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 …

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

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 …

, forecasting of the full density for long horizons is feasible, which we pursue. We document variability in conditional variances … over time, which stresses the importance of careful modeling and forecasting of volatility. We show that improved model fit …

versa occurs over time. Such a change has important implications for forecasting, as negligence may lead to inaccurate model …. Seven different forecasting strategies based on a biasedcorrected estimator are compared by means of a large-scale Monte … predictive ability and its balanced performance among different settings strongly advocate the use of forecasting strategies …