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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...
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We evaluate automatically selecting the relevant variables in an econometric model from a large candidate set.  General-to-specific selection is outlined for a constant model in orthogonal variables, where only one decision is required to select, irrespective of the number of regressors (N T)...
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Our strategy for automatic selection in potentially non-linear processes is: test for non-linearity in the unrestricted linear formulation; if that test rejects, specify a general model using polynomials, to be simplified to a minimal congruent representation; finally select by encompassing...
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