  Wholesale electricity markets are increasingly integrated via high voltage
interconnectors, and inter-regional trade in electricity is growing. To model
this, we consider a spatial equilibrium model of price formation, where
constraints on inter-regional flows result in three distinct equilibria in
prices. We use this to motivate an econometric model for the distribution of
observed electricity spot prices that captures many of their unique empirical
characteristics. The econometric model features supply and inter-regional trade
cost functions, which are estimated using Bayesian monotonic regression
smoothing methodology. A copula multivariate time series model is employed to
capture additional dependence -- both cross-sectional and serial-- in regional
prices. The marginal distributions are nonparametric, with means given by the
regression means. The model has the advantage of preserving the heavy
right-hand tail in the predictive densities of price. We fit the model to
half-hourly spot price data in the five interconnected regions of the
Australian national electricity market. The fitted model is then used to
measure how both supply and price shocks in one region are transmitted to the
distribution of prices in all regions in subsequent periods. Finally, to
validate our econometric model, we show that prices forecast using the proposed
model compare favorably with those from some benchmark alternatives.
