Energy Economics最新文献_第3页

The impact of women's political empowerment on renewable energy demand: Evidence from OECD countries

IF 12.8 2区经济学

Energy Economics Pub Date : 2024-11-28 DOI: 10.1016/j.eneco.2024.108081

Giray Gozgor, Jing Li, Irfan Saleem, Riazullah Shinwari

引用次数: 0

Business strategies and carbon emissions

IF 12.8 2区经济学

Energy Economics Pub Date : 2024-11-28 DOI: 10.1016/j.eneco.2024.108092

Mostafa Monzur Hasan, Xiaomeng Charlene Chen

引用次数: 0

Understanding the drivers of energy capacity transitions: New evidence from a dual approach 了解能源产能转型的驱动因素：来自双重方法的新证据

IF 12.8 2区经济学

Energy Economics Pub Date : 2024-11-27 DOI: 10.1016/j.eneco.2024.108002

Zied Ftiti, Haithem Awijen, Hachmi Ben Ameur, Wael Louhichi

{"title":"Understanding the drivers of energy capacity transitions: New evidence from a dual approach","authors":"Zied Ftiti, Haithem Awijen, Hachmi Ben Ameur, Wael Louhichi","doi":"10.1016/j.eneco.2024.108002","DOIUrl":"https://doi.org/10.1016/j.eneco.2024.108002","url":null,"abstract":"This study investigates the drivers of renewable energy capacity in 25 OECD countries from 1989 to 2019, with a particular focus on the complex role of oil prices in the energy transition. Given their strong correlation with major fossil fuels like coal and gas, understanding the impact of oil price shocks is crucial for shaping effective transition strategies. We examine this impact from a climate mitigation perspective, recognising it as a key dimension of a just transition. Unlike previous research, our approach suggests that policymakers, stakeholders, and investors should focus on two key areas to ensure a sustainable transition: promoting renewable energy capacity and reducing non-renewable energy capacity. We propose a dual-focus approach that acknowledges the importance of both enhancing renewable energy adoption and diminishing reliance on non-renewable sources. By identifying and leveraging both sets of drivers, policymakers and stakeholders can create more balanced and comprehensive strategies for energy transition. We categorise the drivers into four levels: (1) the interplay between oil prices, climate mitigation finance, and green innovation; (2) macroeconomic factors; (3) climate degradation; and (4) environmental management policies. Our results confirm our hypothesis by highlighting the role of certain drivers in reducing non-renewable energy capacity and certain others in promoting renewable energy capacity. Furthermore, our findings underscore the direct and indirect channels through which oil price dynamics influence the promotion of renewable energy capacity and reduction of non-renewable capacity, notably through the climate mitigation finance channel. This multifaceted approach aims to provide a deeper understanding of the various factors influencing energy transition and offer actionable insights for effective policy formulation.","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"82 1","pages":""},"PeriodicalIF":12.8,"publicationDate":"2024-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142825382","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 tail risk premium in the oil market

IF 12.8 2区经济学

Energy Economics Pub Date : 2024-11-27 DOI: 10.1016/j.eneco.2024.108041

Reinhard Ellwanger

引用次数: 0

Green finance and job creation: Analyzing employment effects in China's manufacturing industry within green finance innovation and reform pilot zones

IF 13.6 2区经济学

Energy Economics Pub Date : 2024-11-26 DOI: 10.1016/j.eneco.2024.108090

Bowen Fu , Yixiang Zhang , Sholeh Maani , Le Wen

{"title":"Green finance and job creation: Analyzing employment effects in China's manufacturing industry within green finance innovation and reform pilot zones","authors":"Bowen Fu , Yixiang Zhang , Sholeh Maani , Le Wen","doi":"10.1016/j.eneco.2024.108090","DOIUrl":"10.1016/j.eneco.2024.108090","url":null,"abstract":"<div><div>As environmental issues related to global climate change intensify, green finance (GF) policies have emerged as vital tools for promoting sustainable development. This study examines the impact of GF policies on employment in China's manufacturing sector. Using unbalanced panel data of Chinese listed manufacturing enterprises from 2012 to 2021, and employing the difference-in-differences model, this study analyzes the impact of establishing China's GF innovation and reform pilot zones on manufacturing employment. The results show that the implementation of GF policies significantly increases employment in the manufacturing sector, with a more pronounced effect in non-state-owned enterprises, non-heavy-polluting industries, and high-tech manufacturing enterprises. Additionally, the study finds that GF policies alleviate financing constraints, enhancing employment levels in manufacturing enterprises. This research contributes to the existing literature by elucidating the employment effects of GF and providing insights for policymakers to use in fostering GF for economic growth.</div></div>","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"141 ","pages":"Article 108090"},"PeriodicalIF":13.6,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142743867","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Higher moments interaction between the US treasury yields, energy assets, and green cryptos: Dynamic analysis with portfolio implications

IF 13.6 2区经济学

Energy Economics Pub Date : 2024-11-26 DOI: 10.1016/j.eneco.2024.108077

Najaf Iqbal , Zaghum Umar , Zhang Shaoyong , Tatiana Sokolova

{"title":"Higher moments interaction between the US treasury yields, energy assets, and green cryptos: Dynamic analysis with portfolio implications","authors":"Najaf Iqbal , Zaghum Umar , Zhang Shaoyong , Tatiana Sokolova","doi":"10.1016/j.eneco.2024.108077","DOIUrl":"10.1016/j.eneco.2024.108077","url":null,"abstract":"<div><div>We examine how the US treasury yields are connected with traditional energy and green cryptocurrencies in higher moments. For this purpose, we first compute the US treasury yield curve's Level, Slope, and Curvature based on different maturities from October 2017 to December 2023 and then apply the TVP-VAR model on return, volatility, Skewness, and Kurtosis measures. We find that returns are the most connected compared with the higher moments. The dynamic connectedness represents distinct spikes in each moment's case, sharing patterns during the 2017 crypto rally, the COVID-19 outburst in 2020, and the Russia-Ukraine war eruption in 2022. Despite being the leading shock transmitters, green cryptocurrencies share weak connections in the higher moments, making them suitable diversifiers in turbulent times. We also compute minimum variance, minimum connectedness, and minimum correlation portfolios and their hedging effectiveness. Green cryptos significantly reduce variance in traditional energy portfolios, which is evident from their high hedging effectiveness. The connectedness patterns support the Global Financial Cycle Hypothesis, showing integration in extreme market conditions, partly affected by the US treasury yields. We discuss the important implications of these findings for portfolio managers and policymakers.</div></div>","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"141 ","pages":"Article 108077"},"PeriodicalIF":13.6,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142758810","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

Revealing air quality impacts of the clean heating campaign in northern China

IF 13.6 2区经济学

Energy Economics Pub Date : 2024-11-26 DOI: 10.1016/j.eneco.2024.108078

Yichao He , Huili Wang , Yixuan Zheng , Yueyi Feng , Xiaojun Chen , Ling Jin , Yu Lei

{"title":"Revealing air quality impacts of the clean heating campaign in northern China","authors":"Yichao He , Huili Wang , Yixuan Zheng , Yueyi Feng , Xiaojun Chen , Ling Jin , Yu Lei","doi":"10.1016/j.eneco.2024.108078","DOIUrl":"10.1016/j.eneco.2024.108078","url":null,"abstract":"<div><div>To mitigate air pollution caused by bulk coal burning for heating in northern China during winter, the Chinese government initiated a clean heating campaign in Beijing and the surrounding region starting in 2017. The impact of this historic campaign remained unclear at a fine spatial and temporal resolution. Based on the annually updated high spatial resolution surveyed coal substitution data, this study coupled the multi-period difference-in-differences (DID) model with the two-stage DID model and found that bulk coal substitution would have led to a spatially and temporally averaged reduction by 4.0 μg/m<sup>3</sup> in wintertime PM<sub>2.5</sub> concentration over Beijing and the surrounding region. Furthermore, taking advantage of the spatially disaggregated data, spillover effects associated with air pollution transportation were further quantified. Considering these effects, the estimated air quality benefit would increase to 8.2 μg/m<sup>3</sup>. Additionally, these benefits exhibit sustainability, with the fourth year post-implementation 3.6 times greater than the initial year, suggesting cumulative effects of the policy. On average, every 1kt of bulk coal substitution resulted to 0.3 μg/m<sup>3</sup> PM<sub>2.5</sub> reduction at a 0.1° × 0.1° grid. These findings, validated through extensive robustness testing, underscore the effectiveness and sustainability of the clean heating campaign and would offer valuable insights for relevant policy formulation in China or other developing countries.</div></div>","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"141 ","pages":"Article 108078"},"PeriodicalIF":13.6,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142759421","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

Cross-quantile risk assessment: The interplay of crude oil, artificial intelligence, clean tech, and other markets

IF 13.6 2区经济学

Energy Economics Pub Date : 2024-11-26 DOI: 10.1016/j.eneco.2024.108085

Mariya Gubareva , Muhammad Shafiullah , Tamara Teplova

{"title":"Cross-quantile risk assessment: The interplay of crude oil, artificial intelligence, clean tech, and other markets","authors":"Mariya Gubareva , Muhammad Shafiullah , Tamara Teplova","doi":"10.1016/j.eneco.2024.108085","DOIUrl":"10.1016/j.eneco.2024.108085","url":null,"abstract":"<div><div>This paper explores the interconnections among oil, artificial intelligence (AI), clean technology, and traditional markets. We apply a novel generalized quantile-on-quantile connectedness method that assesses variable cross-quantile interdependencies, analyzing data from 2018 to 2023. Our study provides a detailed examination of risk transmission dynamics between oil, AI, clean technology, and major markets including equity, debt, and currency. Our findings indicate that tail risk spillovers are more pronounced than median quantiles. In contrast, the analysis shows negative spillovers across these tails in markets for U.S. government debt, the U.S. dollar, and gold. The dynamic risk transmission analysis reveals that while the stock and AI markets generally act as net transmitters of risk across all quantiles, the crude oil and USD index markets consistently receive net risk spillovers, particularly in the right tail of the distribution. Our results suggest that, on average, AI, and clean technology markets, along with the stock markets, are more likely to transfer risk spillovers compared to debt, currency, or other commodity markets. This positions the USD and crude oil as potential buffers against extreme risk transmissions emanating from the AI and clean technology sectors. This study highlights the complex risk dynamics and the pivotal role of oil in the interplay between emerging technologies and traditional financial markets.</div></div>","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"141 ","pages":"Article 108085"},"PeriodicalIF":13.6,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142743866","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Natural gas prices, inflation expectations, and the pass-through to euro area inflation

IF 13.6 2区经济学

Energy Economics Pub Date : 2024-11-26 DOI: 10.1016/j.eneco.2024.108061

Maximilian Boeck , Thomas O. Zörner

引用次数: 0

Searching for a just transition: Micro-level employment impacts of climate policies

IF 12.8 2区经济学

Energy Economics Pub Date : 2024-11-26 DOI: 10.1016/j.eneco.2024.108086

Niven Winchester, Lynn Riggs, Livvy Mitchell, Dominic White

{"title":"Searching for a just transition: Micro-level employment impacts of climate policies","authors":"Niven Winchester, Lynn Riggs, Livvy Mitchell, Dominic White","doi":"10.1016/j.eneco.2024.108086","DOIUrl":"https://doi.org/10.1016/j.eneco.2024.108086","url":null,"abstract":"We develop and apply a modelling framework to estimate the micro-level employment impacts of climate policies in Aotearoa New Zealand. Our approach links an economy-wide model with a micro simulation module to calculate employment changes for different groups of the population across several dimensions (and combinations of dimensions), including sectoral, geospatial, demographic, and socio-economic categories. By simulating the linked modelling framework out to 2050 for proposed climate policies, we estimate which industries, workers, and jobs are expected to be most affected by these policies. Industries that experience the largest negative employment impacts include coal mining, oil and gas extraction, and some manufacturing activities. Reflecting the deployment of labour-intensive abatement options, some agriculture industries experience the largest employment increases. Workers that incur a disproportionate share of the transition are older, have lower levels of education, or are Māori. Employment transitions are also concentrated in certain regions. The results and modelling tools can help the New Zealand government formulate policies to ensure a ‘just transition’ to a low carbon future.","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"33 1","pages":""},"PeriodicalIF":12.8,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142790072","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