Energy Economics最新文献_第8页

How can China's healthy city pilot policy improve energy efficiency? Insights from difference-in-differences and double/debiased machine learning approaches 中国健康城市试点政策如何提高能源效率？来自差异中的差异和双重/去偏见机器学习方法的见解

IF 14.2 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2025-12-30 DOI: 10.1016/j.eneco.2025.109119

Zihao Zhou , Shanlang Lin , Zhan He , Xiaoming Zhang , Sutong Chen , Junpei Huang

Improving energy efficiency (EE) is a critical pathway toward resource conservation and urban environmental sustainability. While healthy city initiatives have been acknowledged for their positive environmental and public health outcomes, their implications for urban EE have received limited empirical attention. This study takes China's healthy city pilot (HCP) policy as a quasi-natural experiment to investigate how the HCP policy affects EE. Using panel data from 282 prefecture-level cities between 2006 and 2023, we employ a difference-in-differences (DID) approach and a double/debiased machine learning (DDML) method to ensure robust causal identification. The relevant results are threefold. (1) The HCP policy significantly improves EE in pilot cities, which is driven by increased clean energy adoption, enhanced green technology innovation capabilities, improved public transportation services, and raised public environmental awareness. (2) The result of moderating effect analysis reveals that government environmental regulation can amplify pilot cities' energy transition effect. (3) HCP policy implementation widens regional disparities in EE across pilot cities, exhibiting a Matthew effect, with greater benefits observed in cities with lower resource dependence, better healthcare, stronger digital economies, and more developed green foundations. We propose that alongside expanding healthy city initiatives informed by policy experience, governments should strengthen policy support for underdeveloped cities with weak environmental and economic foundations to advance the Healthy China strategy.

提高能源效率是实现资源节约和城市环境可持续发展的重要途径。虽然健康城市倡议因其积极的环境和公共卫生成果而得到认可，但其对城市EE的影响却受到有限的实证关注。本研究以中国健康城市试点（HCP）政策为准自然实验，探讨健康城市试点政策对情感表达的影响。利用2006年至2023年间282个地级市的面板数据，我们采用了差分法（DID）和双/去偏机器学习（DDML）方法来确保稳健的因果识别。相关的结果有三个方面。(1) HCP政策显著提高了试点城市的能效，这主要得益于清洁能源采用率的提高、绿色技术创新能力的增强、公共交通服务的改善和公众环保意识的提高。(2)调节效应分析结果表明，政府环境规制可以放大试点城市的能源转型效应。(3) HCP政策的实施扩大了试点城市环境友好度的区域差异，呈现马太效应，资源依赖度较低、医疗条件较好、数字经济实力较强、绿色基础较发达的城市环境友好度受益更大。我们建议各国政府在总结政策经验的基础上，在扩大健康城市倡议的同时，加强对环境和经济基础薄弱的欠发达城市的政策支持，以推进“健康中国”战略。

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引用次数: 0

Time segmentation in tanker freight markets: The role of risk and relative freight rates in switching decisions 油轮货运市场的时间分割：风险和相对运价在转换决策中的作用

IF 14.2 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2025-12-26 DOI: 10.1016/j.eneco.2025.109110

Manolis G. Kavussanos, Stergiani (Stella) A. Moysiadou, Dimitris A. Tsouknidis

This paper investigates the influence of macroeconomic and market-related factors on the chartering decisions of shipowners in the tanker segment of the ocean-going maritime industry. It introduces a methodological framework, which for a particular vessel type, highlights segmentation in the freight market based on contract duration. According to this framework, shipowners select charter contracts aligned with their risk preferences and strategic objectives, leading them to operate within a preferred “habitat” time-segment of the freight market -namely, the short-term spot market (single-voyage contracts), medium-term, or long-term time charters. A novel contribution of this study is the incorporation of global as well as shipping industry-specific risk factors. They include the risk aversion index developed by Bekaert et al. (2022), freight and crude oil price volatilities. The paper demonstrates that both global and industry specific risk factors in conjunction with relative freight rate differentials across contract durations significantly influence shipowners' selection of charter length and their potential transitions between different time-segments of the market. Using a unique dataset of 33,564 individual freight fixtures for crude oil tankers over a nine-year period, the study finds that the dominant “habitat” for VLCC and Suezmax tanker operators is the spot market, revealing a low level of risk aversion among market participants. However, changes in perceived risk and in relative freight rates can prompt temporary deviations from their preferred time-segment. The findings are in line with standard economics and finance theories and common shipping practice.

本文研究了宏观经济因素和市场相关因素对远洋航运业油轮行业船东租船决策的影响。它引入了一个方法框架，该框架针对特定的船舶类型，突出了基于合同期限的货运市场细分。根据这一框架，船东根据其风险偏好和战略目标选择租船合同，从而使他们在货运市场的首选“栖息地”时间段内运营，即短期现货市场（单次航程合同）、中期或长期租船。本研究的一个新颖贡献是纳入了全球以及航运业特定的风险因素。它们包括Bekaert et al.（2022）开发的风险规避指数、运费和原油价格波动。本文表明，全球和行业特定的风险因素，以及不同合同期限的相对运费差异，都显著影响了船东对租船期限的选择，以及他们在不同市场时间段之间的潜在转变。该研究使用了一个独特的数据集，该数据集包含了9年期间33564艘原油油轮的单独货运固定设备，研究发现，VLCC和苏伊士型油轮运营商的主要“栖息地”是现货市场，这表明市场参与者的风险厌恶程度较低。然而，感知到的风险和相对运费的变化可能促使他们暂时偏离他们喜欢的时间段。研究结果与标准的经济学和金融学理论以及常见的航运实践相一致。

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引用次数: 0

Can policy achieve environmental improvement? Evidence from the whole county photovoltaic project in China 政策能改善环境吗？来自中国全县光伏项目的证据

IF 14.2 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2025-12-26 DOI: 10.1016/j.eneco.2025.109100

Wanhai You , Chenyao Fang , Yawei Guo , Shijing Nan

To facilitate the transition to clean energy and promote sustainable development, China's National Energy Administration issued the “Notice on the Publication of the County Wide Rooftop Distributed Solar Photovoltaic Development Pilot Project List” (also known as China's Whole County Photovoltaic Project). Using county-level panel data spanning May 2014 to September 2022, this study treats the initiative as an exogenous policy shock and employs a Difference-in-Differences (DID) design to assess its impact on environmental pollution. Empirical results indicate that the pilot policy significantly mitigates environmental pollution; this finding is further confirmed by a battery of robustness tests. Additionally, the mechanism analysis indicates that the project mitigates environmental pollution by facilitating public investment and driving green technological innovation. Furthermore, the heterogeneity analysis reveals that the pollution reduction effect is more pronounced in non-provincial capital, non-resource-based and western counties. Finally, we assess the heterogeneous effects using unconditional quantile regression (UQR). The results demonstrate that the significant impact is driven entirely by counties at the highest quantiles of pollution. Our findings offer valuable insights for policymakers in other countries aiming to advance energy transitions and mitigate environmental pollution.

为促进向清洁能源转型，促进可持续发展，国家能源局发布了《关于公布全县屋顶分布式太阳能光伏发展试点项目名单的通知》（又称全县光伏项目）。本研究使用2014年5月至2022年9月的县级面板数据，将该倡议视为外生政策冲击，并采用差分法（DID）设计评估其对环境污染的影响。实证结果表明，试点政策显著缓解了环境污染；一系列稳健性测试进一步证实了这一发现。机制分析表明，该项目通过促进公共投资和推动绿色技术创新来缓解环境污染。异质性分析表明，非省会城市、非资源型和西部地区的污染减排效果更为显著。最后，我们使用无条件分位数回归（UQR）评估异质性效应。结果表明，显著影响完全是由污染最高分位数的县驱动的。我们的研究结果为旨在推进能源转型和减轻环境污染的其他国家的政策制定者提供了有价值的见解。

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引用次数: 0

Interactions between multiple environmental markets: addressing contamination bias in overlapping policies 多重环境市场之间的相互作用：解决重叠政策中的污染偏差

IF 14.2 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2025-12-24 DOI: 10.1016/j.eneco.2025.109094

Tiantian Yang , Richard S.J. Tol

To address the dual environmental challenges of pollution and climate change, China has established multiple environmental markets, including pollution emissions trading, carbon emissions trading, energy-use rights trading, and green electricity trading. Previous empirical studies suffer from known biases arising from time-varying treatment and multiple treatments. To address these limitations, this study adopts a dynamic control group design and combines Difference-in-Differences (DiD) and Artificial Counterfactual (ArCo) empirical strategies. Using panel data on A-share listed companies from 2000 to 2024, this study investigates the marginal effects and interactive impacts of multiple environmental markets implemented in staggered and overlapping phases. Existing pollution emissions trading mitigates the negative effects of carbon emission trading. Carbon trading suppresses (improves) financial performance (if implemented alongside energy-use rights trading). The addition of energy-use rights or green electricity trading in regions already covered by carbon or pollution markets has no significant effects.

为应对污染和气候变化的双重环境挑战，中国建立了多种环境市场，包括污染排放权交易、碳排放权交易、能源使用权交易和绿色电力交易。以往的实证研究存在时变处理和多重处理的已知偏差。为了解决这些局限性，本研究采用动态控制组设计，并结合差分中的差分（DiD）和人工反事实（ArCo）实证策略。本文利用2000 - 2024年a股上市公司的面板数据，研究了在交错和重叠阶段实施的多重环境市场的边际效应和交互影响。现有的污染排放权交易缓解了碳排放权交易的负面影响。碳交易抑制（改善）财务绩效（如果与能源使用权交易一起实施）。在已经被碳排放或污染市场覆盖的地区增加能源使用权或绿色电力交易没有显著效果。

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引用次数: 0

Market structure and technology adoption in renewable energy 可再生能源的市场结构和技术采用

IF 14.2 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2025-12-24 DOI: 10.1016/j.eneco.2025.109109

Gaurav Doshi , Sarah Johnston

We study the effect of market structure on technology adoption in the U.S. solar and wind power industries. We compare adoption across two market types: restructured markets, which are designed to promote competition, and regulated markets, which are dominated by regulated monopolists. Solar projects in restructured markets are 32 percent less likely to adopt frontier technology. We also find negative effects of restructuring on adoption for wind projects. We provide evidence that this negative relationship between competition and technology adoption is explained by differences in financing costs across the two market types.

我们研究了市场结构对美国太阳能和风能产业技术采用的影响。我们比较了两种市场类型的采用情况：旨在促进竞争的重组市场和受监管的市场，后者由受监管的垄断者主导。重组市场中的太阳能项目采用前沿技术的可能性降低了32%。我们还发现了重组对风电项目采用的负面影响。我们提供的证据表明，竞争与技术采用之间的这种负相关关系可以通过两种市场类型之间融资成本的差异来解释。

引用次数: 0

Economic emission dispatching strategy considering dynamic parameter effects: A novel approach based on projection neural networks and deep learning 考虑动态参数影响的经济排放调度策略：基于投影神经网络和深度学习的新方法

IF 14.2 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2025-12-24 DOI: 10.1016/j.eneco.2025.109104

Xueying Liu, You Zhao, Xing He

The economic emission dispatch (EED) problem is influenced by dynamic parameters such as power demand and climatic factors affecting renewable energy (RES) generation, which adds to the complexity of the dispatch process. Constrained by the serial iterative computing architecture, conventional optimization algorithms often face the challenges such as long computation time and computational inefficiency caused by repeated solving when dealing with EED involving continuous changes in dynamic parameters. To address the problem, this paper combines projection neural network (PNN) and deep learning to cope with the effect of dynamic parameters on the EED. First, a deep PNN (DPNN) is proposed by embedding PNN in deep learning. Then, the dynamic parameters in the EED are taken as input variables to the DPNN. Compared to PNN, DPNN do not require iterations and can respond immediately to dynamic parameter changes to directly provide predicted solutions for EED, which allows the DPNN reduce computation time and improve computational efficiency. Simulation results show that compared with PNN and convex solvers, DPNN can significantly reduce the computation time with good computational performance and can be adapted to EED problems containing dynamic parameters.

经济排放调度问题受电力需求和影响可再生能源发电的气候因素等动态参数的影响，增加了调度过程的复杂性。传统优化算法在处理动态参数连续变化的动态环境时，受串行迭代计算架构的限制，往往面临计算时间长、反复求解效率低的挑战。为了解决这一问题，本文将投影神经网络（PNN）与深度学习相结合，以应对动态参数对EED的影响。首先，通过将PNN嵌入到深度学习中，提出了一种深度PNN （DPNN）。然后，将EED中的动态参数作为DPNN的输入变量。与PNN相比，DPNN不需要迭代，可以立即响应动态参数变化，直接为EED提供预测解，从而减少了计算时间，提高了计算效率。仿真结果表明，与PNN和凸求解器相比，DPNN能显著缩短计算时间，具有良好的计算性能，能够适应包含动态参数的EED问题。

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引用次数: 0

Green bubbles: A four-stage paradigm for detection and propagation 绿色气泡：检测和传播的四阶段范式

IF 14.2 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2025-12-23 DOI: 10.1016/j.eneco.2025.109095

Gian Luca Vriz , Luigi Grossi

Climate change has emerged as a significant global concern that is attracting increasing attention worldwide. Although green bubbles may be examined through a social bubble hypothesis, it is essential not to neglect a “Climate Minsky” moment triggered by sudden asset price changes. The significant increase in green investments highlights the urgent need for a comprehensive understanding of these market dynamics. Therefore, the present paper introduces a novel paradigm for studying such phenomena.

Focusing on the renewable energy sector, change point detection models are employed to identify green bubbles within time series data. Furthermore, search volume indexes and social factors are incorporated into established econometric models to reveal potential implications for the financial system. Inspired by Joseph Schumpeter’s perspectives on business cycles, this study recognizes green bubbles as a “necessary evil” for facilitating a successful transition towards a more sustainable future.

气候变化已成为全球关注的重大问题，在世界范围内引起越来越多的关注。虽然绿色泡沫可以通过社会泡沫假说来检验，但重要的是不要忽视由资产价格突然变化引发的“气候明斯基”时刻。绿色投资的显著增长凸显了全面了解这些市场动态的迫切需要。因此，本文引入了一种研究此类现象的新范式。以可再生能源领域为研究对象，采用变化点检测模型识别时间序列数据中的绿色气泡。此外，将搜索量指数和社会因素纳入已建立的计量经济模型，以揭示对金融体系的潜在影响。受约瑟夫·熊彼特（Joseph Schumpeter）商业周期观点的启发，这项研究认为绿色泡沫是促进向更可持续的未来成功过渡的“必要之恶”。

引用次数: 0

Firm climate investment: A glass half-full 坚定的气候投资：半满的杯子

IF 14.2 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2025-12-23 DOI: 10.1016/j.eneco.2025.109097

Prachi Srivastava , Nicholas Bloom , Philip Bunn , Paul Mizen , Gregory Thwaites , Ivan Yotzov

The green transition will require large investments from firms, yet little is known about the scale and drivers of climate-related capital expenditure across the UK economy. To address this gap, we draw on a large, representative survey of UK firms to quantify how businesses expect to adjust their medium-term investment in response to climate change. Over 2023-2026, firms expect climate-related investments to account for 5.5% of total capital expenditure. These investments will be driven by larger firms as well as those in more energy-intensive sectors. The main channels for these investments are switching to green energy sources and improving energy efficiency, and firms plan to finance them primarily using internal cash reserves. Overall, although firms are expecting to invest more resources in adapting to climate change, under reasonable assumptions, these investments are still not sufficient to meet the estimated targets implied by the UK Net Zero Pathway.

绿色转型将需要企业的大量投资，但人们对英国经济中与气候相关的资本支出的规模和驱动因素知之甚少。为了解决这一差距，我们对英国公司进行了一项具有代表性的大型调查，以量化企业预计如何调整其中期投资以应对气候变化。在2023-2026年期间，企业预计气候相关投资将占总资本支出的5.5%。这些投资将由大型企业以及能源密集型行业的企业推动。这些投资的主要渠道是转向绿色能源和提高能源效率，企业计划主要利用内部现金储备为这些投资提供资金。总体而言，尽管企业期望在适应气候变化方面投入更多资源，但在合理的假设下，这些投资仍然不足以满足英国净零路径所隐含的估计目标。

引用次数: 0

Energy bill pressure stimulates investment intentions primarily for high-socioeconomic households in Australia 能源账单压力主要刺激了澳大利亚高社会经济家庭的投资意愿

IF 14.2 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2025-12-23 DOI: 10.1016/j.eneco.2025.109111

Rohan Best , Madeline Taylor , Raúl Gutiérrez-Alvarez , David Parra

Energy bill pressure likely motivates household investment intentions, but influences could vary based on socioeconomic characteristics. A first possibility is that low-income households, who are more likely to be affected by energy bill pressure, may be more motivated than high-income households to make energy investments. A second possibility is that low-income households may be less likely to intend to invest due to barriers such as perceived unaffordability. We use Australian household survey data from 2017 to 2023 to assess influences of energy bill pressure on intentions for four investments: home batteries, electric vehicles, solar photovoltaic panels, and solar hot water systems. While the first possibility above is commonly mentioned, we instead find that energy bill pressure has a consistently lower influence on intentions for investments by households with a lower socioeconomic status. This finding is consistent across the four investment types. It is also consistent across a range of socioeconomic variables. Our results suggest that policy design should change to give disadvantaged households enhanced opportunities for investments while being responsive to variances in state and territory policies. Our results especially align with policy enhancements helping renters and households with low levels of assets.

能源账单压力可能会激发家庭投资意愿，但影响可能因社会经济特征而异。第一种可能性是，低收入家庭更有可能受到能源账单压力的影响，他们可能比高收入家庭更有动力进行能源投资。第二种可能性是，低收入家庭可能不太可能打算投资，因为他们觉得负担不起等障碍。我们使用2017年至2023年的澳大利亚家庭调查数据来评估能源账单压力对四项投资意向的影响：家用电池、电动汽车、太阳能光伏电池板和太阳能热水系统。虽然第一种可能性通常被提及，但我们发现能源账单压力对社会经济地位较低的家庭投资意愿的影响一直较低。这一发现在四种投资类型中是一致的。这在一系列社会经济变量中也是一致的。我们的研究结果表明，政策设计应该改变，在响应州和地区政策差异的同时，为弱势家庭提供更多的投资机会。我们的结果与帮助租房者和低资产水平家庭的政策加强相一致。

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引用次数: 0

Robust functional principal component analysis for detecting anomalous behaviors in electricity markets 电力市场异常行为检测的鲁棒功能主成分分析

IF 14.2 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2025-12-22 DOI: 10.1016/j.eneco.2025.109091

Mara Sabina Bernardi , Andrea Cerasa , Luigi Grossi , Fany Nan

This paper introduces a novel methodological framework to detect potentially manipulative behaviors in deregulated electricity markets using robust statistical tools. The work focuses on identifying outlying bidding patterns in daily auction microdata by modeling the shape of supply curves, rather than relying solely on price data, to better capture strategic market behavior. The approach is grounded in robust Functional Principal Component Analysis (FPCA), which enables the detection of anomalies in supply curve shapes while being resilient to outliers. A key innovation lies in applying the skewness-adjusted boxplot of Hubert and Vandervieren (2008) to the residuals from robust FPCA, enhancing sensitivity to asymmetric and extreme behaviors. Crucially, it is shown that the anomalies detected via robust FPCA differ significantly from those identified by classical outlier detection methods applied directly to price series, as the suggested method captures deviations in the underlying strategic behavior of market participants that are reflected in the structure of the supply curves, not necessarily in prices. Applied to the Italian day-ahead market, the method detects supply-curve anomalies that differ substantially from those identified by classical price-based techniques. A comparison with the LTSts and rolling-window filtering approaches confirms the distinct contribution of the proposed method, which identifies a complementary set of suspicious events potentially linked to strategic bidding behavior. The findings provide new tools for regulators to support market integrity and ensure compliance with transparency regulations such as the Regulation on Wholesale Energy Market Integrity and Transparency (REMIT).

本文介绍了一种新的方法框架，利用稳健的统计工具来检测放松管制的电力市场中潜在的操纵行为。这项工作的重点是通过对供给曲线的形状建模来识别日常拍卖微观数据中的外围竞标模式，而不是仅仅依赖价格数据，以更好地捕捉战略市场行为。该方法以强大的功能主成分分析（FPCA）为基础，可以检测供应曲线形状中的异常，同时对异常值具有弹性。一个关键的创新在于将偏度调整的箱线图应用于鲁棒FPCA的残差，提高了对不对称和极端行为的灵敏度。至关重要的是，研究表明，通过稳健的FPCA检测到的异常与直接应用于价格序列的经典离群值检测方法发现的异常有很大不同，因为建议的方法捕获了反映在供给曲线结构中的市场参与者潜在战略行为的偏差，而不一定反映在价格中。将该方法应用于意大利日前市场，可以发现与传统基于价格的技术所识别的供应曲线异常有很大不同。与ltst和滚动窗口过滤方法的比较证实了所提出方法的独特贡献，该方法识别了一组互补的可疑事件，这些事件可能与战略投标行为有关。研究结果为监管机构提供了新的工具，以支持市场诚信，并确保遵守《批发能源市场诚信和透明度条例》（REMIT）等透明度法规。

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引用次数: 0