We examine the impact of explanatory variables such as load, weather and capacity constraints on the occurrence and magnitude of price spikes in regional Australian electricity markets. We apply the so-called Heckman correction, a two-stage estimation procedure that allows us to investigate the impact of the considered variables on extreme price observations only, while correcting for a selection bias due to non-random sampling in the analysis. The framework is applied to four regional electricity markets in Australia and it is found that for these markets, load, relative air temperature and reserve margins are significant variables for the occurrence of price spikes, while electricity loads and relative air temperature are significant variables to impact on the magnitude of a price spike. The Heckman selection model is also found to outperform standard OLS regression models with respect to forecasting the magnitude of electricity price spikes.
|Title of host publication||Energy pricing models|
|Subtitle of host publication||recent advances, methods, and tools|
|Place of Publication||New York, NY|
|Number of pages||27|
|Publication status||Published - 2014|