Journal article | Zeitschriftenartikel
Forecasting using a large number of predictors: is Bayesian regression a valid alternative to principal components?
This paper considers Bayesian regression with normal and double-exponential 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 conditions for consistency of the forecast based on Bayesian regression as the cross-section and the sample size become large. This analysis serves as a guide to establish a criterion for setting the amount of shrinkage in a large cross-section.
- Extent
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Seite(n): 318-328
- Language
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Englisch
- Notes
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Status: Postprint; begutachtet (peer reviewed)
- Bibliographic citation
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Journal of Econometrics, 146(2)
- Subject
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Wirtschaft
Sozialwissenschaften, Soziologie
Erhebungstechniken und Analysetechniken der Sozialwissenschaften
Volkswirtschaftslehre
- Event
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Geistige Schöpfung
- (who)
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Mol, Christine de
Giannone, Domenico
Reichlin, Lucrezia
- Event
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Veröffentlichung
- (where)
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Niederlande
- (when)
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2008
- DOI
- URN
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urn:nbn:de:0168-ssoar-198289
- Rights
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GESIS - Leibniz-Institut für Sozialwissenschaften. Bibliothek Köln
- Last update
-
21.06.2024, 4:27 PM CEST
Data provider
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GESIS - Leibniz-Institut für Sozialwissenschaften. Bibliothek Köln. If you have any questions about the object, please contact the data provider.
Object type
- Zeitschriftenartikel
Associated
- Mol, Christine de
- Giannone, Domenico
- Reichlin, Lucrezia
Time of origin
- 2008
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