INDEX TO VOLUME 8 (1 990) |
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Authors: | James H. Stock Mark W. Watson |
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Affiliation: | 1. Department of Economics, Littauer Center , Harvard University , Cambridge , MA;2. Woodrow Wilson School and Department of Economics , Bendheim Hall, Princeton University , Princeton , NJ |
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Abstract: | This article provides a simple shrinkage representation that describes the operational characteristics of various forecasting methods designed for a large number of orthogonal predictors (such as principal components). These methods include pretest methods, Bayesian model averaging, empirical Bayes, and bagging. We compare empirically forecasts from these methods with dynamic factor model (DFM) forecasts using a U.S. macroeconomic dataset with 143 quarterly variables spanning 1960–2008. For most series, including measures of real economic activity, the shrinkage forecasts are inferior to the DFM forecasts. This article has online supplementary material. |
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Keywords: | Dynamic factor models Empirical Bayes High-dimensional model |
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