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Evidence of a nonlinear effect of the EU ETS on the electricity-generation sector

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  • Ibrahim Ahamada

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)

  • Djamel Kirat

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)

Abstract

This article considers the evidence for threshold effects in the relationship between electricity and emission permit prices in France and Germany during the second phase of the EU ETS. Specifically, we compare linear and nonlinear threshold models of electricity prices using Hansen's (2000) approach of sample splitting and threshold estimation. We find evidence of nonlinear threshold effects in both countries. The estimated carbon price thresholds are 14.94 € and 12.57 € in France and Germany, respectively. In Germany, the carbon price does not affect the electricity price below this threshold. In France, the price of emission allowances affects the cost of electricity generation only below the carbon-price threshold, thus revealing speculative behavior by French electricity producers on the carbon-allowance market. This is not the case for German electricity producers.

Suggested Citation

  • Ibrahim Ahamada & Djamel Kirat, 2012. "Evidence of a nonlinear effect of the EU ETS on the electricity-generation sector," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00717629, HAL.
    • Handle: RePEc:hal:cesptp:halshs-00717629
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00717629
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    References listed on IDEAS

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    1. Bruce E. Hansen, 2000. "Sample Splitting and Threshold Estimation," Econometrica, Econometric Society, vol. 68(3), pages 575-604, May.
    2. Ibrahim Ahamada & Djamel Kirat, 2012. "The impact of phase II of the EU ETS on the electricity-generation sector," Documents de travail du Centre d'Economie de la Sorbonne 12007, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    3. Hansen, Bruce E, 1996. "Inference When a Nuisance Parameter Is Not Identified under the Null Hypothesis," Econometrica, Econometric Society, vol. 64(2), pages 413-430, March.
    4. 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.
    5. Perrels, Adriaan & Honkatukia, Juha & Mälkönen, Ville, 2006. "Impacts of the European Emission Trade System on Finnish Wholesale Electricity Prices," Discussion Papers 405, VATT Institute for Economic Research.
    6. Ibrahim Ahamada & Djamel Kirat, 2012. "The impact of phase II of the EU ETS on the electricity-generation sector," Post-Print halshs-00673918, HAL.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Carbon emission trading; energy prices; nonlinear threshold model; prix des énergies; Marché des permis d'émission; modèles à seuil;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: 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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