Energy Economics最新文献_第7页

Agent-based modeling of firm's heterogeneous preferences: Implications for trading and technology adoption in electricity-carbon markets 基于代理的企业异质偏好模型：对电力-碳市场交易和技术采用的影响

IF 13.6 2区经济学

Energy Economics Pub Date : 2025-06-24 DOI: 10.1016/j.eneco.2025.108688

Mei Wang , Songyuan Liu , Jiageng Liu , Zhengjun Li

{"title":"Agent-based modeling of firm's heterogeneous preferences: Implications for trading and technology adoption in electricity-carbon markets","authors":"Mei Wang , Songyuan Liu , Jiageng Liu , Zhengjun Li","doi":"10.1016/j.eneco.2025.108688","DOIUrl":"10.1016/j.eneco.2025.108688","url":null,"abstract":"<div><div>Firm preference and behavior significantly influence carbon market performance and emission reduction efficiency. This paper develops an electricity‑carbon coupled market model, integrating Agent-Based Modeling (ABM) and Multi-Agent Reinforcement Learning (MARL), to analyze the trading and investment behavior of heterogeneous firms in carbon markets. Using calibrated data from China's energy markets, the study uncovers four key findings. First, “compliance-based trading” behavior drives carbon price and volume surges near compliance deadlines. Second, large firms, with financial and technical advantages, act as first movers in adopting low-carbon technologies. Third, longer payback period reduces carbon prices but promote technological innovation, while stronger technology-oriented expectations boost trading activity, prices, and innovation. Fourth, trading preferences shape market outcomes: arbitrage firms increase short-term price volatility, risk-hedge firms stabilize markets and lead in innovation, and speculative firms strike a balance between price impacts and moderate innovation. Policy recommendations include extending payback period to ease financial pressures and encourage technology diffusion, leveraging large firms' resources while supporting smaller firms with fiscal incentives, and regulating arbitrage behavior during compliance periods to stabilize carbon markets.</div></div>","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"148 ","pages":"Article 108688"},"PeriodicalIF":13.6,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144502670","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

A strategic trading model under rate-based emissions trading schemes: Market power, driving factors, and a comparison with mass-based schemes 基于费率的排放交易计划下的战略交易模式：市场力量、驱动因素以及与基于大众的计划的比较

IF 13.6 2区经济学

Energy Economics Pub Date : 2025-06-24 DOI: 10.1016/j.eneco.2025.108665

Wenxin Geng , Ying Fan , Haoran Li , Xing Yao

{"title":"A strategic trading model under rate-based emissions trading schemes: Market power, driving factors, and a comparison with mass-based schemes","authors":"Wenxin Geng , Ying Fan , Haoran Li , Xing Yao","doi":"10.1016/j.eneco.2025.108665","DOIUrl":"10.1016/j.eneco.2025.108665","url":null,"abstract":"<div><div>Some evidence has shown the presence of strategic permit trading, which can reduce the cost-effectiveness of emissions trading schemes (ETSs). In contrast to most strategic trading models that focus on mass-based schemes and assume the existence of price-taking firms, in this study, we develop a two-stage model under a rate-based scheme where all firms are allowed to trade permits strategically by employing the supply function approach. We identify a unique refined equilibrium in permit trading and examine firms’ strategic behavior and the factors influencing market power. We find that both a flatter marginal production cost curve and a larger gap between firms’ emission intensities and the emission benchmark tend to strengthen market power. A similar impact is observed for permit sellers when marginal abatement costs are flatter, whereas the effect for buyers depends on a trade-off between the impact on permit purchases and the slope of the residual permit supply curve. We also conduct numerical simulations of China’s nationwide ETS. The results reveal that the effect of market power on production differs significantly between rate- and mass-based schemes. Additionally, rate-based schemes strengthen sellers’ market power relative to mass-based schemes. Finally, policy implications are proposed to prevent market power.</div></div>","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"148 ","pages":"Article 108665"},"PeriodicalIF":13.6,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144480775","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

Does access to credit promote the use of modern energy services? Evidence from rural Nigeria 获得信贷是否促进了现代能源服务的使用？来自尼日利亚农村的证据

IF 13.6 2区经济学

Energy Economics Pub Date : 2025-06-24 DOI: 10.1016/j.eneco.2025.108666

Abdou Salam Ndiaye

{"title":"Does access to credit promote the use of modern energy services? Evidence from rural Nigeria","authors":"Abdou Salam Ndiaye","doi":"10.1016/j.eneco.2025.108666","DOIUrl":"10.1016/j.eneco.2025.108666","url":null,"abstract":"<div><div>This study examines the impact of access to credit on the adoption of modern energy services among rural households in Nigeria. Using a panel dataset of 3380 households drawn from the General Household Survey (GHS), we apply Coarsened Exact Matching (CEM) to mitigate potential selection bias and Difference-in-Differences (DiD) estimation to address endogeneity concerns. The results reveal that access to credit has a modest yet statistically significant effect on the adoption of modern energy services. Further analysis indicates that this impact is concentrated in the uptake of three basic services: electric lighting, phone charging, and fan ventilation, suggesting that credit is primarily used to finance energy needs considered essential for daily living. Moreover, the source of credit emerges as an important factor, with formal and informal lenders influencing adoption outcomes differently. Beyond financial access, our findings underscore the importance of broader socioeconomic and infrastructural factors. Household wealth is a key determinant of energy service adoption, while the education level of the household head and the type of energy connection (on-grid vs. off-grid) also significantly shape adoption patterns. These insights highlight the multifaceted nature of energy access and suggest that credit interventions alone may be insufficient to drive comprehensive energy transitions in rural contexts.</div></div>","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"148 ","pages":"Article 108666"},"PeriodicalIF":13.6,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144480777","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

Peer effect matters for the adoption of new energy vehicles: Evidence from consumer sentiment analysis using Chat-GPT 同伴效应对新能源汽车采用的影响：基于Chat-GPT的消费者情绪分析证据

IF 13.6 2区经济学

Energy Economics Pub Date : 2025-06-24 DOI: 10.1016/j.eneco.2025.108692

Tong Fu , Shuyi Yu , Shiyu Tan

{"title":"Peer effect matters for the adoption of new energy vehicles: Evidence from consumer sentiment analysis using Chat-GPT","authors":"Tong Fu , Shuyi Yu , Shiyu Tan","doi":"10.1016/j.eneco.2025.108692","DOIUrl":"10.1016/j.eneco.2025.108692","url":null,"abstract":"<div><div>Although it is widely believed that reducing technological uncertainty can promote the adoption of new technologies, the mechanisms through which consumers perceive such reductions—and how these perceptions influence adoption decisions—remain underexplored. Utilizing Chat-GPT for sentiment analysis of online consumer reviews and treating consumer sentiment as a key measure of the peer effect, this study investigates the role of peer effects in mediating the causal relationship between technology uncertainty and the adoption of new energy vehicles (NEVs). The findings indicate that reducing technological uncertainty enhances both online word-of-mouth (active peer effects) and government procurement (passive peer effects), both of which facilitate greater NEVs adoption. Additionally, moderation effect analyses suggest that social trust amplifies the negative impact of technological uncertainty on NEV consumption intensity, thereby indirectly validating the role of peer effects in fostering NEV adoption. Ultimately, this research underscores that, even without government fiscal subsidies, peer effects can serve as a vital self-reinforcing mechanism in adopting green technologies.</div></div>","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"148 ","pages":"Article 108692"},"PeriodicalIF":13.6,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144513212","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

Regional rebound effects of energy efficiency improvements in a spatial general equilibrium framework 空间一般均衡框架下能源效率提高的区域回弹效应

IF 13.6 2区经济学

Energy Economics Pub Date : 2025-06-23 DOI: 10.1016/j.eneco.2025.108645

Tryfonas Christou , Patrizio Lecca , Simone Salotti

引用次数: 0

Multiscale extreme risk spillover between shipping and commodity markets: An analysis based on GARCH-Copula-CoVaR 航运与大宗商品市场的多尺度极端风险溢出：基于GARCH-Copula-CoVaR的分析

IF 13.6 2区经济学

Energy Economics Pub Date : 2025-06-23 DOI: 10.1016/j.eneco.2025.108564

Honghan Bei , Qian Wang , Xiaoxiao Yan , Xinpeng Geng

引用次数: 0

How to enhance China's total-factor energy efficiency via digital-real economy integration: New evidence from dynamic QCA analysis 如何通过数字与实体经济的融合提升中国全要素能源效率：来自动态QCA分析的新证据

IF 13.6 2区经济学

Energy Economics Pub Date : 2025-06-23 DOI: 10.1016/j.eneco.2025.108689

Kaijun Zhong, Yalin Lei, Jun Zhao, Yong Jiang

{"title":"How to enhance China's total-factor energy efficiency via digital-real economy integration: New evidence from dynamic QCA analysis","authors":"Kaijun Zhong, Yalin Lei, Jun Zhao, Yong Jiang","doi":"10.1016/j.eneco.2025.108689","DOIUrl":"10.1016/j.eneco.2025.108689","url":null,"abstract":"<div><div>In response to global climate challenges and China's regional energy efficiency disparities, this study identifies how digital-real economy integration (DRI) enhances total-factor energy efficiency (TFEE) through a novel dynamic qualitative comparative analysis (QCA) of 30 Chinese provinces (2012−2022). The findings reveal three key conclusions. First, while no single condition is strictly necessary for achieving high TFEE, the importance of digital infrastructure and digital finance has increased significantly. Digital infrastructure enhances energy efficiency by optimizing resource allocation and promoting industrial synergy, whereas digital finance contributes through green credit and capital optimization. Second, three primary DRI pathways for improving TFEE are identified: the digital industry-driven pattern, for regions with strong digital foundations but insufficient industrial agglomeration; the industrial synergy optimization pattern, for developed eastern regions; and the technology–capital–space interaction pattern, for areas with advanced green finance and concentrated industries. Third, Kruskal–Wallis rank–sum tests reveal that regional structural differences strongly influence digitalization and TFEE. Eastern regions lead due to policy support, resource allocation, industrial modernization, and talent advantages, whereas central and western regions face challenges such as weaker infrastructure, limited policy support, and slower digital transformation, resulting in unbalanced regional development.</div></div>","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"148 ","pages":"Article 108689"},"PeriodicalIF":13.6,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144517188","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

Artificial intelligence, digital inclusive finance, and financial performance: Dynamic threshold insights from renewable energy enterprises 人工智能、数字普惠金融与财务绩效：来自可再生能源企业的动态阈值洞察

IF 13.6 2区经济学

Energy Economics Pub Date : 2025-06-23 DOI: 10.1016/j.eneco.2025.108687

Wenwen Zhang , Shuai Fu , Yi-Bin Chiu , Cody Yu-Ling Hsiao

{"title":"Artificial intelligence, digital inclusive finance, and financial performance: Dynamic threshold insights from renewable energy enterprises","authors":"Wenwen Zhang , Shuai Fu , Yi-Bin Chiu , Cody Yu-Ling Hsiao","doi":"10.1016/j.eneco.2025.108687","DOIUrl":"10.1016/j.eneco.2025.108687","url":null,"abstract":"<div><div>With the widespread application of artificial intelligence (AI), industrial robots—being a typical example of AI technology—have provided new tools and opportunities for renewable energy enterprises. This paper uses data from 151 renewable energy enterprises and a dynamic panel threshold model to investigate the nonlinear effect of AI on financial performance of renewable energy enterprises and how this effect evolves with varying levels of digital inclusive finance. This paper finds that industrial robot installation exerts a U-shaped influence on renewable energy enterprises' financial performance, and industrial robot stock has a decreasing positive effect. Furthermore, industrial robots' influence on the financial performance of renewable energy enterprises varies by ownership type and scale. Additionally, at a high level of AI development, a high degree of digital inclusive finance amplifies the beneficial influence of industrial robot installation on the performance of renewable energy enterprises, while weakens the positive impact of industrial robot stock.</div></div>","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"148 ","pages":"Article 108687"},"PeriodicalIF":13.6,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144513196","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

Machine learning multi-objective optimization for time-dependent green vehicle routing problem 时变绿色车辆路径问题的机器学习多目标优化

IF 13.6 2区经济学

Energy Economics Pub Date : 2025-06-23 DOI: 10.1016/j.eneco.2025.108628

Sidonie Ienra Nyako , Dalila Tayachi , Fouad Ben Abdelaziz

{"title":"Machine learning multi-objective optimization for time-dependent green vehicle routing problem","authors":"Sidonie Ienra Nyako , Dalila Tayachi , Fouad Ben Abdelaziz","doi":"10.1016/j.eneco.2025.108628","DOIUrl":"10.1016/j.eneco.2025.108628","url":null,"abstract":"<div><div>This study explores the Multi-Objective Time-Dependent Green Vehicle Routing Problem (MOTDGVRP) within the framework of energy economics, focusing on optimizing fuel consumption and transportation efficiency. Our model minimizes total distance, transportation time, and fuel consumption, all of which are critical for reducing energy costs and environmental impact. We introduce methodologies for calculating travel time and fuel consumption, considering time-dependent speed variations across different periods. Key factors influencing fuel consumption include vehicle load, dynamic traffic speeds, and distance traveled, reflecting real-world energy use in logistics. Given the NP-hard nature of the problem, we employ Non-dominated Sorting Genetic Algorithm 2 (NSGA-2) and an NSGA-2 enhanced with Machine Learning (MLNSGA-2) to optimize routing decisions. The originality of this study lies in the integration of machine learning (ML) in vehicle routing optimization,which enhances solution quality and accelerates computational performance. While ML applications in routing are growing, their use in Vehicle Routing related models remains novel. Additionally, the model accounts for time-dependent speed variations, addressing real-world traffic dynamics that significantly impact fuel consumption and delivery efficiency. The combination of ML-enhanced optimization with time-sensitive routing presents a new approach to energy-efficient transportation. From an energy economics perspective, our findings provide valuable insights for optimizing energy use in logistics, reducing operational costs, and promoting sustainable transportation. The integration of machine learning-driven optimization offers a scalable method for enhancing energy efficiency in supply chains, contributing to both economic and environmental objectives.</div></div>","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"148 ","pages":"Article 108628"},"PeriodicalIF":13.6,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144472237","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

A comprehensive structural decomposition analysis of CO2 emissions from vessels: A case study of Japan 船舶二氧化碳排放的综合结构分解分析：以日本为例

IF 13.6 2区经济学

Energy Economics Pub Date : 2025-06-23 DOI: 10.1016/j.eneco.2025.108674

Taiga Shimotsuura

{"title":"A comprehensive structural decomposition analysis of CO2 emissions from vessels: A case study of Japan","authors":"Taiga Shimotsuura","doi":"10.1016/j.eneco.2025.108674","DOIUrl":"10.1016/j.eneco.2025.108674","url":null,"abstract":"<div><div>The increasing focus on zero-emission vessels highlights the need for environmental analyses from a life-cycle assessment perspective. The present study estimates the carbon footprint (CF) of maritime transport in Japan from 2005 to 2022 by assessing the full vessel life cycle, while excluding the end-of-life stage, under varying vessel lifespan scenarios. Furthermore, this study developed a comprehensive structural decomposition analysis (SDA) to quantify stakeholder contributions at detailed vessel life stages under different lifespan scenarios, thereby facilitating the development of more targeted policies. Extending the average vessel lifespan by 5 years results in a cumulative CF reduction of approximately 1.7 Mt-CO₂ compared to that in the baseline scenario, despite increased vessel repair demand. The SDA results demonstrated that shipyards and shipping companies contributed equally to CF reduction. Comparison of SDA across different lifespan scenarios revealed that lifespan extension is a crucial strategy for CF mitigation, suggesting the need to integrate current CF reduction measures with vessel lifespan extension to maximize environmental benefits.</div></div>","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"148 ","pages":"Article 108674"},"PeriodicalIF":13.6,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144472236","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