Over the past decade or so electricity markets have been strongly liberalized throughout the world. In particular, the Nordic power market consisting of Norway, Sweden, Finland, and Denmark has developed remarkably towards liberalization and the establishment of competitive market conditions, and today this market serves as a model for the restructuring of other power markets. The Nordic power market is characterized by a grid of physical exchanges of power across geographical regions where the actual exchange is constrained by the flow capacity. Naturally, this has implications for the way prices are formed. When there are no bilateral capacity restrictions, there is a free flow of power and prices will be identical.
On the other hand, when there is congestion prices tend to depart to meet the supply and demand conditions subject to restricted access to power from other regions. In order to model electricity prices it is thus natural to consider regime dependent price processes reflecting the presence or absence of flow congestion. This particular feature of the market has been addressed in recent work by Haldrup & Nielsen (2006a, b). Another important property of electricity prices modeled in these works is the presence of long memory. Statistical tests strongly reject the price series being I(0) and I(1), whereas I(d) processes with d being fractional (see Granger & Joyeux (1980) and Hosking (1981)) better characterize the data.
The combination of fractional integration and regime switching gives rise to some challenges. Granger & Ding (1996), Diebold & Inoue (2001), and Granger & Hyung (2004), among others, argue that under certain conditions time series variables can spuriously have long memory when measured in terms of their fractional order of integration, when in fact the series exhibit non%linear features such as regime switching. In the model framework of Haldrup & Nielsen (2006a, b) separate long memory price dynamics is allowed in adjacent power regions depending upon whether the power exchange is subject to congestion or non%congestion.
The model has some similarities to the Markov switching model defined by Hamilton (1989). However, because the defining property of e.g. a non%congestion state is that prices are identical, the state variable is observable as opposed to being a latent variable. Thus our model is not of the traditional Hamilton (1989) Markov switching type, but we still refer to it as a regime switching model since it does include switching between two separate regimes.
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A vector autoregressive model for electricity prices subject to long memory and regime switching
