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A comparison of adaptive structural forecasting methods for electricity sales
Authors:Robert F Engle  Scott J Brown  Gary Stern
Abstract:This paper presents the results of a study to determine whether new forecasting technologies might be of use to electric utilities for sales forecasting up to 3 years into the future. The methods considered included ordinary least squares on dynamic structural models, autocorrelated error models, adaptive variance and adaptive parameter models. Overall, the more adaptive models performed best, but most of the methods proved vastly superior to simple least squares models which do not take dynamics into account.
Keywords:Forecasting  Time-varying parameters  Serial correlation  Electricity sales  Kalman Filter  Post sample forecast comparison  Model selection criteria
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