Bayesian VARs with large panels

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Forecasting exchange rates with a large Bayesian VAR (2009, methodology): “Besides this, as the number of variables in the V AR increases, smaller values of the tightness parameter θ are needed in order to avoid overfitting (see Banbura et al (2007)).”
Forecasting using a large number of predictors: Is Bayesian regression a valid alternative to principal components? (2008, unknown): “hence, from Corollary 2, when the prior is such that ‖Φ0‖−1 = cnT 1 2, we 17This is a generalization to the dynamic case of the assumptions defining an approximate factor structure given by Chamberlain and Rothschild (1983). Bai (2003), Bai and Ng (2002) and Stock and Watson (2002a) give similar con”
The Dynamic Effects of Monetary Policy: A Structural Factor Model Approach (2010, background): “However, in both cases the reaction of prices is nearly zero or still positive during the first year.(7) Moreover, in both cases the percentage of the forecast error variance of prices explained by the policy shock is very low (less than 5%) even in the long run (see CEE and BBE).”