administration, from January 1995 to February 2011. Empirical results demonstrate that the proposed model improves accuracy by 6.35% compared with the state-of-the-art benchmark, and the model’s robustness is verified by ablation study. Gasoline sales volume and finished gasoline inventories are identified as key drivers of price movement wherein sales volume has a positive impact, while inventories exert a negative effect. The TADHGCN model with time-series attention and SHAP analysis provide accurate price trend forecasts and offer valuable insights into the contributing factors. This study provides both theoretical and practical guidance for anticipating gasoline price fluctuations more accurately.</div></div>","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"151 ","pages":"Article 108895"},"PeriodicalIF":14.2,"publicationDate":"2025-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145093850","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0