IDEAS home Printed from https://ideas.repec.org/a/eco/journ2/2018-01-6.html
   My bibliography  Save this article

Using a Rolling Vector Error Correction Model to Model Static and Dynamic Causal Relations between Electricity Spot Price and Related Fundamental Factors: The Case of Greek Electricity Market

Author

Listed:
  • George P. Papaioannou

    (Department of Research, Technology & Development, Independent Power Transmission Operator S.A., 89 Dyrrachiou & Kifisou Str. Gr, 104 43, Athens, Greece,)

  • Christos Dikaiakos

    (Department of Mathematics, Center for Research and Applications in Nonlinear Systems, University of Patras, Patras 26 500, Greece,)

  • Akylas Stratigakos

    (Department of Electrical and Computer Engineering, University of Patras, Patras)

  • Anargyros Dramountanis

    (Department of Electrical and Computer Engineering, University of Patras, Patras)

  • Antonio T. Alexandridis

    (Department of Electrical and Computer Engineering, University of Patras, Patras)

Abstract

The purpose of this study is to investigate short and long run relationships between electricity spot prices in Greece, Brent oil, natural gas, lignite fuel cost and carbon allowances using daily data from 2007 to 2014. Static and dynamic Johansen test are applied in order to identify long run relations and also to assess the evolution over time in the level of cointegration. Additionally we test for Granger Causality in a Vector error correction model and embrace impulse response and variance decomposition techniques to model the dynamic response of electricity prices in excitation of another variable. Overall our results suggest an important long run relation between spot electricity prices in Greece, natural gas price and carbon allowances, while in the short run electricity prices are not affected by any of the other variables, results that are of practical importance for the market regulator as well as the wholesale market participants.

Suggested Citation

  • George P. Papaioannou & Christos Dikaiakos & Akylas Stratigakos & Anargyros Dramountanis & Antonio T. Alexandridis, 2018. "Using a Rolling Vector Error Correction Model to Model Static and Dynamic Causal Relations between Electricity Spot Price and Related Fundamental Factors: The Case of Greek Electricity Market," International Journal of Energy Economics and Policy, Econjournals, vol. 8(1), pages 38-54.
    • Handle: RePEc:eco:journ2:2018-01-6
    as

    Download full text from publisher

    File URL: https://www.econjournals.com/index.php/ijeep/article/download/5624/3491
    Download Restriction: no
    File URL: https://www.econjournals.com/index.php/ijeep/article/view/5624/3491
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Choi, Kyongwook & Hammoudeh, Shawkat, 2010. "Volatility behavior of oil, industrial commodity and stock markets in a regime-switching environment," Energy Policy, Elsevier, vol. 38(8), pages 4388-4399, August.
    2. Lance J. Bachmeier & James M. Griffin, 2006. "Testing for Market Integration: Crude Oil, Coal, and Natural Gas," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 55-72.
    3. Daskalakis, George & Psychoyios, Dimitris & Markellos, Raphael N., 2009. "Modeling CO2 emission allowance prices and derivatives: Evidence from the European trading scheme," Journal of Banking & Finance, Elsevier, vol. 33(7), pages 1230-1241, July.
    4. Frank Asche & Petter Osmundsen & Maria Sandsmark, 2006. "The UK Market for Natural Gas, Oil and Electricity: Are the Prices Decoupled?," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 27-40.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Moon, Jongwoo & Jung, Tae Yong, 2020. "A critical review of Korea's long-term contract for renewable energy auctions: The relationship between the import price of liquefied natural gas and system marginal price," Utilities Policy, Elsevier, vol. 67(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Abdullahi Alim & Peter R. Hartley & Yihui Lan, 2018. "Asian Spot Prices for LNG and other Energy Commodities," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    2. Hengyun Ma & Les Oxley & John Gibson, 2008. "Testing for Energy Market Integration in China," Working Papers in Economics 08/12, University of Canterbury, Department of Economics and Finance.
    3. Gatfaoui, Hayette, 2016. "Linking the gas and oil markets with the stock market: Investigating the U.S. relationship," Energy Economics, Elsevier, vol. 53(C), pages 5-16.
    4. Lindback, Morten & Osmundsen, Petter & Øglend, Atle, 2013. "Shale Gas and the Relationship between U.S. Natural Gas, Liquified Petroleum Gases and Oil Market," UiS Working Papers in Economics and Finance 2013/5, University of Stavanger.
    5. Ramberg, David J. & Henry Chen, Y.H. & Paltsev, Sergey & Parsons, John E., 2017. "The economic viability of gas-to-liquids technology and the crude oil–natural gas price relationship," Energy Economics, Elsevier, vol. 63(C), pages 13-21.
    6. Gatfaoui, Hayette, 2015. "Pricing the (European) option to switch between two energy sources: An application to crude oil and natural gas," Energy Policy, Elsevier, vol. 87(C), pages 270-283.
    7. Zied Ftiti & Kais Tissaoui & Sahbi Boubaker, 2022. "On the relationship between oil and gas markets: a new forecasting framework based on a machine learning approach," Annals of Operations Research, Springer, vol. 313(2), pages 915-943, June.
    8. Zaighum, Isma & Aman, Ameenullah & Sharif, Arshian & Suleman, Muhammad Tahir, 2021. "Do energy prices interact with global Islamic stocks? Fresh insights from quantile ARDL approach," Resources Policy, Elsevier, vol. 72(C).
    9. Chevallier, Julien, 2011. "A model of carbon price interactions with macroeconomic and energy dynamics," Energy Economics, Elsevier, vol. 33(6), pages 1295-1312.
    10. Kentaka Aruga & Shunsuke Managi, 2013. "Linkages among the US energy futures markets," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 36(1), pages 13-26.
    11. Regnard, Nazim & Zakoïan, Jean-Michel, 2011. "A conditionally heteroskedastic model with time-varying coefficients for daily gas spot prices," Energy Economics, Elsevier, vol. 33(6), pages 1240-1251.
    12. Panagiotis G. Papaioannou & George P. Papaioannou & Kostas Siettos & Akylas Stratigakos & Christos Dikaiakos, 2017. "Dynamic Conditional Correlation between Electricity and Stock markets during the Financial Crisis in Greece," Papers 1708.07063, arXiv.org.
    13. Cristina Bencivenga & Giulia Sargenti, 2010. "Crucial relationship among energy commodity prices," Working Papers 5, Doctoral School of Economics, Sapienza University of Rome, revised 2010.
    14. Asche, Frank & Misund, Bård & Sikveland, Marius, 2013. "The relationship between spot and contract gas prices in Europe," Energy Economics, Elsevier, vol. 38(C), pages 212-217.
    15. Subhani, Muhammad Imtiaz & Hasan, Syed Akif & Osman, Ms. Amber, 2012. "Are the Prices of Light Diesel Oil, Gasoline, CNG and Kerosene Oil Co-Integrated?," MPRA Paper 45142, University Library of Munich, Germany.
    16. Ma, Hengyun & Oxley, Les, 2010. "The integration of major fuel source markets in China: Evidence from panel cointegration tests," Energy Economics, Elsevier, vol. 32(5), pages 1139-1146, September.
    17. Asche, Frank & Oglend, Atle & Osmundsen, Petter, 2012. "Gas versus oil prices the impact of shale gas," Energy Policy, Elsevier, vol. 47(C), pages 117-124.
    18. Sensoy, Ahmet & Hacihasanoglu, Erk & Nguyen, Duc Khuong, 2015. "Dynamic convergence of commodity futures: Not all types of commodities are alike," Resources Policy, Elsevier, vol. 44(C), pages 150-160.
    19. Ma, Hengyun & Oxley, Les, 2011. "Are China's energy markets cointegrated?," China Economic Review, Elsevier, vol. 22(3), pages 398-407, September.
    20. Potts, Todd B. & Yerger, David B., 2016. "Marcellus Shale and structural breaks in oil and gas markets: The case of Pennsylvania," Energy Economics, Elsevier, vol. 57(C), pages 50-58.

    More about this item

    Keywords

    Vector Error Correction; Electricity Markets; Fuel Markets;
    All these keywords.

    JEL classification:

    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eco:journ2:2018-01-6. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Ilhan Ozturk (email available below). General contact details of provider: http://www.econjournals.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.