In a factor-augmented regression, the forecast of a variable depends on a few factors estimated from a large number of predictors. But how does one determine the appropriate number of factors relevant for such a regression? Existing work has focused on criteria that can consistently estimate the...

This paper revisits a number of data-rich prediction methods that are widely used in macroeconomic forecasting, such as factor models and Bayesian shrinkage regression, and compares these methods with a lesser known alternative: partial least squares regression. In this method, linear,...