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Spillover Effects among Electricity Prices, Traditional Energy Prices and Carbon Market under Climate Risk

Author

Listed:
  • Donglan Liu

    (State Grid Shandong Electric Power Research Institute, Jinan 250003, China)

  • Xin Liu

    (State Grid Shandong Electric Power Research Institute, Jinan 250003, China)

  • Kun Guo

    (School of Economics and Management, University of Chinese Academy of Sciences, Beijing 101408, China)

  • Qiang Ji

    (Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China
    School of Public Policy and Management, University of Chinese Academy of Sciences, Beijing 100190, China)

  • Yingxian Chang

    (State Grid Shandong Electric Power Company, Jinan 250001, China)

Abstract

With the increase in global geopolitical risks and the frequent occurrence of extreme climate in recent years, the electricity prices in Europe have shown large fluctuations. Electricity price has an important impact on the cost of production and living, while electricity demand will also affect other energy markets. A double-layer system based on the spillover effects from a systematic perspective is constructed in this paper to explore the connectedness between different electricity markets and other related energy markets in Europe, considering the impact of climate risks. The results show that there are certain spillover effects among electricity markets in different countries, with a temporary upward trend in the beginning of the Russia–Ukraine conflict, and the electricity markets in the UK and Germany have a more important role in Europe. There are two-way spillover effects between the electricity market and fossil fuel markets, carbon market and carbon emission. Since 2022, the electricity market is affected by gas prices, while it has a certain impact on carbon emissions. The heating degree day ( HDD ) has significant spillover effects on the electricity market and other energy markets, while the spillover effects of the cooling degree day ( CDD ) are relatively small.

Suggested Citation

  • Donglan Liu & Xin Liu & Kun Guo & Qiang Ji & Yingxian Chang, 2023. "Spillover Effects among Electricity Prices, Traditional Energy Prices and Carbon Market under Climate Risk," IJERPH, MDPI, vol. 20(2), pages 1-18, January.
    • Handle: RePEc:gam:jijerp:v:20:y:2023:i:2:p:1116-:d:1028983
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    References listed on IDEAS

    as
    1. de Menezes, Lilian M. & Houllier, Melanie A. & Tamvakis, Michael, 2016. "Time-varying convergence in European electricity spot markets and their association with carbon and fuel prices," Energy Policy, Elsevier, vol. 88(C), pages 613-627.
    2. Guo, Jiaqi & Long, Shaobo & Luo, Weijie, 2022. "Nonlinear effects of climate policy uncertainty and financial speculation on the global prices of oil and gas," International Review of Financial Analysis, Elsevier, vol. 83(C).
    3. Taseska, Verica & Markovska, Natasa & Callaway, John M., 2012. "Evaluation of climate change impacts on energy demand," Energy, Elsevier, vol. 48(1), pages 88-95.
    4. Grillini, Stefano & Ozkan, Aydin & Sharma, Abhijit, 2022. "Static and dynamic liquidity spillovers in the Eurozone: The role of financial contagion and the Covid-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 83(C).
    5. Weron, Rafał, 2014. "Electricity price forecasting: A review of the state-of-the-art with a look into the future," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1030-1081.
    6. Ziel, Florian & Steinert, Rick, 2018. "Probabilistic mid- and long-term electricity price forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 251-266.
    7. Ohler, Adrienne & Mohammadi, Hassan & Loomis, David G., 2020. "Electricity restructuring and the relationship between fuel costs and electricity prices for industrial and residential customers," Energy Policy, Elsevier, vol. 142(C).
    8. Gary W. Emery & Qingfeng (Wilson) Liu, 2002. "An analysis of the relationship between electricity and natural‐gas futures prices," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 22(2), pages 95-122, February.
    9. Georgios Maris & Floros Flouros, 2021. "The Green Deal, National Energy and Climate Plans in Europe: Member States’ Compliance and Strategies," Administrative Sciences, MDPI, vol. 11(3), pages 1-17, July.
    10. Trujillo-Baute, Elisa & del Río, Pablo & Mir-Artigues, Pere, 2018. "Analysing the impact of renewable energy regulation on retail electricity prices," Energy Policy, Elsevier, vol. 114(C), pages 153-164.
    11. Gil-Alana, Luis A. & Mudida, Robert & Carcel, Hector, 2017. "Shocks affecting electricity prices in Kenya, a fractional integration study," Energy, Elsevier, vol. 124(C), pages 521-530.
    12. Deschatre, Thomas & Féron, Olivier & Gruet, Pierre, 2021. "A survey of electricity spot and futures price models for risk management applications," Energy Economics, Elsevier, vol. 102(C).
    13. Pietzcker, Robert C. & Osorio, Sebastian & Rodrigues, Renato, 2021. "Tightening EU ETS targets in line with the European Green Deal: Impacts on the decarbonization of the EU power sector," Applied Energy, Elsevier, vol. 293(C).
    14. Tselika, Kyriaki, 2022. "The impact of variable renewables on the distribution of hourly electricity prices and their variability: A panel approach," Discussion Papers 2022/4, Norwegian School of Economics, Department of Business and Management Science.
    15. Kristjanpoller, Werner & Minutolo, Marcel C., 2021. "Asymmetric multi-fractal cross-correlations of the price of electricity in the US with crude oil and the natural gas," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 572(C).
    16. Ozturk, Serda Selin & Demirer, Riza & Gupta, Rangan, 2022. "Climate uncertainty and carbon emissions prices: The relative roles of transition and physical climate risks," Economics Letters, Elsevier, vol. 217(C).
    17. Thomas Deschatre & Olivier F'eron & Pierre Gruet, 2021. "A survey of electricity spot and futures price models for risk management applications," Papers 2103.16918, arXiv.org, revised Jul 2021.
    18. Heidarpanah, Mohammadreza & Hooshyaripor, Farhad & Fazeli, Meysam, 2023. "Daily electricity price forecasting using artificial intelligence models in the Iranian electricity market," Energy, Elsevier, vol. 263(PE).
    19. Rowińska, Paulina A. & Veraart, Almut E.D. & Gruet, Pierre, 2021. "A multi-factor approach to modelling the impact of wind energy on electricity spot prices," Energy Economics, Elsevier, vol. 104(C).
    20. Tselika, Kyriaki, 2022. "The impact of variable renewables on the distribution of hourly electricity prices and their variability: A panel approach," Energy Economics, Elsevier, vol. 113(C).
    21. Mosquera-López, Stephanía & Nursimulu, Anjali, 2019. "Drivers of electricity price dynamics: Comparative analysis of spot and futures markets," Energy Policy, Elsevier, vol. 126(C), pages 76-87.
    22. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    23. Florian Ziel & Rick Steinert, 2017. "Probabilistic Mid- and Long-Term Electricity Price Forecasting," Papers 1703.10806, arXiv.org, revised May 2018.
    24. Müller, Gernot & Seibert, Armin, 2019. "Bayesian estimation of stable CARMA spot models for electricity prices," Energy Economics, Elsevier, vol. 78(C), pages 267-277.
    25. Woo, C.K. & Olson, A. & Chen, Y. & Moore, J. & Schlag, N. & Ong, A. & Ho, T., 2017. "Does California's CO2 price affect wholesale electricity prices in the Western U.S.A.?," Energy Policy, Elsevier, vol. 110(C), pages 9-19.
    26. Borovkova, Svetlana & Schmeck, Maren Diane, 2017. "Electricity price modeling with stochastic time change," Energy Economics, Elsevier, vol. 63(C), pages 51-65.
    27. Francis A. Longstaff & Ashley W. Wang, 2004. "Electricity Forward Prices: A High-Frequency Empirical Analysis," Journal of Finance, American Finance Association, vol. 59(4), pages 1877-1900, August.
    28. Ji, Qiang & Bouri, Elie & Lau, Chi Keung Marco & Roubaud, David, 2019. "Dynamic connectedness and integration in cryptocurrency markets," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 257-272.
    29. Lin, Jianing & Bao, Minglei & Liang, Ziyang & Sang, Maosheng & Ding, Yi, 2022. "Spatio-temporal evaluation of electricity price risk considering multiple uncertainties under extreme cold weather," Applied Energy, Elsevier, vol. 328(C).
    30. Pietzcker, Robert & Osorio, Sebastian & Rodrigues, Renato, 2021. "Tightening EU ETS targets in line with the European Green Deal: Impacts on the decarbonization of the EU power sector," EconStor Preprints 222579, ZBW - Leibniz Information Centre for Economics, revised 2021.
    31. Schöniger, Franziska & Morawetz, Ulrich B., 2022. "What comes down must go up: Why fluctuating renewable energy does not necessarily increase electricity spot price variance in Europe," Energy Economics, Elsevier, vol. 111(C).
    Full references (including those not matched with items on IDEAS)

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    1. Gupta, Rangan & Nel, Jacobus & Salisu, Afees A. & Ji, Qiang, 2023. "Predictability of economic slowdowns in advanced countries over eight centuries: The role of climate risks," Finance Research Letters, Elsevier, vol. 54(C).
    2. Shen, Yiran & Sun, Xiaolei & Ji, Qiang & Zhang, Dayong, 2023. "Climate events matter in the global natural gas market," Energy Economics, Elsevier, vol. 125(C).
    3. Dan Xiong & Yiming Yan & Mengjiao Qin & Sensen Wu & Renyi Liu, 2023. "Quantitative Assessment of the Impact of Extreme Events on Electricity Consumption," Energies, MDPI, vol. 17(1), pages 1-18, December.
    4. Guo, Kun & Liu, Fengqi & Sun, Xiaolei & Zhang, Dayong & Ji, Qiang, 2023. "Predicting natural gas futures’ volatility using climate risks," Finance Research Letters, Elsevier, vol. 55(PA).

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