Dynamic Granger-causal networks of electricity spot prices: A novel approach to market integration

This study uses network theory to analyze the interactions of a representative sample of 13 European (EU) electricity spot prices during the period 2007-2012. We construct 7651 dynamic multivariate networks, where the nodes correspond to different EU countries and the links weight the Granger-causality between the variations of the respective electricity prices. Global connectivity is then characterized by the system's density, or the total quantity of causal interactivity sustained by the network system, which informs about the occurrence of abnormal changes in connectivity. We report a considerably large peak lasting from October 2011 to April 2012, where the graph's density over-basal jump reached a magnitude of 2.4 times, suggesting an improved degree of connectivity of electricity markets during this period. By applying the Markov regime-switching model on the network density we find that this change coincides with the implementation of the European Commission's Third Energy Package. At the local level, the in-strength values quantifying the dependence of the electricity price variation of an EU country on other countries, validate the reliability of our technique by verifying historical events such as the occurrence of interconnectors commissioning and market coupling. On the path to full market integration, market networks should be periodically monitored. Our model, which is able to create a time-varying network describing the evolving influences between the European electricity prices, is able to detect important changes in market integration and can be considered a suitable and promising approach for this task.