Pub Date : 2024-12-18DOI: 10.1016/j.eneco.2024.108134
Kathrin Kaestner, Stephan Sommer, Jessica Berneiser, Ralph Henger, Christian Oberst
The building sector offers an important lever for reducing carbon emissions, with carbon pricing considered as one essential policy instrument to unleash this potential. Yet, carbon pricing in residential buildings faces challenges, particularly in rental housing, as the financial burden and thus the incentives to reduce carbon emissions may be distributed differently between landlords and tenants, presenting a principal–agent problem that may lead to conflict and low public support. Using extensive survey data from about 12,000 households, we analyze the support for different concepts to share the cost burden owed to carbon pricing between landlords and tenants. We particularly examine the role of perceived cost, effectiveness, and fairness and experimentally study the impact of revenue use and carbon price level on public preferences. Our results suggest that the price level and revenue use hardly affect support, whereas tenancy – and thus self-interest – as well as perceived fairness of the sharing concept strongly correlate with preferences. Overall, a sharing mechanism according to the energy efficiency of the building is the most preferred cost allocation among our participants.
{"title":"Cost sharing mechanisms for carbon pricing: What drives support in the housing sector?","authors":"Kathrin Kaestner, Stephan Sommer, Jessica Berneiser, Ralph Henger, Christian Oberst","doi":"10.1016/j.eneco.2024.108134","DOIUrl":"https://doi.org/10.1016/j.eneco.2024.108134","url":null,"abstract":"The building sector offers an important lever for reducing carbon emissions, with carbon pricing considered as one essential policy instrument to unleash this potential. Yet, carbon pricing in residential buildings faces challenges, particularly in rental housing, as the financial burden and thus the incentives to reduce carbon emissions may be distributed differently between landlords and tenants, presenting a principal–agent problem that may lead to conflict and low public support. Using extensive survey data from about 12,000 households, we analyze the support for different concepts to share the cost burden owed to carbon pricing between landlords and tenants. We particularly examine the role of perceived cost, effectiveness, and fairness and experimentally study the impact of revenue use and carbon price level on public preferences. Our results suggest that the price level and revenue use hardly affect support, whereas tenancy – and thus self-interest – as well as perceived fairness of the sharing concept strongly correlate with preferences. Overall, a sharing mechanism according to the energy efficiency of the building is the most preferred cost allocation among our participants.","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"10 1","pages":""},"PeriodicalIF":12.8,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142968127","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 : 2024-12-18DOI: 10.1016/j.eneco.2024.108143
Shupei Huang, Xinya Wang, Qiang Ji
Geopolitical risk interacts with natural resource commodity markets closely and dynamically, which complicates the fluctuation spillover among those markets. We firstly uncover the overall and dynamic information spillover features among energy and metal markets, namely traditional energy, transition energy, new energy metals, precious metals, and traditional bulk metals in the nonlinear causal network constructed by combining the leave-one-out and transfer entropy methods. We then quantify the systemic significance of each sector in that network and further explore the impact of unexpected geopolitical risk in multiple-order moments on the significance of each sector during the sample period from January 4, 2011 to May 7, 2024. The results indicate that precious metals and traditional bulk metals are the two most significant sectors in the nonlinear causal network for information spillovers during the overall sample period, followed by traditional energy, new energy metals, and transition energy sectors; from a dynamic perspective, the significance of the transition energy and new energy metal sectors fluctuates with greater amplitude compared to other sectors. Regarding the impact of geopolitical risk on the significance of each sector, unexpected geopolitical risks have a more significant influence on energy and metal markets compared to generic geopolitical risks; moreover, the mean value of geopolitical risks exerts a greater effect on all sectors than its higher-order moment counterparts; all sectors except the traditional bulk metal sector, their systemic significance is sensitive to geopolitical shocks, especially above the 50th percentile. These results may offer effective references for financial risk management during the energy transition process.
{"title":"How unexpected geopolitical risk affect the nonlinear spillover among energy and metal markets?","authors":"Shupei Huang, Xinya Wang, Qiang Ji","doi":"10.1016/j.eneco.2024.108143","DOIUrl":"https://doi.org/10.1016/j.eneco.2024.108143","url":null,"abstract":"Geopolitical risk interacts with natural resource commodity markets closely and dynamically, which complicates the fluctuation spillover among those markets. We firstly uncover the overall and dynamic information spillover features among energy and metal markets, namely traditional energy, transition energy, new energy metals, precious metals, and traditional bulk metals in the nonlinear causal network constructed by combining the leave-one-out and transfer entropy methods. We then quantify the systemic significance of each sector in that network and further explore the impact of unexpected geopolitical risk in multiple-order moments on the significance of each sector during the sample period from January 4, 2011 to May 7, 2024. The results indicate that precious metals and traditional bulk metals are the two most significant sectors in the nonlinear causal network for information spillovers during the overall sample period, followed by traditional energy, new energy metals, and transition energy sectors; from a dynamic perspective, the significance of the transition energy and new energy metal sectors fluctuates with greater amplitude compared to other sectors. Regarding the impact of geopolitical risk on the significance of each sector, unexpected geopolitical risks have a more significant influence on energy and metal markets compared to generic geopolitical risks; moreover, the mean value of geopolitical risks exerts a greater effect on all sectors than its higher-order moment counterparts; all sectors except the traditional bulk metal sector, their systemic significance is sensitive to geopolitical shocks, especially above the 50th percentile. These results may offer effective references for financial risk management during the energy transition process.","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"50 1","pages":""},"PeriodicalIF":12.8,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142889329","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 : 2024-12-18DOI: 10.1016/j.eneco.2024.108140
Wei Wu, Shuochen Bi, Yunqiu Zhan, Xiao Gu
Considering the global awareness regarding the issue of climate change and global warming, several nations, including the United States, are focusing on achieving carbon neutrality goals. In doing so, this study examines how supply chain digitalization, green technologies, and energy efficiency influence greenhouse gas (GHG) emissions in the United States. This is the first empirical study evaluating how supply chain digitalization and energy efficiency influence GHG emissions, thus filling the gap in the literature. The study applied several quantile-based techniques, including wavelet quantile regression, quantile causality, and quantile regressions, as robustness checks used data spanning the period between 2000Q1 to 2022Q4. The results show that (i) across all periods and quantiles, a surge in supply chain digitalization intensifies GHG emissions in the United States; (ii) across all periods and quantiles, energy efficiency (oil and gas) lessens GHG emissions; (iii) across all periods and quantiles economic growth and financial globalization mitigate GHG emissions; and (iv) all the regressors can significantly predict GHG emissions. Based on these findings, policymakers in the United States should prioritize investments in green technologies and energy efficiency improvements, offering tax incentives, grants, and subsidies to businesses that adopt such practices.
{"title":"Supply chain digitalization and energy efficiency (gas and oil): How do they contribute to achieving carbon neutrality targets?","authors":"Wei Wu, Shuochen Bi, Yunqiu Zhan, Xiao Gu","doi":"10.1016/j.eneco.2024.108140","DOIUrl":"https://doi.org/10.1016/j.eneco.2024.108140","url":null,"abstract":"Considering the global awareness regarding the issue of climate change and global warming, several nations, including the United States, are focusing on achieving carbon neutrality goals. In doing so, this study examines how supply chain digitalization, green technologies, and energy efficiency influence greenhouse gas (GHG) emissions in the United States. This is the first empirical study evaluating how supply chain digitalization and energy efficiency influence GHG emissions, thus filling the gap in the literature. The study applied several quantile-based techniques, including wavelet quantile regression, quantile causality, and quantile regressions, as robustness checks used data spanning the period between 2000Q<ce:inf loc=\"post\">1</ce:inf> to 2022Q<ce:inf loc=\"post\">4</ce:inf>. The results show that (i) across all periods and quantiles, a surge in supply chain digitalization intensifies GHG emissions in the United States; (ii) across all periods and quantiles, energy efficiency (oil and gas) lessens GHG emissions; (iii) across all periods and quantiles economic growth and financial globalization mitigate GHG emissions; and (iv) all the regressors can significantly predict GHG emissions. Based on these findings, policymakers in the United States should prioritize investments in green technologies and energy efficiency improvements, offering tax incentives, grants, and subsidies to businesses that adopt such practices.","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"26 1","pages":""},"PeriodicalIF":12.8,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142889323","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 : 2024-12-17DOI: 10.1016/j.eneco.2024.108137
Chuan Zhao, Yutong Yin, Kun Wang, Xuying Ma
The Original Equipment Manufacturers (OEMs), serving as the paramount constituents of the manufacturing industry, have emerged as the focus of global economic competition. However, due to their cross-border operations associated with high carbon emissions, the OEMs' carbon reducing is constrained by both their foreign clients and local governments. This study utilizes a tripartite evolutionary game model to examine the complex interactions among OEMs, foreign clients, and the local government regarding the carbon pricing, technology sharing and the accountability mechanism. Evolution process, stability (instability) points, dynamic government policies, as well as carbon trading in different scenarios are also studied. The results show that precise government penalties push OEMs to actively reduce carbon emissions. Insufficient assistance or incentives will pull OEMs towards a negative carbon reduction. The push effect of foreign clients' assistance on OEMs carbon reducing surpasses that of the local government incentives when the carbon price rises. The technology sharing and accountability mechanism present a bidirectional effect that enables both OEMs and foreign clients achieve a win-win outcome in carbon reduction. This study examines the economic trade-off of carbon reduction in the OEM industry, especially under the push-pull pressures exerted by local government and foreign clients from both static and dynamic evolutionary perspectives.
{"title":"Push or pull? Identifying the OEMs' carbon reduction strategies based on the dynamic evolutionary game approach","authors":"Chuan Zhao, Yutong Yin, Kun Wang, Xuying Ma","doi":"10.1016/j.eneco.2024.108137","DOIUrl":"https://doi.org/10.1016/j.eneco.2024.108137","url":null,"abstract":"The Original Equipment Manufacturers (OEMs), serving as the paramount constituents of the manufacturing industry, have emerged as the focus of global economic competition. However, due to their cross-border operations associated with high carbon emissions, the OEMs' carbon reducing is constrained by both their foreign clients and local governments. This study utilizes a tripartite evolutionary game model to examine the complex interactions among OEMs, foreign clients, and the local government regarding the carbon pricing, technology sharing and the accountability mechanism. Evolution process, stability (instability) points, dynamic government policies, as well as carbon trading in different scenarios are also studied. The results show that precise government penalties push OEMs to actively reduce carbon emissions. Insufficient assistance or incentives will pull OEMs towards a negative carbon reduction. The push effect of foreign clients' assistance on OEMs carbon reducing surpasses that of the local government incentives when the carbon price rises. The technology sharing and accountability mechanism present a bidirectional effect that enables both OEMs and foreign clients achieve a win-win outcome in carbon reduction. This study examines the economic trade-off of carbon reduction in the OEM industry, especially under the push-pull pressures exerted by local government and foreign clients from both static and dynamic evolutionary perspectives.","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"114 1","pages":""},"PeriodicalIF":12.8,"publicationDate":"2024-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142889249","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 : 2024-12-16DOI: 10.1016/j.eneco.2024.108122
David Adeabah, Thu Phuong Pham
We investigate the tail risk spillover, co-movement, and causal effect between climate risk and international energy markets using daily data from 2010 to 2022. Employing Bua et al.'s (2022) innovative measures of climate risk and various methodologies, we discover an asymmetric spillover of tail risk from climate to energy markets, emphasizing systemic tail risk contagion in extreme market conditions. Notably, climate risk primarily transmits downside tail risk in bearish states. The dynamic, negative, time-varying correlation between climate risk and energy markets is highlighted by wavelets analysis. Our study underscores that fluctuations in climate physical and transition risks can predict energy market tail risks, revealing tail risk dependence. The results also indicate a unidirectional causality from climate risks to the energy market.
{"title":"Asymmetric tail risk spillover and co-movement between climate risk and the international energy market","authors":"David Adeabah, Thu Phuong Pham","doi":"10.1016/j.eneco.2024.108122","DOIUrl":"https://doi.org/10.1016/j.eneco.2024.108122","url":null,"abstract":"We investigate the tail risk spillover, co-movement, and causal effect between climate risk and international energy markets using daily data from 2010 to 2022. Employing Bua et al.'s (2022) innovative measures of climate risk and various methodologies, we discover an asymmetric spillover of tail risk from climate to energy markets, emphasizing systemic tail risk contagion in extreme market conditions. Notably, climate risk primarily transmits downside tail risk in bearish states. The dynamic, negative, time-varying correlation between climate risk and energy markets is highlighted by wavelets analysis. Our study underscores that fluctuations in climate physical and transition risks can predict energy market tail risks, revealing tail risk dependence. The results also indicate a unidirectional causality from climate risks to the energy market.","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"148 1","pages":""},"PeriodicalIF":12.8,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142873876","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 : 2024-12-14DOI: 10.1016/j.eneco.2024.108129
Jalal Siddiki, Prakash Singh
Using hourly data from June 1, 2020 to April 25, 2024, this paper first examines the characteristics of wholesale spot - Day Ahead Market (DAM) and Real Time Market (RTM) - prices in India. Second, we examine the impact on risk premiums (RPs) of changes in coal prices, the Russian-Ukraine war, demand conditions, economic policy uncertainty (EPU) and geopolitical risks (GPRs). We find that spot prices are highly volatile. Average hourly DAM prices are significantly higher than RTM prices for most hours during both weekdays and weekends, resulting in positive RPs and reflecting supply shortages and the presence of inefficiency in Indian wholesale electricity markets. The Russia-Ukraine war, EPU, GPRs, coal prices and high peak-hour demand increase RPs and are critical factors in explaining RPs. Results are robust across data frequencies and across sample periods. The results suggest increasing product diversification to reduce dependence on coal-based electricity production. These results have important policy implications for attempts to circumvent uncertainty, given that the Russia-Ukraine war has accelerated the rise in energy prices and brought significant uncertainty to Indian and global energy markets.
{"title":"The cost of uncertainty: Analysing the influence of coal price changes, the Russia-Ukraine war and geopolitical risk on risk premiums in the Indian electricity spot market","authors":"Jalal Siddiki, Prakash Singh","doi":"10.1016/j.eneco.2024.108129","DOIUrl":"https://doi.org/10.1016/j.eneco.2024.108129","url":null,"abstract":"Using hourly data from June 1, 2020 to April 25, 2024, this paper first examines the characteristics of wholesale spot - Day Ahead Market (DAM) and Real Time Market (RTM) - prices in India. Second, we examine the impact on risk premiums (RPs) of changes in coal prices, the Russian-Ukraine war, demand conditions, economic policy uncertainty (EPU) and geopolitical risks (GPRs). We find that spot prices are highly volatile. Average hourly DAM prices are significantly higher than RTM prices for most hours during both weekdays and weekends, resulting in positive RPs and reflecting supply shortages and the presence of inefficiency in Indian wholesale electricity markets. The Russia-Ukraine war, EPU, GPRs, coal prices and high peak-hour demand increase RPs and are critical factors in explaining RPs. Results are robust across data frequencies and across sample periods. The results suggest increasing product diversification to reduce dependence on coal-based electricity production. These results have important policy implications for attempts to circumvent uncertainty, given that the Russia-Ukraine war has accelerated the rise in energy prices and brought significant uncertainty to Indian and global energy markets.","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"128 1","pages":""},"PeriodicalIF":12.8,"publicationDate":"2024-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142873940","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 : 2024-12-13DOI: 10.1016/j.eneco.2024.108118
Laura Wallenko, Gabriel Bachner
In 2022 Austria has introduced a CO2 pricing scheme that aims at emissions from activities not covered by the EU Emissions Trading System. To increase social acceptability, the policy includes a region-specific compensation scheme, with higher transfers for households living in less densely populated areas. This is motivated by the hypothesis that rural households are hit harder by a CO2 price due to their relatively higher emission intensity of consumption. We test this hypothesis by using a recursive-dynamic computable general equilibrium model. Specifically, we compare the macroeconomic and distributional effects of three recycling schemes: i) region-specific transfers (the system in place), ii) no compensation but increased public consumption and iii) region- and income-specific transfers. At the macroeconomic level we find negative effects on GDP and welfare, compared to a baseline scenario without unilateral CO2 pricing under all three schemes. Interestingly, welfare effects are progressive irrespective of the recycling measure. Furthermore, we find that the scheme without compensation does not burden households in rural areas substantially more than those in urban areas. This results from an income side effect that works against the relatively stronger rise of consumer prices for rural households. However, the latter finding is sensitive to the labour market model closure, with a slightly higher burden for rural households under the assumption of full employment (as compared to our default closure with endogenous labour supply). Overall, we conclude that carbon pricing policies do not necessarily need to contain region- or income-based compensation schemes to enhance distributional equity.
{"title":"Are rural households hit hardest? Exploring the distributional effects of region-specific compensation payments in the Austrian CO2 pricing scheme","authors":"Laura Wallenko, Gabriel Bachner","doi":"10.1016/j.eneco.2024.108118","DOIUrl":"https://doi.org/10.1016/j.eneco.2024.108118","url":null,"abstract":"In 2022 Austria has introduced a CO<ce:inf loc=\"post\">2</ce:inf> pricing scheme that aims at emissions from activities not covered by the EU Emissions Trading System. To increase social acceptability, the policy includes a region-specific compensation scheme, with higher transfers for households living in less densely populated areas. This is motivated by the hypothesis that rural households are hit harder by a CO<ce:inf loc=\"post\">2</ce:inf> price due to their relatively higher emission intensity of consumption. We test this hypothesis by using a recursive-dynamic computable general equilibrium model. Specifically, we compare the macroeconomic and distributional effects of three recycling schemes: i) region-specific transfers (the system in place), ii) no compensation but increased public consumption and iii) region- and income-specific transfers. At the macroeconomic level we find negative effects on GDP and welfare, compared to a baseline scenario without unilateral CO<ce:inf loc=\"post\">2</ce:inf> pricing under all three schemes. Interestingly, welfare effects are progressive irrespective of the recycling measure. Furthermore, we find that the scheme without compensation does not burden households in rural areas substantially more than those in urban areas. This results from an income side effect that works against the relatively stronger rise of consumer prices for rural households. However, the latter finding is sensitive to the labour market model closure, with a slightly higher burden for rural households under the assumption of full employment (as compared to our default closure with endogenous labour supply). Overall, we conclude that carbon pricing policies do not necessarily need to contain region- or income-based compensation schemes to enhance distributional equity.","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"14 1","pages":""},"PeriodicalIF":12.8,"publicationDate":"2024-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142873877","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 : 2024-12-12DOI: 10.1016/j.eneco.2024.108108
Andu Berha, Sandeep Mohapatra
This paper examines the effect of ownership structure on the distribution of household electricity costs and its implications for income inequality. We leverage data on household electricity expenditure, income, and utility tariff structures to provide new insights into the comparative merits of alternative ownership regimes in the U.S. electricity sector. We use ownership discontinuities between adjacent statistical areas to establish causal effects. We find strong evidence that electricity costs are more regressive under cooperative and public ownership, resulting in undesirable distributional outcomes. Households served by cooperative and publicly-owned utilities spend a larger share of their income on electricity than those served by private utilities. We present suggestive evidence that high fixed charges and limited segmentation of economically diverse consumer groups are potential mechanisms driving the observed regressivity of electricity costs. Our findings highlight the role of firms ownership structures and pricing strategies in shaping existing income inequality by determining how energy burdens are distributed across income groups.
{"title":"Distributional effects of energy costs: Does firm ownership structure matter?","authors":"Andu Berha, Sandeep Mohapatra","doi":"10.1016/j.eneco.2024.108108","DOIUrl":"https://doi.org/10.1016/j.eneco.2024.108108","url":null,"abstract":"This paper examines the effect of ownership structure on the distribution of household electricity costs and its implications for income inequality. We leverage data on household electricity expenditure, income, and utility tariff structures to provide new insights into the comparative merits of alternative ownership regimes in the U.S. electricity sector. We use ownership discontinuities between adjacent statistical areas to establish causal effects. We find strong evidence that electricity costs are more regressive under cooperative and public ownership, resulting in undesirable distributional outcomes. Households served by cooperative and publicly-owned utilities spend a larger share of their income on electricity than those served by private utilities. We present suggestive evidence that high fixed charges and limited segmentation of economically diverse consumer groups are potential mechanisms driving the observed regressivity of electricity costs. Our findings highlight the role of firms ownership structures and pricing strategies in shaping existing income inequality by determining how energy burdens are distributed across income groups.","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"60 1","pages":""},"PeriodicalIF":12.8,"publicationDate":"2024-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142873880","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}
This paper investigates the impact of oil supply, demand, and risk shocks on U.S. state-level stock and bond returns, utilizing daily data from February 1994 to March 2024. It examines the individual effects of oil price shocks on each state's stock and bond returns and explores how fluctuations in oil prices influence the interdependence between state-level stock and bond markets. The findings reveal that oil demand shocks have a significant positive impact, while oil supply shocks have a significant negative impact on state-level stock returns. Although state-level bond returns also react to these supply and demand shocks, their response is statistically less significant than that of stock returns, indicating that cross-asset diversification is possible during periods of oil supply and demand shocks. However, both stock and bond returns are significantly and negatively affected by oil risk shocks, which implies limited opportunities for cross-asset diversification when oil price fluctuations are driven by risk factors. Additionally, the interdependence between U.S. equity and bond markets is more significantly influenced by oil risk shocks than by supply or demand shocks, suggesting an increase in the interconnectedness of stock and bond returns following an oil risk shock. Further analysis, using a reverse-MIDAS model to relate high-frequency connectedness measures to monthly oil price shocks, indicates that oil supply shocks positively and significantly impact stock market connectedness, while oil inventory demand shocks negatively affect bond market connectedness. Implications of our findings are discussed.
{"title":"Oil price shocks and the connectedness of US state-level financial markets","authors":"Onur Polat, Juncal Cunado, Oguzhan Cepni, Rangan Gupta","doi":"10.1016/j.eneco.2024.108128","DOIUrl":"https://doi.org/10.1016/j.eneco.2024.108128","url":null,"abstract":"This paper investigates the impact of oil supply, demand, and risk shocks on U.S. state-level stock and bond returns, utilizing daily data from February 1994 to March 2024. It examines the individual effects of oil price shocks on each state's stock and bond returns and explores how fluctuations in oil prices influence the interdependence between state-level stock and bond markets. The findings reveal that oil demand shocks have a significant positive impact, while oil supply shocks have a significant negative impact on state-level stock returns. Although state-level bond returns also react to these supply and demand shocks, their response is statistically less significant than that of stock returns, indicating that cross-asset diversification is possible during periods of oil supply and demand shocks. However, both stock and bond returns are significantly and negatively affected by oil risk shocks, which implies limited opportunities for cross-asset diversification when oil price fluctuations are driven by risk factors. Additionally, the interdependence between U.S. equity and bond markets is more significantly influenced by oil risk shocks than by supply or demand shocks, suggesting an increase in the interconnectedness of stock and bond returns following an oil risk shock. Further analysis, using a reverse-MIDAS model to relate high-frequency connectedness measures to monthly oil price shocks, indicates that oil supply shocks positively and significantly impact stock market connectedness, while oil inventory demand shocks negatively affect bond market connectedness. Implications of our findings are discussed.","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"53 1","pages":""},"PeriodicalIF":12.8,"publicationDate":"2024-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142873936","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 : 2024-12-12DOI: 10.1016/j.eneco.2024.108126
Yongguang Zhu, Yuna Gong, Lanyong Yang, Deyi Xu
This study investigates the dynamic volatility spillovers among critical metals, traditional energy, and clean energy markets using a sophisticated frequency-domain approach. Leveraging the improved complete ensemble empirical mode decomposition with adaptive noise and time-varying parameter vector autoregression models, we decompose daily logarithmic returns into high, middle, and low-frequency components. Our findings reveal significant heterogeneity in spillover effects across different frequencies, industries, and commodity categories. Clean energy sectors emerge as prominent contributors to market spillovers, reflecting their increasing sensitivity to short-term market dynamics. In contrast, traditional energy markets transition from being spillover sources to net recipients as the energy transition accelerates. Critical metals, particularly lithium and platinum, play a dominant role in long-term market integration, highlighting their growing importance in the global energy transition. These results provide actionable insights for policymakers and investors seeking to manage risks and optimize strategies in the evolving energy landscape.
{"title":"The rise of clean energy markets: Evidence from frequency-domain spillover effects between critical metals and energy markets","authors":"Yongguang Zhu, Yuna Gong, Lanyong Yang, Deyi Xu","doi":"10.1016/j.eneco.2024.108126","DOIUrl":"https://doi.org/10.1016/j.eneco.2024.108126","url":null,"abstract":"This study investigates the dynamic volatility spillovers among critical metals, traditional energy, and clean energy markets using a sophisticated frequency-domain approach. Leveraging the improved complete ensemble empirical mode decomposition with adaptive noise and time-varying parameter vector autoregression models, we decompose daily logarithmic returns into high, middle, and low-frequency components. Our findings reveal significant heterogeneity in spillover effects across different frequencies, industries, and commodity categories. Clean energy sectors emerge as prominent contributors to market spillovers, reflecting their increasing sensitivity to short-term market dynamics. In contrast, traditional energy markets transition from being spillover sources to net recipients as the energy transition accelerates. Critical metals, particularly lithium and platinum, play a dominant role in long-term market integration, highlighting their growing importance in the global energy transition. These results provide actionable insights for policymakers and investors seeking to manage risks and optimize strategies in the evolving energy landscape.","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"14 1","pages":""},"PeriodicalIF":12.8,"publicationDate":"2024-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142873879","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}
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