Energy prices and CO2 emission allowance prices: A quantile regression approach |
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| Affiliation: | 1. LeBow College of Business, Drexel University, Philadelphia, PA, USA;2. IPAG Lab, IPAG Business School, 184 Boulevard Saint-Germain, 75006, France;3. London School of Economics, LSE Alumni Association, London, United Kingdom;4. Department of Economics and Economic Policies Research Unit (NIPE), University of Minho, Braga, Portugal;1. Collaborative Innovation Center for Energy Economics and Energy Policy, China Institute for Studies in Energy Policy, Xiamen University, Fujian, 361005, PR China;2. Newhuadu Business School, Minjiang University, Fuzhou 350108, China;1. Mercator Research Institute on Global Commons and Climate Change, Resources and International Trade, Torgauer Straße 12-15, 10829 Berlin, Germany;2. International Institute for Applied Systems Analysis, Ecosystems Services & Management, Schlossplatz 1, 2361 Laxenburg, Austria;3. Potsdam Institute for Climate Impact Research, Telegrafenberg A31, 14473 Potsdam, Germany;4. Technische Universität Berlin, Strasse des 17. Juni 135, 10623 Berlin, Germany;1. School of Finance, Zhejiang University of Finance and Economics, Hangzhou 310038 China;2. The Center for Research of Regulation and Policy of Zhejiang Province, Hangzhou 310018 China;3. China Academy of Financial Research, Zhejiang University of Finance & Economics, Hangzhou 310038 China;4. School of law, Zhejiang University of Finance and Economics, Hangzhou 310038 China;1. M & A project manager at Vattenfall, Sweden;2. University of Groningen, Energy and Sustainability Centre, Faculty of Economics and Business, PO Box 800, 9700 AV Groningen, The Netherlands;3. Centre for Responsible Banking & Finance, School of Management, University of Saint Andrews, The Gateway, North Haugh, St. Andrews, KY16 9SS, Scotland, UK;1. Business School of Hunan University, Changsha 410082, PR China;2. Center for Resource and Environmental Management, Hunan University, Changsha 410082, PR China |
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| Abstract: | We use a quantile regression framework to investigate the impact of changes in crude oil prices, natural gas prices, coal prices, and electricity prices on the distribution of the CO2 emission allowance prices in the United States. We find that: (i) an increase in the crude oil price generates a substantial drop in the carbon prices when the latter is very high; (ii) changes in the natural gas prices have a negative effect on the carbon prices when they are very low but have a positive effect when they are quite high; (iii) the impact of the changes in the electricity prices on the carbon prices can be positive in the right tail of the distribution; and (iv) the coal prices exert a negative effect on the carbon prices. |
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| Keywords: | Energy prices Quantile regression |
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