Forecasting by factors, by variables, or both?

Working paper

We consider forecasting with factors, variables and both, modeling in-sample using Autometrics so all principal components and variables can be included jointly, while tackling multiple breaks by impulse-indicator saturation. A forecast-error taxonomy for factor models highlights the impacts of location shifts on forecast-error biases. Forecasting US GDP over 1-, 4- and 8-step horizons using the dataset from Stock and Watson (2009) updated to 2011:2 shows factor models are more useful for n...

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Authors: Castle, J; Hendry, D

• Publication status: Published
• Publisher: University of Oxford Publisher's website
• Series: Department of Economics Discussion Paper Series
• Publication date: 2012-04-01
• Paper number: 600
• Keywords: model selection; forecasting; autometrics; impulse-indicator saturation; factor models