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The impact of the European Union emission trading scheme on the electricity-generation sector

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  • Kirat, Djamel
  • Ahamada, Ibrahim

Abstract

In order to comply with their commitments under the Kyoto Protocol, France and Germany participate in the European Union Emission Trading Scheme (EU ETS) which predominantly concerns the electricity-generation sectors. In this paper we ask whether the EU ETS provides the appropriate economic incentives to produce an efficient system in line with the Kyoto commitments. If so, electricity producers in the countries concerned should include the price of carbon in their cost functions. After identifying different sub-periods of the EU ETS during its pilot phase (2005-2007), we model the prices of various electricity contracts in France and Germany and look at the volatility of electricity prices around their fundamentals while evaluating the correlation between electricity prices in the two countries. We find that electricity producers in both countries were constrained to include the carbon price in their cost functions during the first two years of the EU ETS. Over this period, German electricity producers were more constrained than their French counterparts, and the inclusion of the carbon price in the electricity-generation cost function was much more stable in Germany than in France. We also find evidence of fuel switching in electricity generation in Germany after the collapse of the carbon market. Furthermore, the European market for emission allowances has greatly contributed to the partial alignment of the wholesale price of electricity in France to that in Germany.

Suggested Citation

  • Kirat, Djamel & Ahamada, Ibrahim, 2011. "The impact of the European Union emission trading scheme on the electricity-generation sector," Energy Economics, Elsevier, vol. 33(5), pages 995-1003, September.
  • Handle: RePEc:eee:eneeco:v:33:y:2011:i:5:p:995-1003
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    1. Robert F. Engle & Kevin Sheppard, 2001. "Theoretical and Empirical properties of Dynamic Conditional Correlation Multivariate GARCH," NBER Working Papers 8554, National Bureau of Economic Research, Inc.
    2. Clemente, Jesus & Montanes, Antonio & Reyes, Marcelo, 1998. "Testing for a unit root in variables with a double change in the mean," Economics Letters, Elsevier, vol. 59(2), pages 175-182, May.
    3. Bunn, Derek W. & Fezzi, Carlo, 2007. "Interaction of European Carbon Trading and Energy Prices," Climate Change Modelling and Policy Working Papers 9092, Fondazione Eni Enrico Mattei (FEEM).
    4. Derek W. Bunn & Carlo Fezzi, 2007. "Interaction of European Carbon Trading and Energy Prices," Working Papers 2007.63, Fondazione Eni Enrico Mattei.
    5. Tomoaki Nakatani & Timo Terasvirta, 2009. "Testing for volatility interactions in the Constant Conditional Correlation GARCH model," Econometrics Journal, Royal Economic Society, vol. 12(1), pages 147-163, March.
    6. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    7. repec:dau:papers:123456789/4222 is not listed on IDEAS
    8. Luc Bauwens & Sébastien Laurent & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109, January.
    9. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
    10. Alberola, Emilie & Chevallier, Julien & Cheze, Benoi^t, 2008. "Price drivers and structural breaks in European carbon prices 2005-2007," Energy Policy, Elsevier, vol. 36(2), pages 787-797, February.
    11. Maria Mansanet-Bataller & Angel Pardo & Enric Valor, 2007. "CO2 Prices, Energy and Weather," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 73-92.
    12. Ahamada, Ibrahim & Flachaire, Emmanuel, 2010. "Non-Parametric Econometrics," OUP Catalogue, Oxford University Press, number 9780199578009, Decembrie.
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    More about this item

    Keywords

    Carbon emission trading Multivariate GARCH models Structural breaks Non-parametric approach Energy prices;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • Q49 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Other
    • Q58 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Government Policy

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