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The growing importance of natural gas as a predictor for retail electricity prices in US

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  • Alexopoulos, Thomas A.

Abstract

In the literature, there are tests about long and or short Granger causality between primary energy sources such as natural gas and secondary energy sources like electricity. Nevertheless the existence of a causal relationship or not, cannot clearly illustrate the dynamics in their relationship over time. Towards this direction, we apply a one step ahead rolling forecast and examine the performance of the average cost of natural gas as a predictor for retail electricity prices at national and regional level over time. Our analysis answers if, how and when the cost of natural gas becomes a significant predictor of electricity prices. Besides lower natural gas prices, the existence of sufficient gas infrastructures or a competitive market environment or both of them is needed in order to couple retail electricity prices with the cost of natural gas. This growing importance must be taken into account from policy makers by allowing additional gas based stations in the main-grid but at the same time avoiding the risks from the natural gas price volatility.

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  • Alexopoulos, Thomas A., 2017. "The growing importance of natural gas as a predictor for retail electricity prices in US," Energy, Elsevier, vol. 137(C), pages 219-233.
    • Handle: RePEc:eee:energy:v:137:y:2017:i:c:p:219-233
    DOI: 10.1016/j.energy.2017.07.002
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    1. Junjie Sun & Leigh Tesfatsion, 2007. "Dynamic Testing of Wholesale Power Market Designs: An Open-Source Agent-Based Framework," Computational Economics, Springer;Society for Computational Economics, vol. 30(3), pages 291-327, October.
    2. Burtraw, Dallas & Palmer, Karen & Paul, Anthony & Woerman, Matt, 2012. "Secular Trends, Environmental Regulation, and Electricity Markets," RFF Working Paper Series dp-12-15, Resources for the Future.
    3. Pérez-García, Julián & Moral-Carcedo, Julián, 2016. "Analysis and long term forecasting of electricity demand trough a decomposition model: A case study for Spain," Energy, Elsevier, vol. 97(C), pages 127-143.
    4. Osman, Mohamed & Gachino, Geoffrey & Hoque, Ariful, 2016. "Electricity consumption and economic growth in the GCC countries: Panel data analysis," Energy Policy, Elsevier, vol. 98(C), pages 318-327.
    5. Yock Y. Chong & David F. Hendry, 1986. "Econometric Evaluation of Linear Macro-Economic Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 53(4), pages 671-690.
    6. Ozturk, Ilhan & Acaravci, Ali, 2010. "The causal relationship between energy consumption and GDP in Albania, Bulgaria, Hungary and Romania: Evidence from ARDL bound testing approach," Applied Energy, Elsevier, vol. 87(6), pages 1938-1943, June.
    7. Severin Borenstein & James Bushnell, 2015. "The US Electricity Industry After 20 Years of Restructuring," Annual Review of Economics, Annual Reviews, vol. 7(1), pages 437-463, August.
    8. Eric Guerci & Mohammad Ali Rastegar & Silvano Cincotti, 2010. "Agent-based modeling and simulation of competitive wholesale electricity markets," Post-Print halshs-00871063, HAL.
    9. Timmermann, Allan, 2006. "Forecast Combinations," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 4, pages 135-196, Elsevier.
    10. Capistrán, Carlos & Timmermann, Allan, 2009. "Forecast Combination With Entry and Exit of Experts," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 428-440.
    11. Cowan, Wendy N. & Chang, Tsangyao & Inglesi-Lotz, Roula & Gupta, Rangan, 2014. "The nexus of electricity consumption, economic growth and CO2 emissions in the BRICS countries," Energy Policy, Elsevier, vol. 66(C), pages 359-368.
    12. Kristiansen, Tarjei, 2012. "Forecasting Nord Pool day-ahead prices with an autoregressive model," Energy Policy, Elsevier, vol. 49(C), pages 328-332.
    13. García-Ascanio, Carolina & Maté, Carlos, 2010. "Electric power demand forecasting using interval time series: A comparison between VAR and iMLP," Energy Policy, Elsevier, vol. 38(2), pages 715-725, February.
    14. 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.
    15. 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.
    16. He, Kaijian & Yu, Lean & Tang, Ling, 2015. "Electricity price forecasting with a BED (Bivariate EMD Denoising) methodology," Energy, Elsevier, vol. 91(C), pages 601-609.
    17. Barnett, A.H. & Reutter, Keith A. & Thompson, Henry, 2005. "The first step in restructuring the US electric industry," Energy Economics, Elsevier, vol. 27(2), pages 225-235, March.
    18. Mazur, Allan, 2011. "Does increasing energy or electricity consumption improve quality of life in industrial nations?," Energy Policy, Elsevier, vol. 39(5), pages 2568-2572, May.
    19. Brown, Stephen P.A. & Krupnick, Alan, 2010. "Abundant Shale Gas Resources: Long-Term Implications for U.S. Natural Gas Markets," RFF Working Paper Series dp-10-41, Resources for the Future.
    20. Furió, Dolores & Chuliá, Helena, 2012. "Price and volatility dynamics between electricity and fuel costs: Some evidence for Spain," Energy Economics, Elsevier, vol. 34(6), pages 2058-2065.
    21. Knudsen, Brage Rugstad & Whitson, Curtis H. & Foss, Bjarne, 2014. "Shale-gas scheduling for natural-gas supply in electric power production," Energy, Elsevier, vol. 78(C), pages 165-182.
    22. Nguyen, Hang T. & Nabney, Ian T., 2010. "Short-term electricity demand and gas price forecasts using wavelet transforms and adaptive models," Energy, Elsevier, vol. 35(9), pages 3674-3685.
    23. Weron, Rafal & Misiorek, Adam, 2008. "Forecasting spot electricity prices: A comparison of parametric and semiparametric time series models," International Journal of Forecasting, Elsevier, vol. 24(4), pages 744-763.
    24. Woo, Chi-Keung & Olson, Arne & Horowitz, Ira & Luk, Stephen, 2006. "Bi-directional causality in California's electricity and natural-gas markets," Energy Policy, Elsevier, vol. 34(15), pages 2060-2070, October.
    25. G. Elliott & C. Granger & A. Timmermann (ed.), 2006. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 1, number 1.
    26. Kowalska-Pyzalska, Anna & Maciejowska, Katarzyna & Suszczyński, Karol & Sznajd-Weron, Katarzyna & Weron, Rafał, 2014. "Turning green: Agent-based modeling of the adoption of dynamic electricity tariffs," Energy Policy, Elsevier, vol. 72(C), pages 164-174.
    27. Wolde-Rufael, Yemane, 2004. "Disaggregated industrial energy consumption and GDP: the case of Shanghai, 1952-1999," Energy Economics, Elsevier, vol. 26(1), pages 69-75, January.
    28. Durbin, James & Koopman, Siem Jan, 2012. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, edition 2, number 9780199641178, Decembrie.
    29. Koopman, Siem Jan & Ooms, Marius & Carnero, M. Angeles, 2007. "Periodic Seasonal Reg-ARFIMAGARCH Models for Daily Electricity Spot Prices," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 16-27, March.
    30. Hu, Jin-Li & Lin, Cheng-Hsun, 2008. "Disaggregated energy consumption and GDP in Taiwan: A threshold co-integration analysis," Energy Economics, Elsevier, vol. 30(5), pages 2342-2358, September.
    31. Bolinger, Mark & Wiser, Ryan & Golove, William, 2006. "Accounting for fuel price risk when comparing renewable to gas-fired generation: the role of forward natural gas prices," Energy Policy, Elsevier, vol. 34(6), pages 706-720, April.
    32. Chae, Yeoungjin & Kim, Myunghwan & Yoo, Seung-Hoon, 2012. "Does natural gas fuel price cause system marginal price, vice-versa, or neither? A causality analysis," Energy, Elsevier, vol. 47(1), pages 199-204.
    33. Brown, Stephen P.A. & Yücel, Mine K., 2008. "Deliverability and regional pricing in U.S. natural gas markets," Energy Economics, Elsevier, vol. 30(5), pages 2441-2453, September.
    34. Apostolos Serletis & Akbar Shahmoradi, 2007. "Measuring and Testing Natural Gas and Electricity Markets Volatility: Evidence from Alberta's Deregulated Markets," World Scientific Book Chapters, in: Quantitative And Empirical Analysis Of Energy Markets, chapter 16, pages 205-220, World Scientific Publishing Co. Pte. Ltd..
    35. Lueken, Roger & Klima, Kelly & Griffin, W. Michael & Apt, Jay, 2016. "The climate and health effects of a USA switch from coal to gas electricity generation," Energy, Elsevier, vol. 109(C), pages 1160-1166.
    36. Bruno Bosco & Lucia Parisio & Matteo Pelagatti & Fabio Baldi, 2010. "Long-run relations in european electricity prices," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(5), pages 805-832.
    37. Nakajima, Tadahiro & Hamori, Shigeyuki, 2013. "Testing causal relationships between wholesale electricity prices and primary energy prices," Energy Policy, Elsevier, vol. 62(C), pages 869-877.
    38. Bannai, Masaaki & Tomita, Yasushi & Ishida, Yasushi & Miyazaki, Takahiko & Akisawa, Atsushi & Kashiwagi, Takao, 2007. "Risk hedging against the fuel price fluctuation in energy service business," Energy, Elsevier, vol. 32(11), pages 2051-2060.
    39. Smil, Vaclav, 2005. "Creating the Twentieth Century: Technical Innovations of 1867-1914 and Their Lasting Impact," OUP Catalogue, Oxford University Press, number 9780195168747, Decembrie.
    40. Rafal Weron, 2006. "Modeling and Forecasting Electricity Loads and Prices: A Statistical Approach," HSC Books, Hugo Steinhaus Center, Wroclaw University of Technology, number hsbook0601.
    41. Linn, Joshua & Anna Muehlenbachs, Lucija & Wang, Yshuang, 2014. "How Do Natural Gas Prices Affect Electricity Consumers and the Environment?," RFF Working Paper Series dp-14-19, Resources for the Future.
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    More about this item

    Keywords

    Retail electricity price; Cost of natural gas; Rolling forecast; NERC regions; Time-dependent relationship;
    All these keywords.

    JEL classification:

    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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