We propose a discussion index model (Stock and Watson, 2002) to fore- cast electricity demand for one hour to one week ahead. The model is particularly useful as it captures complicated seasonal patterns in the data. The forecast performance of the proposed method is illustrated with a simulated real-time experiment for data from the Pennsylvania- New Jersey-Maryland Interchange.

Additional Metadata
Keywords diffusion index forecast, electricity load, seasonality
JEL Hypothesis Testing (jel C12), Time-Series Models; Dynamic Quantile Regressions (jel C22), Time-Series Models; Dynamic Quantile Regressions (jel C32)
Persistent URL hdl.handle.net/1765/8001
Series Econometric Institute Research Papers
Journal Report / Econometric Institute, Erasmus University Rotterdam
Citation
Rotger, G.P, & Franses, Ph.H.B.F. (2006). Forecasting high-frequency electricity demand with a diffusion index model. (No. EI 2006-38). Report / Econometric Institute, Erasmus University Rotterdam. Retrieved from http://hdl.handle.net/1765/8001