A number of recent studies in the economics literature have focused on the usefulness of factor models in the context of prediction using "big data". In this paper, our over-arching question is whether such "big data" are useful for modelling low frequency macroeconomic variables such as...

This paper puts forward kernel ridge regression as an approach for forecasting with many predictors that are related nonlinearly to the target variable. In kernel ridge regression, the observed predictor variables are mapped nonlinearly into a high-dimensional space, where estimation of the...

The paper considers the task of selecting a flexible nonlinear model which can be used as a baseline model. The baseline model may be used as a testing ground for more structural models which are congruent with economic theory. From the limited empirical evidence obtained here it is tentatively...