Energy Economics最新文献_第2页

Wealth maximisation and residential energy-efficiency retrofits: Insights from a real options model 财富最大化与住宅节能改造：实物期权模型的启示

IF 13.6 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2024-11-05 DOI: 10.1016/j.eneco.2024.108022

Anthony Britto, Joris Dehler-Holland, Wolf Fichtner

The slow adoption of residential energy-efficiency retrofits continues to hamper the energy transition. We study incentives for adoption by proposing a model of optimal investment under uncertainty where the wealth-maximising agent has the option to delay. Stochastic portfolio returns and energy prices are taken into account. An extension of the model where the energy carrier is switched, e.g. from gas to electricity, is also considered. Exercise boundaries for the optimal stopping problem are estimated numerically for recent case studies of German buildings. Investment is generally not optimal at current energy prices and market conditions. Increasing correlation between gas and electricity prices erodes the value of technology switching. Comparative statics reveal that energy-efficiency investments become optimal at relatively lower energy prices as wealth, income, and savings behaviour increase, and portfolio drift and volatility decrease. Consequently, incentive to invest in retrofits is far more heterogeneous along wealth dimensions than standard discounted cash flow analyses suggest. An examination of retrofit subsidies demonstrates how free-riding by wealthier agents occurs when subsidies are not appropriately targeted. We show that the pursuit of economic efficiency in subsidy design might have regressive effects on the wealth distribution.

住宅节能改造进展缓慢，继续阻碍着能源转型。我们提出了一个不确定性条件下的最优投资模型，在该模型中，财富最大化的代理人可以选择延迟投资，以此来研究采用节能技术的激励机制。该模型考虑了随机投资组合收益和能源价格。我们还考虑了该模型的扩展，即能源载体的转换，例如从天然气到电力的转换。针对最近的德国建筑案例研究，对最优停止问题的练习边界进行了数值估算。在当前的能源价格和市场条件下，投资通常不是最优的。天然气和电力价格之间的相关性不断增加，削弱了技术转换的价值。比较静态分析表明，随着财富、收入和储蓄行为的增加，以及投资组合漂移和波动的减少，在能源价格相对较低的情况下，节能投资成为最优选择。因此，投资节能改造的动机在财富方面的异质性远远大于标准贴现现金流分析所显示的。对节能改造补贴的研究表明，如果补贴的目标不明确，较富裕的主体就会搭便车。我们表明，在补贴设计中追求经济效益可能会对财富分配产生倒退效应。

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引用次数: 0

Aligning common prosperity with sustainable development goals 3 and 7 through sustainable insurance 通过可持续保险使共同繁荣与可持续发展目标 3 和 7 相一致

IF 13.6 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2024-11-05 DOI: 10.1016/j.eneco.2024.108033

Wei Zhou , Xuelian Li , Jyh-Horng Lin , Chuen-Ping Chang , Yujie Cai

This paper develops a capped-call option model to evaluate sustainable insurance for achieving common prosperity. It integrates policyholder protection (Sustainable Development Goal 3 (SDG 3)) and the cap-and-trade mechanism (SDG 7) in modeling the Gini coefficient, thereby connecting SDGs 3 and 7 with common prosperity. The main findings are as follows. Life insurance policies that prioritize saving features enhance policyholder protection (SDG 3) but can detract from common prosperity. This impact is magnified when the regulatory cap within the cap-and-trade scheme for carbon-intensive manufacturers becomes stricter. High investment risks for carbon-intensive manufacturers reduce policyholder protection but support common prosperity. A stricter cap-and-trade scheme (SDG 7) also reduces policyholder protection and contradicts common prosperity. This paper avoids concluding any inherent inconsistency between the SDGs and common prosperity, as our analysis is based on the structure-conduct-performance paradigm rather than a macro perspective. Policymakers should carefully balance objectives between SDG 3 and common prosperity to ensure that policies promoting individual security do not compromise broader societal well-being and economic equality, as outlined by the SDGs.

本文建立了一个上限-赎回期权模型，以评估实现共同繁荣的可持续保险。它将投保人保护（可持续发展目标 3）和限额交易机制（可持续发展目标 7）纳入基尼系数模型，从而将可持续发展目标 3 和 7 与共同繁荣联系起来。主要结论如下优先考虑储蓄功能的人寿保险政策可加强对投保人的保护（可持续发展目标 3），但会减损共同繁荣。当针对碳密集型制造商的限额与交易计划中的监管上限变得更加严格时，这种影响会被放大。碳密集型制造商的高投资风险降低了对投保人的保护，但支持了共同繁荣。更严格的总量控制与交易计划（可持续发展目标 7）也会减少对政策持有者的保护，并与共同繁荣相矛盾。本文避免得出可持续发展目标与共同繁荣之间存在内在矛盾的结论，因为我们的分析是基于结构-行为-绩效范式，而非宏观视角。决策者应谨慎平衡可持续发展目标 3 和共同繁荣之间的目标，以确保促进个人安全的政策不会损害可持续发展目标所概述的更广泛的社会福祉和经济平等。

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引用次数: 0

Domestic and foreign cap-and-trade regulations, carbon tariffs, and product tariffs during international trade conflicts: A multiproduct cost-efficiency analysis 国际贸易冲突中的国内外限额交易法规、碳关税和产品关税：多产品成本效益分析

IF 13.6 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2024-11-05 DOI: 10.1016/j.eneco.2024.108034

Yonghong Zhao , Fu-Wei Huang , Ching-Hui Chang , Jyh-Jiuan Lin

This paper develops a down-and-out call option model with structural breaks to examine the effects of domestic environmental policies on carbon-intensive firms amid international trade conflicts. The findings reveal that stricter cap-and-trade regulations, carbon tariffs, and product tariffs exacerbate pollutant-specific diseconomies of scale, limit economies of scope, and reduce firm equity. The positive impact on pollutant-specific diseconomies of scale leads to higher pollution, hindering progress toward Sustainable Development Goal 7 (SDG 7: Affordable and Clean Energy) from a multiproduct cost-efficiency perspective. Meanwhile, the negative impact on economies of scope results in fewer products and pollutants, aligning with SDG 7 but conflicting with Sustainable Development Goal 8 (SDG 8: Decent Work and Economic Growth), as the scope measure accounts for efficiency in both products and pollutants. Additionally, the negative impact on firm equity discourages progress toward both SDGs, especially during trade conflicts. In summary, environmental policies distinctly affect firm multiproduct cost efficiency and equity, particularly under varying trade conflict conditions.

本文建立了一个具有结构性中断的向下和向下看涨期权模型，以研究在国际贸易冲突中国内环境政策对碳密集型企业的影响。研究结果表明，更严格的总量控制与交易法规、碳关税和产品关税会加剧特定污染物的规模不经济，限制范围经济，并降低企业公平性。对特定污染物规模不经济的积极影响导致污染加剧，从多产品成本效益的角度来看，阻碍了可持续发展目标 7（SDG 7：负担得起的清洁能源）的实现。同时，对范围经济的负面影响导致产品和污染物减少，这与可持续发展目标 7 一致，但与可持续发展目标 8（可持续发展目标 8：体面工作和经济增长）相冲突，因为范围衡量标准同时考虑了产品和污染物的效率。此外，对企业公平性的负面影响阻碍了两个可持续发展目标的实现，尤其是在贸易冲突期间。总之，环境政策会明显影响企业的多产品成本效率和公平性，尤其是在不同的贸易冲突条件下。

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引用次数: 0

Bank-firm common ownership, green credit and enterprise green technology innovation: Evidence from Chinese credit markets 银行-企业共同所有权、绿色信贷与企业绿色技术创新：来自中国信贷市场的证据

IF 13.6 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2024-11-04 DOI: 10.1016/j.eneco.2024.108014

Minghao Liu , Kun Xu , Lihong Zhai

Bank-firm common ownership can tackle the innovation dilemma of bank loans on firms' green development. This paper constructs indicators of common ownership and green technological innovation and then investigates the impact of bank-firm common ownership on corporates' green technological innovation using Chinese A-share listed enterprises samples from 2004 to 2021. Our conducted experiments reveal that bank-firm common ownership shareholders not only make banks and lending firms have the same goal, promote the total level, quantity, and quality of technological innovation for the green development of lending firms, and profit from the firms' short- and long-term market responses. Our findings are prominent in private enterprises, small-capitalization enterprises, and bull market cycles. In addition, we discover that shareholder reduction restrictions and policies restricting corporate shareholding in financial institutions enhance bank-firm common ownership shareholders on corporate green technological innovation development. Common ownership shareholders reduce information asymmetry between banks and lending enterprises and provide green loans to support enterprise green technology innovations. Furthermore, alleviating financing constraints and strengthening the supervisory role are important influence mechanisms. In this regard, carried PSE analysis indicates the direct effect of bank-firm common ownership shareholders to promote enterprise green development of technological innovation accounts for about 41% of the total effect, the intermediary effect of “financing mechanism” and “supervision mechanism” account for about 50% and 9%, and the “financing mechanism” is more important than the “supervision mechanism.” The findings of this paper can optimize the credit market to serve the green and high-quality development of Chinese enterprises better.

银企共同持股可以解决银行贷款对企业绿色发展的创新困境。本文以 2004 年至 2021 年中国 A 股上市企业为样本，构建了共同持股和绿色技术创新指标，并研究了银企共同持股对企业绿色技术创新的影响。实验结果表明，银企共同持股不仅能使银行和贷款企业目标一致，促进贷款企业绿色发展的技术创新总量、数量和质量，还能从企业短期和长期的市场反应中获利。我们的研究结果在民营企业、小市值企业和牛市周期中表现突出。此外，我们还发现，金融机构的股东减持限制和公司持股限制政策增强了银行-企业共同持股股东对企业绿色技术创新发展的影响。共同持股股东减少了银行与贷款企业之间的信息不对称，为支持企业绿色技术创新提供了绿色贷款。此外，缓解融资约束和加强监管作用也是重要的影响机制。对此，进行的PSE分析表明，银企共同持股股东促进企业绿色发展技术创新的直接效应约占总效应的41%，"融资机制 "和 "监督机制 "的中介效应约占50%和9%，且 "融资机制 "比 "监督机制 "更重要。本文的研究结论可以优化信贷市场，更好地服务于中国企业的绿色发展和高质量发展。

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引用次数: 0

Does climate risk as barometers for specific clean energy indices? Insights from quartiles and time-frequency perspective 气候风险是特定清洁能源指数的晴雨表吗？从四分位数和时间频率角度看问题

IF 13.6 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2024-11-03 DOI: 10.1016/j.eneco.2024.108003

Hongjun Zeng , Mohammad Zoynul Abedin , Vineet Upreti

This study presents the first analysis of the nexus between the Southern Oscillation Index (SOI), a measure of climate risk, and segmented clean energy indices (such as solar, renewable, and bioenergy). Our research findings indicate that (i) the Granger quantile causality significance of SOI on segmented clean energy indices is asymmetric across different conditional quantiles. Significant predictability of SOI is observed only at the 0.25 and 0.75 quantile levels for all segmented clean energy indices, except for the WilderHill Clean Energy Index and NASDAQ OMX Fuel Cell Index. (ii) The clean energy market is significantly influenced by SOI under bullish market conditions. Impacts of SOI on all clean energy markets are nearly negligible when clean energy indices are at the median and lower quantile levels. (iii) The influence of strong La Niña episodes on segmented clean energy indices is more pronounced than during periods of intense El Niño phenomena. (iv) SOI exhibited a positive correlation at mid-term and long-term frequencies with segmented Clean Energy sectors, excluding bioenergy, for the majority of the sample period. Our conclusions provide deeper insights for investors managing clean energy investments in extreme climate conditions. Additionally, they offer useful information for policymakers to formulate viable economic policies addressing climate change, ensuring energy security, and facilitating a safer transition to clean energy.

本研究首次分析了衡量气候风险的南方涛动指数（SOI）与细分清洁能源指数（如太阳能、可再生能源和生物能源）之间的关系。我们的研究结果表明：(i) SOI 对细分清洁能源指数的格兰杰量级因果关系在不同条件量级之间是不对称的。除 WilderHill 清洁能源指数和纳斯达克 OMX 燃料电池指数外，所有细分清洁能源指数仅在 0.25 和 0.75 量级水平上观察到 SOI 的显著预测性。(ii) 在牛市条件下，清洁能源市场受到 SOI 的显著影响。当清洁能源指数处于中位数和低分位数水平时，SOI 对所有清洁能源市场的影响几乎可以忽略不计。(iii) 与强烈的厄尔尼诺现象相比，强烈的拉尼娜现象对分部清洁能源指数的影响更为明显。(iv) 在样本期的大部分时间里，SOI 在中期和长期频率上与除生物能源外的分部清洁能源行业呈正相关。我们的结论为投资者在极端气候条件下管理清洁能源投资提供了更深刻的见解。此外，这些结论还为政策制定者提供了有用的信息，帮助他们制定可行的经济政策来应对气候变化、确保能源安全并促进向清洁能源更安全的过渡。

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引用次数: 0

Predicting the volatility of major energy commodity prices: The dynamic persistence model 预测主要能源商品价格的波动：动态持续性模型

IF 13.6 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2024-11-02 DOI: 10.1016/j.eneco.2024.107982

Jozef Baruník , Lukáš Vácha

Time variation and persistence are crucial properties of volatility that are often studied separately in energy volatility forecasting models. Here, we propose a novel approach that allows shocks with heterogeneous persistence to vary smoothly over time, and thus model the two together. We argue that this is important because such dynamics arise naturally from the dynamic nature of shocks in energy commodities. We identify such dynamics from the data using localised regressions and build a model that significantly improves volatility forecasts. Such forecasting models, based on a rich persistence structure that varies smoothly over time, outperform state-of-the-art benchmark models and are particularly useful for forecasting over longer horizons.

时间变化和持续性是波动性的关键属性，在能源波动性预测模型中通常是分开研究的。在这里，我们提出了一种新方法，允许具有异质持续性的冲击随时间平滑变化，从而将两者结合起来建模。我们认为这一点非常重要，因为能源商品冲击的动态性质自然会产生这种动态变化。我们利用局部回归从数据中识别出了这种动态，并建立了一个能显著改善波动率预测的模型。这种预测模型基于随时间平滑变化的丰富持久性结构，其预测结果优于最先进的基准模型，尤其适用于较长时期的预测。

引用次数: 0

The service trade with AI and energy efficiency: Multiplier effect of the digital economy in a green city by using quantum computation based on QUBO modeling 人工智能与能源效率的服务贸易：基于 QUBO 模型的量子计算：绿色城市数字经济的乘数效应

IF 13.6 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2024-11-02 DOI: 10.1016/j.eneco.2024.107976

Da Huo , Wenjia Gu , Dongmei Guo , Aidi Tang

This research examines the energy efficiency of city districts through the Malmquist–DEA model and investigates the spatial effects of the service trade and the digital economy on energy efficiency in urban green development. The study also delves into the specific context of the AI service trade to gain insights into and align with the emerging digital intelligence industry. The interplay of the service trade with the digital economy, alongside the AI service trade with innovation, significantly enhances urban energy efficiency and demonstrates positive externalities. Building on the empirical findings, this research employs cluster analysis to explore the green development of city districts and uses AI technology to program green communication and cooperation mechanisms across district clusters, employing quantum computation based on QUBO modeling. This study contributes to a deeper understanding of the cofunction of the service trade and the digital economy in terms of energy efficiency and aids in developing new quality productivities for green cities through quantum-based AI advancements. This research has clear implications for cutting-edge interdisciplinary applications of green AI technologies in social computing science.

本研究通过 Malmquist-DEA 模型考察了城市地区的能源效率，并研究了服务贸易和数字经济对城市绿色发展中能源效率的空间效应。研究还深入探讨了人工智能服务贸易的具体背景，以深入了解并与新兴的数字智能产业接轨。服务贸易与数字经济以及人工智能服务贸易与创新的相互作用，大大提高了城市能效，并显示出积极的外部效应。在实证研究结果的基础上，本研究采用集群分析方法探索城市各区的绿色发展，并利用人工智能技术，在QUBO建模的基础上，运用量子计算，对各区集群的绿色交流与合作机制进行编程。这项研究有助于深入理解服务贸易和数字经济在能源效率方面的共同作用，并通过基于量子的人工智能进步，帮助绿色城市开发新的优质产品。这项研究对绿色人工智能技术在社会计算科学领域的前沿跨学科应用具有明确的意义。

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引用次数: 0

Key effects contributing to changes in energy imports in the EU-27 between 2000 and 2020: A decomposition analysis based on the Sankey diagram 2000 至 2020 年间欧盟 27 国能源进口变化的主要影响：基于桑基图的分解分析

IF 13.6 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2024-11-02 DOI: 10.1016/j.eneco.2024.108009

Rocío Román-Collado , Virginia Casado Ruíz

The aim of this paper is to analyse the key effects contributing to changes in energy imports in the European Union (EU-27) in the period 2000–2020. Using the Logarithmic Mean Divisia Index (LMDI), the analysis examines the effect of changes in six factors—energy structure, energy dependence, energy transformation efficiency, energy yield after transformation, energy efficiency and activity—on imports of oil, natural gas and other sources of energy. The results of the analysis reveal that the decarbonisation process has fostered the abandonment of the most polluting fossil fuel sources; however, there has been an increase in energy dependence on less polluting sources that are not produced domestically. In contrast, there has been an opportunity for change through improved energy efficiency, which has made it possible to reduce energy requirements per unit produced. In short, in order to achieve a sustainable and secure energy future, it is crucial to implement policies and actions that promote both the diversification of the energy mix—particularly renewable energies—and efficiency in consumption. Doing so will enable countries to move towards true decarbonisation and minimise vulnerability in their energy supply.

本文旨在分析 2000-2020 年间欧盟（EU-27）能源进口变化的主要影响因素。分析采用对数平均指数（LMDI），研究了能源结构、能源依赖性、能源转化效率、转化后的能源产量、能源效率和活动这六个因素的变化对石油、天然气和其他能源进口的影响。分析结果表明，去碳化进程促使人们放弃了污染最严重的化石燃料来源；然而，对国内不生产的污染较小来源的能源依赖性却在增加。与此相反，通过提高能源效率，有可能减少单位生产所需的能源，从而带来变革的机会。总之，为了实现可持续和安全的能源未来，必须实施促进能源组合多样化（特别是可再生能源）和提高消费效率的政策和行动。这样做将使各国实现真正的去碳化，并将能源供应的脆弱性降至最低。

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引用次数: 0

Forecasting carbon futures returns using feature selection and Markov chain with sample distribution 利用特征选择和带有样本分布的马尔可夫链预测碳期货收益率

IF 13.6 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2024-11-01 DOI: 10.1016/j.eneco.2024.107962

Yuan Zhao , Xue Gong , Weiguo Zhang , Weijun Xu

The accurate forecasting of carbon returns is paramount for enabling informed investment decisions, promoting emissions reduction, and effectively shaping policies to combat climate change. In this paper, we propose a novel method to improve carbon returns predictability in a data-rich environment. The innovations of the model are manifested in two key dimensions: (i) a feature selection strategy based on the minimum prediction error is introduced; (ii) a novel Markov chain with sample distribution considering both prediction and parameter estimation is proposed to quantify the error information and perfect the prediction performance by error modification. Our empirical findings demonstrate that the proposed model outperforms a comprehensive array of competing models, both in point and interval forecasting of carbon returns. The results are consistently confirmed in various robustness checks. Finally, we show that the enhanced prediction performance of the proposed model is economically significant, which can help investors make favorable decisions.

准确预测碳回报对于做出明智的投资决策、促进减排和有效制定应对气候变化的政策至关重要。在本文中，我们提出了一种在数据丰富的环境中提高碳收益可预测性的新方法。该模型的创新之处主要体现在两个方面：(i) 引入了基于最小预测误差的特征选择策略；(ii) 提出了一种同时考虑预测和参数估计的具有样本分布的新型马尔可夫链，以量化误差信息并通过误差修正完善预测性能。我们的实证研究结果表明，无论是在碳收益的点预测还是区间预测方面，所提出的模型都优于一系列竞争模型。这些结果在各种稳健性检验中得到了一致证实。最后，我们表明，所提模型的预测性能的提高具有重要的经济意义，可以帮助投资者做出有利的决策。

引用次数: 0

Renewable energy production across U.S. states: Convergence or divergence? 美国各州的可再生能源生产：趋同还是分歧？

IF 13.6 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2024-10-30 DOI: 10.1016/j.eneco.2024.108015

James E. Payne , James W. Saunoris , Saban Nazlioglu , Russell Smyth

This study explores the degree to which per capita aggregate renewable energy production is converging across U.S. states. Specifically, we examine both relative (club) convergence and weak σ-convergence. The results reject overall convergence in per capita aggregate renewable energy production for the panel of U.S. states, but identifies two convergence clubs. The results also suggest that there is considerable heterogeneity in the number of convergence clubs for the different subcomponents of per capita renewable energy production and consumption (biomass, geothermal, hydropower, solar and wind). We examine the factors which are associated with the emergence of the convergence clubs at the aggregate level. In the case of per capita aggregate renewable energy production, the average marginal effects from the logit analysis indicate that neighboring states with renewable portfolio standards, mandatory green power options, maximum effective retail rate increase, and per capita CO₂ emissions are associated with a higher likelihood of being in the convergence club with higher per capita renewable energy production. However, interconnection standards, having a public benefit fund, renewable energy certificates trading, compliance penalities, and per capita fossil fuel production are correlated with a lower likelihood of being in the convergence club with higher per capita renewable energy production. We also consider the factors correlated with convergence for the subcomponents of per capita renewable energy production and consumption, with the results suggesting considerable heterogeneity of the various factors at the subcomponent level.

本研究探讨了美国各州人均可再生能源总产量的趋同程度。具体而言，我们考察了相对（俱乐部）趋同和弱σ趋同。结果拒绝了美国各州人均可再生能源生产总量的总体趋同，但确定了两个趋同俱乐部。结果还表明，人均可再生能源生产和消费的不同分项（生物质能、地热能、水电、太阳能和风能）的趋同俱乐部数量存在相当大的异质性。我们研究了在总体水平上出现趋同俱乐部的相关因素。就人均可再生能源总产量而言，Logit 分析得出的平均边际效应表明，邻近州的可再生能源组合标准、强制性绿色电力选择、最高有效零售价涨幅和人均二氧化碳排放量都与更高的人均可再生能源产量相关。然而，互联标准、拥有公益基金、可再生能源证书交易、合规处罚和人均化石燃料产量与跻身人均可再生能源产量较高的趋同俱乐部的可能性较低相关。我们还考虑了与人均可再生能源生产量和消费量子项趋同相关的因素，结果表明，在子项层面，各种因素之间存在相当大的异质性。

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引用次数: 0