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A Regime Switching Long Memory Model for Electricity Prices

Author

Listed:
  • Niels Haldrup
  • Morten O. Nielsen

    (Department of Economics, University of Aarhus, Denmark)

Abstract
In this paper we develop a regime switching model which can generate long memory (fractional integration) in each of the regime states. This property is relevant in a number of cases. For instance, the deregulated market for electricity power in the Nordic countries is characterized by electricity spot prices with a high degree of long memory. It occurs that in some time periods bilateral prices are identical whereas in other periods the prices differ. The latter occurs when a capacity congestion exists across regions and multiple price areas will result. If the price series are fractionally integrated this means that in some regimes, an extreme form of fractional cointegration amongst prices will exist. We define a Markov switching fractional integration model from which the fractional orders of integration in separate states can be estimated using Maximum Likelihood techniques. The model is adapted to data for the Nordic electricity spot market, and we find that regime swithing and long memory are empirically relevant to co-exist. In particular, we find that the price behaviour for single markets can be very different depending upon the presence or absence of bottlenecks in electricity transmission. Using Monte Carlo forecasting we find that the regime switching model appears to be especially attractive in forecasting relative prices.

Suggested Citation

  • Niels Haldrup & Morten O. Nielsen, 2004. "A Regime Switching Long Memory Model for Electricity Prices," Economics Working Papers 2004-2, Department of Economics and Business Economics, Aarhus University.
    • Handle: RePEc:aah:aarhec:2004-2
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    References listed on IDEAS

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    More about this item

    Keywords

    Cointegration; electricity prices; forecasting; fractional integration and cointegration; ong memory; Markov switching;
    All these keywords.

    JEL classification:

    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • 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

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