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A stochastic fuel switching model for electricity prices

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  • Zachmann, Georg

Abstract

This paper develops and applies a novel electricity price model. We reproduce the merit order of a thermal-dominated electricity system by establishing a non-linear dependency of wholesale electricity prices on the prices of fuels (coal and natural gas) and of CO2 emission allowances. The coefficients are estimated using a Markov Switching Regression.

Suggested Citation

  • Zachmann, Georg, 2013. "A stochastic fuel switching model for electricity prices," Energy Economics, Elsevier, vol. 35(C), pages 5-13.
  • Handle: RePEc:eee:eneeco:v:35:y:2013:i:c:p:5-13
    DOI: 10.1016/j.eneco.2012.06.019
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    References listed on IDEAS

    as
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    Citations

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    Cited by:

    1. Afanasyev, Dmitriy O. & Fedorova, Elena A. & Popov, Viktor U., 2015. "Fine structure of the price–demand relationship in the electricity market: Multi-scale correlation analysis," Energy Economics, Elsevier, vol. 51(C), pages 215-226.
    2. Figueiredo, Nuno Carvalho & Silva, Patrícia Pereira da & Bunn, Derek, 2016. "Weather and market specificities in the regional transmission of renewable energy price effects," Energy, Elsevier, vol. 114(C), pages 188-200.
    3. Luigi Grossi & Fany Nan, 2017. "Forecasting electricity prices through robust nonlinear models," Working Papers 06/2017, University of Verona, Department of Economics.
    4. Gerster, Andreas, 2016. "Negative price spikes at power markets: The role of energy policy," Ruhr Economic Papers 636, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    5. Andreas Gerster, 2016. "Negative price spikes at power markets: the role of energy policy," Journal of Regulatory Economics, Springer, vol. 50(3), pages 271-289, December.
    6. repec:spr:annopr:v:255:y:2017:i:1:d:10.1007_s10479-015-1967-5 is not listed on IDEAS

    More about this item

    Keywords

    Electricity prices; Markov switching models;

    JEL classification:

    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • D43 - Microeconomics - - Market Structure, Pricing, and Design - - - Oligopoly and Other Forms of Market Imperfection

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