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Forecasting with a large number of predictors: Is Bayesian regression a valid alternative to principal components?

Journal

Journal of Econometrics

Subject

Economics

Publishing details

Journal of Econometrics 2008 Vol 146:2 p 318-328

Authors / Editors

Reichlin L;De Mol C;Giannone D

Biographies

Lucrezia Reichlin

Publication Year

2008

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 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.

Keywords

Bayesian shrinkage; Bayesian VAR; Ridge regression; Lasso regression; Principal components; Large cross-sections

Available on ECCH

No


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