Volltext herunterladen
(926.7 KB)
Zitationshinweis
Bitte beziehen Sie sich beim Zitieren dieses Dokumentes immer auf folgenden Persistent Identifier (PID):
https://nbn-resolving.org/urn:nbn:de:0168-ssoar-198289
Export für Ihre Literaturverwaltung
Forecasting using a large number of predictors: is Bayesian regression a valid alternative to principal components?
[Zeitschriftenartikel]
Abstract 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 p... mehr
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.... weniger
Klassifikation
Erhebungstechniken und Analysetechniken der Sozialwissenschaften
Volkswirtschaftslehre
Freie Schlagwörter
Bayesian shrinkage; Bayesian VAR; Ridge regression; Lasso regression; Principal components; Large cross-sections
Sprache Dokument
Englisch
Publikationsjahr
2008
Seitenangabe
S. 318-328
Zeitschriftentitel
Journal of Econometrics, 146 (2008) 2
DOI
https://doi.org/10.1016/j.jeconom.2008.08.011
Status
Postprint; begutachtet (peer reviewed)
Lizenz
PEER Licence Agreement (applicable only to documents from PEER project)