The online Supplement presents the proof the auxiliary Lemmas 1-6, the entire set of tables with results from the Monte Carlo and the empirical studies, and further discussion on selected topics.Full paper is available at: 'https://ssrn.com/abstract=2707176' https://ssrn.com/abstract=2707176

We address the issue of modelling and forecasting macroeconomic variables using rich datasets by adopting the class of Vector Autoregressive Moving Average (VARMA) models. We overcome the estimation issue that arises with this class of models by implementing an iterative ordinary least squares...

Vector autoregressive moving-average (VARMA) processes are suitable models for producing linear forecasts of sets of time series variables. They provide parsimonious representations of linear data generation processes. The setup for these processes in the presence of stationary and cointegrated...