| Summary: | Over the last decade, many electricity markets have introduced purely financial trading alongside transactions between operators who own physical generation capacity and entities, such as utilities, that serve physical demand. As it has been in other markets, the effect of these financial trades is the subject of an ongoing debate; while they are expected to increase liquidity and informational efficiency, they have also been blamed for higher prices and led to allegations of price manipulation. This paper studies the role of financial trading by examining a natural experiment in the Midwest electricity market. A 2011 regulatory change exogenously attracted more financial players to this market, and a rich dataset on individual behavior allows me to study both physical and financial participants' reaction to it. First, I use a reduced form analysis to show that the regulatory change lead to more financial trading, and less generators' market power. I then use a structural approach to examine the causal relationship between these two observations, which requires the computation of the residual demand faced by each firm. A major challenge here is that electricity markets are segmented by transmission lines with limited capacity, which creates local markets in which only a subset of the firms competes. I deal with this issue using techniques from machine learning, presenting a new method to study the competitive structure of electricity markets. My findings indicate that financial trading decreases generators market power, but does not fully eliminate it. As a consequence, consumers are better off but productive efficiency might go down.
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