Pub Date : 2024-10-05DOI: 10.1016/j.eneco.2024.107940
We study the effect of oil price shocks on bond risk premia. Based on Baumeister and Hamilton (2019), we identify the different sources of oil price shocks using a structural vector autoregressive (SVAR) model of the global market for crude oil. These structural factors are then used as unspanned factors in an affine term structure model based on the representation of Joslin et al. (2014). This is done for a total of 15 countries. Unspanned factors are responsible for most of the variability in bond risk premia for short holding periods, while spanned factors dominate the variance decomposition for longer holding periods. In both cases, global oil supply and global economic activity are clearly the most important unspanned shocks. A historical decomposition around the outbreak of the COVID-19 crisis shows the clear influence of global economic activity shocks during the months of February and March 2020, increasing bond risk premia significantly.
{"title":"Oil price shocks and bond risk premia: Evidence from a panel of 15 countries","authors":"","doi":"10.1016/j.eneco.2024.107940","DOIUrl":"10.1016/j.eneco.2024.107940","url":null,"abstract":"<div><div>We study the effect of oil price shocks on bond risk premia. Based on Baumeister and Hamilton (2019), we identify the different sources of oil price shocks using a structural vector autoregressive (SVAR) model of the global market for crude oil. These structural factors are then used as unspanned factors in an affine term structure model based on the representation of Joslin et al. (2014). This is done for a total of 15 countries. Unspanned factors are responsible for most of the variability in bond risk premia for short holding periods, while spanned factors dominate the variance decomposition for longer holding periods. In both cases, global oil supply and global economic activity are clearly the most important unspanned shocks. A historical decomposition around the outbreak of the COVID-19 crisis shows the clear influence of global economic activity shocks during the months of February and March 2020, increasing bond risk premia significantly.</div></div>","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":null,"pages":null},"PeriodicalIF":13.6,"publicationDate":"2024-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142420850","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}
Pub Date : 2024-10-05DOI: 10.1016/j.eneco.2024.107942
A significant share of corporate carbon emissions stems from the supply chain, necessitating an analysis of how supply chain digitalization influences green innovation in the digital age. This paper examines this impact using data from Chinese listed firms (2012−2022). Theoretically, the study posits that supply chain digitalization facilitates green innovation through two primary mechanisms: enhancing upstream and downstream integration and boosting the internal efficiency of supply chain management at nodal enterprises. Empirically, a quasi-natural experiment leveraging the Supply Chain Innovation and Application Pilot Program serves as an exogenous shock. Key findings include: (1) Supply chain digitalization enhances corporate green innovation, with robust results across various tests. (2) The effect is mainly driven by enhanced supply chain integration—more from supplier concentration than customer concentration—and improved internal supply chain management efficiency. (3) The impact has three characteristics: Quality-first Effect, Crowding-in Effect and Persistence Effect. Specifically, supply chain digitalization mainly boosts high-quality green invention patent applications without crowding-out other non-green innovation, while also positively influences sustained green innovation. (4) Supply chain digitalization primarily enhances green innovation in End-of-Pipe and Process Control Technologies, with limited effects on Pollution Prevention at Source.
{"title":"From bytes to green: The impact of supply chain digitization on corporate green innovation","authors":"","doi":"10.1016/j.eneco.2024.107942","DOIUrl":"10.1016/j.eneco.2024.107942","url":null,"abstract":"<div><div>A significant share of corporate carbon emissions stems from the supply chain, necessitating an analysis of how supply chain digitalization influences green innovation in the digital age. This paper examines this impact using data from Chinese listed firms (2012−2022). Theoretically, the study posits that supply chain digitalization facilitates green innovation through two primary mechanisms: enhancing upstream and downstream integration and boosting the internal efficiency of supply chain management at nodal enterprises. Empirically, a quasi-natural experiment leveraging the Supply Chain Innovation and Application Pilot Program serves as an exogenous shock. Key findings include: (1) Supply chain digitalization enhances corporate green innovation, with robust results across various tests. (2) The effect is mainly driven by enhanced supply chain integration—more from supplier concentration than customer concentration—and improved internal supply chain management efficiency. (3) The impact has three characteristics: Quality-first Effect, Crowding-in Effect and Persistence Effect. Specifically, supply chain digitalization mainly boosts high-quality green invention patent applications without crowding-out other non-green innovation, while also positively influences sustained green innovation. (4) Supply chain digitalization primarily enhances green innovation in End-of-Pipe and Process Control Technologies, with limited effects on Pollution Prevention at Source.</div></div>","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":null,"pages":null},"PeriodicalIF":13.6,"publicationDate":"2024-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142432681","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}
Pub Date : 2024-10-05DOI: 10.1016/j.eneco.2024.107934
Operational decisions relying on predictive distributions of electricity prices can result in significantly higher profits compared to those based solely on point forecasts. However, the majority of models developed in both academic and industrial settings provide only point predictions. To address this, we examine three postprocessing methods for converting point forecasts of day-ahead electricity prices into probabilistic ones: Quantile Regression Averaging, Conformal Prediction, and the recently introduced Isotonic Distributional Regression. We find that while the latter demonstrates the most varied behavior, it contributes the most to the ensemble of the three predictive distributions, as measured by Shapley values. Remarkably, the performance of the combination is superior to that of state-of-the-art Distributional Deep Neural Networks over two 4.5-year test periods from the German and Spanish power markets, spanning the COVID pandemic and the war in Ukraine.
{"title":"Postprocessing of point predictions for probabilistic forecasting of day-ahead electricity prices: The benefits of using isotonic distributional regression","authors":"","doi":"10.1016/j.eneco.2024.107934","DOIUrl":"10.1016/j.eneco.2024.107934","url":null,"abstract":"<div><div>Operational decisions relying on predictive distributions of electricity prices can result in significantly higher profits compared to those based solely on point forecasts. However, the majority of models developed in both academic and industrial settings provide only point predictions. To address this, we examine three postprocessing methods for converting point forecasts of day-ahead electricity prices into probabilistic ones: Quantile Regression Averaging, Conformal Prediction, and the recently introduced Isotonic Distributional Regression. We find that while the latter demonstrates the most varied behavior, it contributes the most to the ensemble of the three predictive distributions, as measured by Shapley values. Remarkably, the performance of the combination is superior to that of state-of-the-art Distributional Deep Neural Networks over two 4.5-year test periods from the German and Spanish power markets, spanning the COVID pandemic and the war in Ukraine.</div></div>","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":null,"pages":null},"PeriodicalIF":13.6,"publicationDate":"2024-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142420854","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}
Pub Date : 2024-10-04DOI: 10.1016/j.eneco.2024.107952
This paper proposes a novel Multi-scale Interval-valued Decomposition Ensemble (MIDE) framework for forecasting European Union Allowance (EUA) carbon futures prices, which integrates Noise-assisted Multivariate Empirical Mode Decomposition (NAMEMD), Interval-valued Vector Auto-Regressive (IVAR) model, Interval Event Analysis (IEA) method, and Interval Multi-Layer Perceptron (IMLP). First, the original interval-valued carbon prices with other interval-valued control variables are decomposed and integrated into high, medium, and low-frequency components by NAMEMD. Second, IVAR is used to investigate the dynamics of the interval-valued vector system in low-frequency components, while IMLP is employed to characterize the high-frequency components. Besides, the interval event analysis investigates typical events that significantly impact carbon prices in the medium-frequency component. Furthermore, empirical findings indicate that our proposed MIDE learning approach significantly outperforms some other benchmark models in out-of-sample forecasting.
本文提出了一种用于预测欧盟配额（EUA）碳期货价格的新型多尺度区间值分解集合（MIDE）框架，该框架集成了噪声辅助多变量经验模式分解（NAMEMD）、区间值矢量自回归（IVAR）模型、区间事件分析（IEA）方法和区间多层感知器（IMLP）。首先，利用 NAMEMD 将原始区间值碳价格与其他区间值控制变量分解并整合为高、中、低频成分。其次，利用 IVAR 研究区间值向量系统在低频成分中的动态变化，同时利用 IMLP 描述高频成分的特征。此外，区间事件分析研究了在中频成分中对碳价格产生重大影响的典型事件。此外，实证研究结果表明，我们提出的 MIDE 学习方法在样本外预测方面明显优于其他一些基准模型。
{"title":"Forecasting interval carbon price through a multi-scale interval-valued decomposition ensemble approach","authors":"","doi":"10.1016/j.eneco.2024.107952","DOIUrl":"10.1016/j.eneco.2024.107952","url":null,"abstract":"<div><div>This paper proposes a novel Multi-scale Interval-valued Decomposition Ensemble (MIDE) framework for forecasting European Union Allowance (EUA) carbon futures prices, which integrates Noise-assisted Multivariate Empirical Mode Decomposition (NAMEMD), Interval-valued Vector Auto-Regressive (IVAR) model, Interval Event Analysis (IEA) method, and Interval Multi-Layer Perceptron (IMLP). First, the original interval-valued carbon prices with other interval-valued control variables are decomposed and integrated into high, medium, and low-frequency components by NAMEMD. Second, IVAR is used to investigate the dynamics of the interval-valued vector system in low-frequency components, while IMLP is employed to characterize the high-frequency components. Besides, the interval event analysis investigates typical events that significantly impact carbon prices in the medium-frequency component. Furthermore, empirical findings indicate that our proposed MIDE learning approach significantly outperforms some other benchmark models in out-of-sample forecasting.</div></div>","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":null,"pages":null},"PeriodicalIF":13.6,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142420800","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}
Pub Date : 2024-10-04DOI: 10.1016/j.eneco.2024.107931
International climate policy risk spillovers occur when expected changes to climate policy stringency in one country affect expected climate policy stringency in another country. We develop an event study procedure to identify such spillovers in emissions trading systems, specifically examining the impact from the United States (US) to the European Union (EU). Distinguishing between policy events likely to reduce US commitment to climate action (‘brown events’) and those likely to increase it (‘green events’), we find that the average brown US policy event is associated with an anticipated increase in future EU carbon permit supply, leading to a cumulative 7.1% drop in EU carbon prices over the event window. Conversely, green US policy events are linked to an expected decrease in future EU permit supply, resulting in a cumulative 4.7% rise in EU carbon prices. These findings suggest that financial markets anticipate EU regulators to align with the direction of US climate policy. Our results underscore the significance of regulatory risk spillovers in global climate policy coordination.
{"title":"Global spillovers of US climate policy risk: Evidence from EU carbon emissions futures","authors":"","doi":"10.1016/j.eneco.2024.107931","DOIUrl":"10.1016/j.eneco.2024.107931","url":null,"abstract":"<div><div>International climate policy risk spillovers occur when expected changes to climate policy stringency in one country affect expected climate policy stringency in another country. We develop an event study procedure to identify such spillovers in emissions trading systems, specifically examining the impact from the United States (US) to the European Union (EU). Distinguishing between policy events likely to reduce US commitment to climate action (‘brown events’) and those likely to increase it (‘green events’), we find that the average brown US policy event is associated with an anticipated increase in future EU carbon permit supply, leading to a cumulative 7.1% drop in EU carbon prices over the event window. Conversely, green US policy events are linked to an expected decrease in future EU permit supply, resulting in a cumulative 4.7% rise in EU carbon prices. These findings suggest that financial markets anticipate EU regulators to align with the direction of US climate policy. Our results underscore the significance of regulatory risk spillovers in global climate policy coordination.</div></div>","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":null,"pages":null},"PeriodicalIF":13.6,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142420851","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}
Pub Date : 2024-10-04DOI: 10.1016/j.eneco.2024.107946
In our previous publication “Assessing the effectiveness of energy efficiency measures in the residential sector gas consumption through dynamic treatment effects: Evidence from England and Wales”, we analyzed the impact of the implementation of energy efficiency (EE) measures, in particular loft insulation and cavity walls, on household gas consumption up to five years after installation. Upon review, we realized that our phrasing, specifically the term “energy savings disappear,” might have led to misunderstandings regarding our findings. In this commentary, we clarify that our results indicate reductions in the level of energy (gas) savings achieved, two to four years after the implementation of the energy efficiency measures. The adoption of EE measures is associated with significant reductions in household residential gas consumption one year after their implementation, as we expressed in Peñasco and Anadon (2023). However, the level of savings decreases four years after the retrofitting of cavity wall insulation measures and two years after the installation of loft insulation, generating increases in consumption with respect to the maximum level of savings achieved, i.e., rebounds in consumption. We find that, after five years, energy savings from loft installations are still positive, in the range of 4–5 % compared to the control group—a level of savings that represents a rebound of about 20–25 %, when compared to the maximum level of savings that occurs two years after installation. For cavity walls, after five years gas savings are in the range of 6–9 % compared to the control group, with rebounds of about 10–13 % compared to the maximum savings in year two. This clarification is crucial to prevent a misinterpretation of the results in future research and policy making.
{"title":"A comment on “Assessing the effectiveness of energy efficiency measures in the residential sector gas consumption through dynamic treatment effects: Evidence from England and Wales”","authors":"","doi":"10.1016/j.eneco.2024.107946","DOIUrl":"10.1016/j.eneco.2024.107946","url":null,"abstract":"<div><div>In our previous publication “Assessing the effectiveness of energy efficiency measures in the residential sector gas consumption through dynamic treatment effects: Evidence from England and Wales”, we analyzed the impact of the implementation of energy efficiency (EE) measures, in particular loft insulation and cavity walls, on household gas consumption up to five years after installation. Upon review, we realized that our phrasing, specifically the term “energy savings disappear,” might have led to misunderstandings regarding our findings. In this commentary, we clarify that our results indicate reductions in the level of energy (gas) savings achieved, two to four years after the implementation of the energy efficiency measures. The adoption of EE measures is associated with significant reductions in household residential gas consumption one year after their implementation, as we expressed in Peñasco and Anadon (2023). However, the level of savings decreases four years after the retrofitting of cavity wall insulation measures and two years after the installation of loft insulation, generating increases in consumption with respect to the maximum level of savings achieved, i.e., rebounds in consumption. We find that, after five years, energy savings from loft installations are still positive, in the range of 4–5 % compared to the control group—a level of savings that represents a rebound of about 20–25 %, when compared to the maximum level of savings that occurs two years after installation. For cavity walls, after five years gas savings are in the range of 6–9 % compared to the control group, with rebounds of about 10–13 % compared to the maximum savings in year two. This clarification is crucial to prevent a misinterpretation of the results in future research and policy making.</div></div>","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":null,"pages":null},"PeriodicalIF":13.6,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142432680","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}
Pub Date : 2024-10-03DOI: 10.1016/j.eneco.2024.107950
Emerging economies are burdened with multiple tasks related to economic development and environmental protection. Based on the phenomenon of “brain gain,” we examine whether overseas-returned executives (“returnees”) help emerging economies better cope with this multitasking. Drawing insights from a Chinese listed firm dataset for the period 2010–2020, this study provides significant observations regarding returnees' influence on firms' environmental performance. The findings show that hiring returnees makes firms greener for three main reasons. First, returnees enjoy favorable treatment provided by the worksite, and the mood of giving back makes them inclined toward low-pollution development. Second, returnees have more green skills. Third, returnees alleviate the principal–agent problem of firms in green development. There are also some extended findings from this study. As inferred from the firms' environmental performance, returnees' overseas study experience may be more important than pure overseas work experience. Additionally, firms that green up by hiring returnees are not biased by firm seniority. Finally, if returnees are viewed as a scarce resource, conditional talent wars will emerge among firms. These findings provide insight into how emerging economies can balance economic development with environmental protection.
{"title":"Bluer skies and clearer rivers? Returnees as silver bullets for pollution abatement in an emerging economy","authors":"","doi":"10.1016/j.eneco.2024.107950","DOIUrl":"10.1016/j.eneco.2024.107950","url":null,"abstract":"<div><div>Emerging economies are burdened with multiple tasks related to economic development and environmental protection. Based on the phenomenon of “brain gain,” we examine whether overseas-returned executives (“returnees”) help emerging economies better cope with this multitasking. Drawing insights from a Chinese listed firm dataset for the period 2010–2020, this study provides significant observations regarding returnees' influence on firms' environmental performance. The findings show that hiring returnees makes firms greener for three main reasons. First, returnees enjoy favorable treatment provided by the worksite, and the mood of giving back makes them inclined toward low-pollution development. Second, returnees have more green skills. Third, returnees alleviate the principal–agent problem of firms in green development. There are also some extended findings from this study. As inferred from the firms' environmental performance, returnees' overseas study experience may be more important than pure overseas work experience. Additionally, firms that green up by hiring returnees are not biased by firm seniority. Finally, if returnees are viewed as a scarce resource, conditional talent wars will emerge among firms. These findings provide insight into how emerging economies can balance economic development with environmental protection.</div></div>","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":null,"pages":null},"PeriodicalIF":13.6,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142420852","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}
Pub Date : 2024-10-02DOI: 10.1016/j.eneco.2024.107951
Green investments play a crucial role in fighting climate change and facilitating the shift towards a low-carbon economy in line with goals of the Paris Agreement. This paper focuses on the U.S. green energy sector, analyzing its underlying risk dynamics, especially during crisis periods. In this paper, we employ a novel green energy time-varying beta (GETVB) to assess the risk profiles of U.S. green energy stocks across different market conditions. We have chosen NASDAQ Clean Edge Green Energy Index (CELS) as the U.S. green energy market index. We use Markov-switching and discrete-threshold-regression models to examine whether the GETVB varies across regimes and is affected by market stress. In particular, we examine if the market risk of these stocks itself exhibits higher volatility during regimes of stress. Our results show that the green stocks are apparently risky, with a GETVB most likely to lie between 1.2 and 1.6. However, these stocks turn out to be resilient against market volatility with the market stress having negligible impact on GETVB. This suggests an inherent robustness of green stocks against extreme market conditions. This resilience makes the U.S. green energy stocks a potential safe destination for investors during times of significant market volatility. Based on the results, we recommend that policymakers bolster support for green investments through enhanced tax incentives and subsidies, aiming to standardize the ESG metrics for increased transparency, and aligning the international financial flows with strategies that align with meeting the Paris Agreement targets.
{"title":"Exploring the risk dynamics of US green energy stocks: A green time-varying beta approach","authors":"","doi":"10.1016/j.eneco.2024.107951","DOIUrl":"10.1016/j.eneco.2024.107951","url":null,"abstract":"<div><div>Green investments play a crucial role in fighting climate change and facilitating the shift towards a low-carbon economy in line with goals of the Paris Agreement. This paper focuses on the U.S. green energy sector, analyzing its underlying risk dynamics, especially during crisis periods. In this paper, we employ a novel green energy time-varying beta (GETVB) to assess the risk profiles of U.S. green energy stocks across different market conditions. We have chosen NASDAQ Clean Edge Green Energy Index (CELS) as the U.S. green energy market index. We use Markov-switching and discrete-threshold-regression models to examine whether the GETVB varies across regimes and is affected by market stress. In particular, we examine if the market risk of these stocks itself exhibits higher volatility during regimes of stress. Our results show that the green stocks are apparently risky, with a GETVB most likely to lie between 1.2 and 1.6. However, these stocks turn out to be resilient against market volatility with the market stress having negligible impact on GETVB. This suggests an inherent robustness of green stocks against extreme market conditions. This resilience makes the U.S. green energy stocks a potential safe destination for investors during times of significant market volatility. Based on the results, we recommend that policymakers bolster support for green investments through enhanced tax incentives and subsidies, aiming to standardize the ESG metrics for increased transparency, and aligning the international financial flows with strategies that align with meeting the Paris Agreement targets.</div></div>","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":null,"pages":null},"PeriodicalIF":13.6,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142420853","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}
Pub Date : 2024-10-02DOI: 10.1016/j.eneco.2024.107947
Over the past, all the big economies across the world are focusing on attainment of objectives of COP27 and COP28 and USA is forefront among them. Therefore, present study aims to unraveling the role of renewable energy, energy innovation, climate change and green financial development in mapping and shaping the energy transition system in the USA. In view of this, study utilizes annual data of said constructs from 2008 to 2022 and estimates through Dynamic Autoregressive Distributed Lag simulations (DARDLS) approach. Results indicate the positve impacts of renewable energy and energy innovation on energy transition and sustainable energy management in both long and short run. Whereas green financial development reflects low positive impact on energy transition in short run and getting stronger in long run. Expectedly, climate change adversely affect the energy transition and increases energy risk for the USA. Policy implications and Government frameworks are suggested to facilitate the renewable energy, energy innovation and green financial development and to mitigate climate change risk in USA.
{"title":"How do renewable energy, energy innovation and climate change shape the energy transition in USA? Unraveling the role of green finance development","authors":"","doi":"10.1016/j.eneco.2024.107947","DOIUrl":"10.1016/j.eneco.2024.107947","url":null,"abstract":"<div><div>Over the past, all the big economies across the world are focusing on attainment of objectives of COP27 and COP28 and USA is forefront among them. Therefore, present study aims to unraveling the role of renewable energy, energy innovation, climate change and green financial development in mapping and shaping the energy transition system in the USA. In view of this, study utilizes annual data of said constructs from 2008 to 2022 and estimates through Dynamic Autoregressive Distributed Lag simulations (DARDLS) approach. Results indicate the positve impacts of renewable energy and energy innovation on energy transition and sustainable energy management in both long and short run. Whereas green financial development reflects low positive impact on energy transition in short run and getting stronger in long run. Expectedly, climate change adversely affect the energy transition and increases energy risk for the USA. Policy implications and Government frameworks are suggested to facilitate the renewable energy, energy innovation and green financial development and to mitigate climate change risk in USA.</div></div>","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":null,"pages":null},"PeriodicalIF":13.6,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142532888","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}
Pub Date : 2024-10-01DOI: 10.1016/j.eneco.2024.107948
This study investigates the relationship between bank boards' characteristics and their commitment to divest from fossil fuels. Using data on worldwide listed banks from 2016 to 2022, the results show a positive influence of board gender diversity on bank divestment from fossil fuel companies. We find that this result holds even following numerous robustness tests. A sub-sample analysis reveals that the effect of board gender diversity is significant for laggards' countries in environmental performance. These results highlight that greater gender diversity in board composition promotes sustainability, facilitating a shift towards business models prioritizing environmental goals. Evidence also offers valuable insights for policymakers in their efforts to align financial activities with sustainability goals. By embracing these implications, banks can contribute to the global transition towards a more environmentally sustainable and socially responsible future.
{"title":"Banks' fossil fuel divestment and corporate governance: The role of board gender diversity","authors":"","doi":"10.1016/j.eneco.2024.107948","DOIUrl":"10.1016/j.eneco.2024.107948","url":null,"abstract":"<div><div>This study investigates the relationship between bank boards' characteristics and their commitment to divest from fossil fuels. Using data on worldwide listed banks from 2016 to 2022, the results show a positive influence of board gender diversity on bank divestment from fossil fuel companies. We find that this result holds even following numerous robustness tests. A sub-sample analysis reveals that the effect of board gender diversity is significant for laggards' countries in environmental performance. These results highlight that greater gender diversity in board composition promotes sustainability, facilitating a shift towards business models prioritizing environmental goals. Evidence also offers valuable insights for policymakers in their efforts to align financial activities with sustainability goals. By embracing these implications, banks can contribute to the global transition towards a more environmentally sustainable and socially responsible future.</div></div>","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":null,"pages":null},"PeriodicalIF":13.6,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142420799","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}
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