variable selection and estimation in one step. We evaluate the forecasting accuracy of these estimators for a large set of …

The use of large-dimensional factor models in forecasting has received much attention in the literature with the … model which is better suited for forecasting compared to the traditional principal components (PC) approach.We provide an … asymptotic analysis of the estimator and illustrate its merits empirically in a forecasting experiment based on US macroeconomic …

-sample forecasting regressions. The predictive power of the model stays high at longer horizons. The estimated factors are strongly …

weighted by the measurement error variance, thus avoiding the calibration of a design parameter. The standardization leads to a …

Macroeconomic forecasting using factor models estimated by principal components has become a popular research topic … simply screen datasets prior to estimation and remove anomalous observations.We investigate whether forecasting performance … Carlo simulation studies. Finally, we apply our proposed estimator in a simulated real-time forecasting exercise to test its …

We address the issue of modelling and forecasting macroeconomic variables using medium and large datasets, by adopting … that VARMA models outperform the AR(1), VAR(p) and factor models, considering different model dimensions. …