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Forecasting using a large number of predictors: is Bayesian regression a valid alternative to principal components?
[journal article]
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... view more
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.... view less
Classification
Methods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methods
Political Economy
Free Keywords
Bayesian shrinkage; Bayesian VAR; Ridge regression; Lasso regression; Principal components; Large cross-sections
Document language
English
Publication Year
2008
Page/Pages
p. 318-328
Journal
Journal of Econometrics, 146 (2008) 2
DOI
https://doi.org/10.1016/j.jeconom.2008.08.011
Status
Postprint; peer reviewed
Licence
PEER Licence Agreement (applicable only to documents from PEER project)