Credible Granger-causality analysis appears to require post-sample inference, as it is well-known that in-sample fit can be a poor guide to actual forecasting effectiveness. However, post-sample model testing requires an often-consequential a priori partitioning of the data into an "in-sample"...

We extract principal components from a panel of 17 exchange rates and use the deviations from the components to forecast future exchange rate movements, following the idea in Engel, Mark, and West (2015). Instead of using the standard method, we apply a generalized principal components analysis...