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Space-time modeling of electricity spot prices

Author

Listed:
  • Girum D. Abate

    () (Aarhus University and CREATES)

  • Niels Haldrup

    () (Aarhus University and CREATES)

Abstract

In this paper we derive a space-time model for electricity spot prices. A general spatial Durbin model that incorporates the temporal as well as spatial lags of spot prices is presented. Joint modeling of space-time effects is necessarily important when prices and loads are determined in a network of power exchange areas. We use data from the Nord Pool electricity power exchange area bidding markets. Different spatial weight matrices are considered to capture the structure of the spatial dependence process across different bidding markets and statistical tests show significant spatial dependence in the spot price dynamics. Estimation of the spatial Durbin model show that the spatial lag variable is as important as the temporal lag variable in describing the spot price dynamics. We use the partial derivatives impact approach to decompose the price impacts into direct and indirect effects and we show that price effects transmit to neighboring markets and decline with distance. In order to examine the evolution of the spatial correlation over time, a time varying parameters spot price spatial Durbin model is estimated using recursive estimation. It is found that the spatial correlation within the Nord Pool grid has been increasing over time which we interpret as evidence for an increasing degree of market integration.

Suggested Citation

  • Girum D. Abate & Niels Haldrup, 2015. "Space-time modeling of electricity spot prices," CREATES Research Papers 2015-22, Department of Economics and Business Economics, Aarhus University.
  • Handle: RePEc:aah:create:2015-22
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    References listed on IDEAS

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    More about this item

    Keywords

    Autoregressive; Spatial-Time series; Spatial dependence;

    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
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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