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Space-time modeling of electricity spot prices

Using data for the Nord Pool power grid, we derive a space-time Durbin model for electricity spot prices with both temporal and spatial lags. Joint modeling of temporal and spatial adjustment effects is necessarily important when prices and loads are determined in a network grid. By using different spatial weight matrices, statistical tests show significant spatial dependence in the spot price dynamics across areas. In fact, estimation of the model shows that the spatial dependence is as important as the temporal dependence in describing the spot price dynamics. We decompose price impacts into direct and indirect effects and demonstrate how price effects transmit to neighboring markets and decline with distance. A forecasting comparison with a non-spatial model shows that the space-time model improves forecasting performance for 7 and 30 days ahead forecasts. A model with time-varying parameters is estimated for an expanded sample period and it is found that the spatial correlation within the power grid has increased over time. We interpret this to indicate an increasing degree of market integration within the sample period.

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Energy Specializations: Electricity – Markets and Prices ; Energy Modeling – Forecasting and Market Analysis

JEL Codes: C51: Model Construction and Estimation, Q42: Alternative Energy Sources, C58: Financial Econometrics, Q41: Energy: Demand and Supply; Prices, R15: General Regional Economics: Econometric and Input-Output Models; Other Models, R12: Size and Spatial Distributions of Regional Economic Activity, Q54: Climate; Natural Disasters and Their Management; Global Warming, D44: Auctions

Keywords: Electricity spot prices, Nord Pool, recursive estimation; space-time dependence forecast comparison

DOI: https://doi.org/10.5547/01956574.38.5.gaba

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Published in Volume 38, Number 5 of the bi-monthly journal of the IAEE's Energy Economics Education Foundation.


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