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α: calibrated so average coauthorship-adjusted count equals average raw count
Electricity prices in an interconnected market are influenced by the occurrence of transmission constraints. Until relatively recently, however, the important effects of transmission constraints on both the trajectory and volatility of electricity prices have not played a large role in empirical models of prices. This paper explores the contribution to price volatility in the Queensland electricity market made by transmission constraints. It is found that robust estimation techniques are necessary to guard against incorrect inference in time series models using electricity price data in which severe price spikes occur. The main empirical lesson is that transmission constraints contribute significantly both to the level and variability of price and consequently the performance of a price forecasting model is likely to be improved by incorporating information on transmission constraints. While the general tenor of this conclusion will come as no surprise, the extent and the importance of these effects found in this paper for forecasting price and for computing summary measures like Value-at-Risk serve as a timely reminder to practitioners.