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Time Varying Long Run Dynamics And Convergence In The Uk Energy Market

Author

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  • Melanie Houllier
  • Lilian M. De Menezes
  • Michael Tamvakis

Abstract

For a long time fuels such as gas, coal or oil have been the most important cost items for power generation accounting for 70% of the variable costs (Crampes and Fabra, 2005), since they were usually marginal generation technologies that set wholesale prices (Bosco et al., 2010). Intuitively, long run dynamics of electricity prices should therefore reflect fuel price developments, at least in markets with a significant share in their energy mix. However, with the EU Directive 2009/28/EC, EU Member States have established national action plans, which set the share of energy from renewable sources for 2020 (20-20-20 targets) (EC, 2009). The EU Renewable Energy Target decreed that 15% of all energy (or 30-35% of electricity) is to be generated by RES-E by 2020 in the UK. This change in energy mix may have altered traditional associations between fuel inputs and price behaviour, at least in the short run. We therefore identify changes in wholesale price dynamics, using weekdaily APX spot prices from February 2003 to October 2013, and investigate their association with gas and coal prices as well as wind penetration levels. Localized autocorrelation (Cardinali and Nason, 2013) are used to identify changes of long run dynamics in the time series. Cointegration analysis (Engle and Granger 1987) and fractional co-integration analysis are then employed to investigare common long run dynamics in the UK energy sector for stationary and non-stationary periods respectively. UK electricity spot prices are found to be locally non-stationary processes (see Figure 1), which means that there are periods when prices are stable around a level and others when the time series describe a trend that is associated with the dominant fossil fuel being used. During these non-stationary periods, UK electricity spot prices are shown to have common long run dynamics with fossil fuels. During stationary periods, shocks can take a while to dilute, as it is observed that the price series shows long-memory behaviour. In such periods, wind penetration levels are significantly associated with spot price dynamics. In all, the results illustrate how different inputs influence wholesale prices and how a changing energy mix may affect the long run dynamics in the UK electricity market.

Suggested Citation

  • Melanie Houllier & Lilian M. De Menezes & Michael Tamvakis, 2014. "Time Varying Long Run Dynamics And Convergence In The Uk Energy Market," EcoMod2014 6970, EcoMod.
    • Handle: RePEc:ekd:006356:6970
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    1. Okimoto, Tatsuyoshi & Shimotsu, Katsumi, 2010. "Decline in the persistence of real exchange rates, but not sufficient for purchasing power parity," Journal of the Japanese and International Economies, Elsevier, vol. 24(3), pages 395-411, September.
    2. Haldrup, Niels & Nielsen, Morten Orregaard, 2006. "A regime switching long memory model for electricity prices," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 349-376.
    3. de Jong, C.M. & Huisman, R., 2002. "Option Formulas for Mean-Reverting Power Prices with Spikes," ERIM Report Series Research in Management ERS-2002-96-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    4. Perron, Pierre & Qu, Zhongjun, 2010. "Long-Memory and Level Shifts in the Volatility of Stock Market Return Indices," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(2), pages 275-290.
    5. Roques, Fabien A. & Newbery, David M. & Nuttall, William J., 2008. "Fuel mix diversification incentives in liberalized electricity markets: A Mean-Variance Portfolio theory approach," Energy Economics, Elsevier, vol. 30(4), pages 1831-1849, July.
    6. Mjelde, James W. & Bessler, David A., 2009. "Market integration among electricity markets and their major fuel source markets," Energy Economics, Elsevier, vol. 31(3), pages 482-491, May.
    7. Davide Ciferri & Maria Chiara D’Errico & Paolo Polinori, 2020. "Integration and convergence in European electricity markets," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 37(2), pages 463-492, July.
    8. Aatola, Piia & Ollikainen, Markku & Toppinen, Anne, 2013. "Impact of the carbon price on the integrating European electricity market," Energy Policy, Elsevier, vol. 61(C), pages 1236-1251.
    9. Trueck, Stefan & Weron, Rafal & Wolff, Rodney, 2007. "Outlier Treatment and Robust Approaches for Modeling Electricity Spot Prices," MPRA Paper 4711, University Library of Munich, Germany.
    10. Perron, P, 1993. "Erratum [The Great Crash, the Oil Price Shock and the Unit Root Hypothesis]," Econometrica, Econometric Society, vol. 61(1), pages 248-249, January.
    11. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-1072, June.
    12. Jos Sijm & Karsten Neuhoff & Yihsu Chen, 2006. "CO 2 cost pass-through and windfall profits in the power sector," Climate Policy, Taylor & Francis Journals, vol. 6(1), pages 49-72, January.
    13. 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.
    14. Perron, Pierre, 1989. "The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis," Econometrica, Econometric Society, vol. 57(6), pages 1361-1401, November.
    15. Haldrup Niels & Nielsen Morten Ø., 2006. "Directional Congestion and Regime Switching in a Long Memory Model for Electricity Prices," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 10(3), pages 1-24, September.
    16. 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.
    17. Guy Nason, 2013. "A test for second-order stationarity and approximate confidence intervals for localized autocovariances for locally stationary time series," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 75(5), pages 879-904, November.
    18. 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.
    19. T Robinson, 2008. "The Evolution of Electricity Prices in The EU since the Single European Act," Economic Issues Journal Articles, Economic Issues, vol. 13(2), pages 59-70, September.
    20. Muñoz, M. Pilar & Dickey, David A., 2009. "Are electricity prices affected by the US dollar to Euro exchange rate? The Spanish case," Energy Economics, Elsevier, vol. 31(6), pages 857-866, November.
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