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A Vector Autoregressive Model for Electricity Prices Subject to Long Memory and Regime Switching

Author

Listed:
  • Niels Haldrup
  • Frank S. Nielsen
  • Morten Ørregaard Nielsen

    (School of Economics and Management, University of Aarhus, Denmark and CREATES)

Abstract
A regime dependent VAR model is suggested that allows long memory (fractional integration) in each of the regime states as well as the possibility of fractional cointegra- tion. The model is relevant in describing the price dynamics of electricity prices where the transmission of power is subject to occasional congestion periods. For a system of bilat- eral prices non-congestion means that electricity prices are identical whereas congestion makes prices depart. Hence, the joint price dynamics implies switching between essen- tially a univariate price process under non-congestion and a bivariate price process under congestion. At the same time it is an empirical regularity that electricity prices tend to show a high degree of fractional integration, and thus that prices may be fractionally cointegrated. An empirical analysis using Nord Pool data shows that even though the prices strongly co-move under non-congestion, the prices are not, in general, fractional cointegrated in the congestion state.

Suggested Citation

  • Niels Haldrup & Frank S. Nielsen & Morten Ørregaard Nielsen, 2007. "A Vector Autoregressive Model for Electricity Prices Subject to Long Memory and Regime Switching," CREATES Research Papers 2007-29, Department of Economics and Business Economics, Aarhus University.
  • Handle: RePEc:aah:create:2007-29
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    File URL: https://repec.econ.au.dk/repec/creates/rp/07/rp07_29.pdf
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Cointegration; electricity prices; fractional integration; long memory; Markov switching;
    All these keywords.

    JEL classification:

    • 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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