Interrelationship models in energy markets

This thesis aims to make two types of academic contributions. It includes both methodological insights about the application of quantitative methods to the study of network industries and theoretical results concerning the economics of energy markets. The theoretical literature on interconnectors has established their potential to mitigate local market power, but the relationship between capacity utilisation and locational market splitting has not been studied empirically. Thus, in the first essay of the thesis I apply Vector Autorregressive (VAR) modelling techniques to data from the Bacton (UK)-Zeebrugge (Belgium) natural gas pipeline. The analysis identifies a threshold of capacity utilisation after which the UK and Continental markets split. The relationship between local price differences and capacity use is increasing and convex. A difference between the UK and Continental markets is that while there are extensive crossholdings in the Continent, UK firms remain in general independent from each other. This raises the issue of how crossholdings affect the firms' ability to coordinate in higher prices. Hence, the second essay presents a set of simulations in which computational agents try to optimise their profit using parameters adapted from the Roth and Erev (1995) reinforcement algorithm. The auction setting is a double-sided stylisation of the European energy markets. The results indicate that market transparency leads to higher prices, that the functional form of the crossholdings to prices relationship is not linear but concave and that more downstream competition reduces the influence of information on wholesale prices. The model in the third essay is complementary to the crossholdings research and incorporates key aspects of the interlinked operations of gas and electricity wholesale markets in the short-run. These sequential multiple-unit auctions present many non-Pareto ranked equilibria and we propose another Roth and Erev (1995) simulation as an alternative. The simulations unveil a new market power mechanism that explains why vertical market power can be observed in the energy industry