This dissertation is composed of four essays on the behavior of wholesale electricity prices and their derivatives. The first essay provides an empirical model that takes into account the spatial features of a transmission network on the electricity market. The spatial structure of the transmission grid plays a key role in determining electricity prices, but it has not been incorporated into previous empirical models. The econometric model in this essay incorporates a simple representation of the transmission system into a spatial panel data model of electricity prices, and also accounts for the effect of dynamic transmission system constraints on electricity market integration. Empirical results using PJM data confirm the existence of spatial patterns in electricity prices and show that spatial correlation diminishes as transmission lines become more congested. The second essay develops and empirically tests a model of the influence of natural gas storage inventories on the electricity forward premium. I link a model of the effect of gas storage constraints on the higher moments of the distribution of electricity prices to a model of the effect of those moments on the forward premium. Empirical results using PJM data support the model's predictions that gas storage inventories sharply reduce the electricity forward premium when demand for electricity is high and space-heating demand for gas is low. The third essay examines the efficiency of PJM electricity markets. A market is efficient if prices reflect all relevant information, so that prices follow a random walk. The hypothesis of random walk is examined using empirical tests, including the Portmanteau, Augmented Dickey-Fuller, KPSS, and multiple variance ratio tests. The results are mixed though evidence of some level of market efficiency is found. The last essay investigates the possibility that previous researchers have drawn spurious conclusions based on classical unit root tests incorrectly applied to wholesale electricity prices. It is well known that electricity prices exhibit both cyclicity and high volatility which varies through time. Results indicate that heterogeneity in unconditional variance---which is not detected by classical unit root tests---may contribute to the appearance of non-stationarity.
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