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Discussion Paper Series 1: Economic Studies, Deutsche Bundesbank >
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http://hdl.handle.net/10419/19661
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| Title: | | Forecasting using a large number of predictors: is Bayesian regression a valid alternative to principal components?  |
| Authors: | | De Mol, Christine Giannone, Domenico Reichlin, Lucrezia |
| Issue Date: | | 2006 |
| Series/Report no.: | | Discussion paper Series 1 / Volkswirtschaftliches Forschungszentrum der Deutschen Bundesbank 2006,32 |
| Abstract: | | This paper considers Bayesian regression with normal and doubleexponential priors as forecasting methods based on large panels of time series. We show that, empirically, these forecasts are highly correlated with principal component forecasts and that they perform equally well for a wide range of prior choices. Moreover, we study the asymptotic properties of the Bayesian regression under Gaussian prior under the assumption that data are quasi collinear to establish a criterion for setting parameters in a large cross-section. |
| Subjects: | | Bayesian VAR ridge regression Lasso regression principal components large cross-sections |
| JEL: | | C33 C13 C53 C11 |
| Document Type: | | Working Paper |
| Appears in Collections: | | Discussion Paper Series 1: Economic Studies, Deutsche Bundesbank
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