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Co2 Abatement and Fuel Mix in German Electric Power Generation — Is the “Ecological Electricity Tax†Ecologically Effective?

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  • Harald Tauchmann

    (Rheinisch Westfälisches Institut für Wirtschaftsforschung, Essen)

Abstract

This paper analyzes the effect of a potential carbon tax on inter-fuel substitution in the electric power sector in Germany. By analyzing firm level panel data (1980–1998), we show that the fuel mix as used by power plants is price inelastic. That means that differential fuel taxes, e.g. a carbon tax, will not induce inter-fuel substitution towards less carbon intensive fuels. This in turn means that the recent introduction in Germany of an electricity tax cannot be judged less effective than the hypothetical introduction of a carbon tax with respect to power related CO 2 emissions. It is likely, however, that in the course of the deregulation of the German power sector a carbon tax will become significantly more effective than an electricity tax.

Suggested Citation

  • Harald Tauchmann, 2005. "Co2 Abatement and Fuel Mix in German Electric Power Generation — Is the “Ecological Electricity Tax†Ecologically Effective?," Energy & Environment, , vol. 16(2), pages 255-271, March.
    • Handle: RePEc:sae:engenv:v:16:y:2005:i:2:p:255-271
    DOI: 10.1260/0958305053749561
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    References listed on IDEAS

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    1. Ahn, Seung C. & Schmidt, Peter, 1995. "Efficient estimation of models for dynamic panel data," Journal of Econometrics, Elsevier, vol. 68(1), pages 5-27, July.
    2. Atkinson, Scott E & Halvorsen, Robert, 1976. "Interfuel Substitution in Steam Electric Power Generation," Journal of Political Economy, University of Chicago Press, vol. 84(5), pages 959-978, October.
    3. Pindyck, Robert S, 1979. "Interfuel Substitution and the Industrial Demand for Energy: An International Comparison," The Review of Economics and Statistics, MIT Press, vol. 61(2), pages 169-179, May.
    4. John F. Stewart, 1979. "Plant Size, Plant Factor, and the Shape of the Average Cost Function in Electric Power Generation: A Nonhomogeneous Capital Approach," Bell Journal of Economics, The RAND Corporation, vol. 10(2), pages 549-565, Autumn.
    5. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
    6. Anderson, T. W. & Hsiao, Cheng, 1982. "Formulation and estimation of dynamic models using panel data," Journal of Econometrics, Elsevier, vol. 18(1), pages 47-82, January.
    7. Seifi, Ahmad & McDonald, John F., 1986. "Fuel choice in new fossil fuel electric power plants," Resources and Energy, Elsevier, vol. 8(1), pages 21-34, March.
    8. Soderholm, Patrik, 2001. "Fossil fuel flexibility in west European power generation and the impact of system load factors," Energy Economics, Elsevier, vol. 23(1), pages 77-97, January.
    9. Timothy J. Considine, 2000. "Cost Structures for Fossil Fuel-Fired Electric Power Generation," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 83-104.
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    Cited by:

    1. Mikael Linden, Matti Makela, and Jussi Uusivuori, 2013. "Fuel Input Substitution under Tradable Carbon Permits System: Evidence from Finnish Energy Plants 2005-2008," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    2. Tauchmann, H., 2006. "Firing the furnace? An econometric analysis of utilities' fuel choice," Energy Policy, Elsevier, vol. 34(18), pages 3898-3909, December.

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