On the applicability of dynamic factor models for forecasting real GDP growth in Armenia

In this paper, we are trying to find out whether large-scale factor-augmented models can be successfully used for forecasting real GDP growth rate in Armenia. We compare the forecasting performance of factor-augmented models such as FAAR, FAVAR and Bayesian FAVAR with their small-scale benchmark counterpart models like AR, VAR and Bayesian VAR. Based on the ex-post out-of-sample recursive and rolling forecast evaluations and using RMSFE’s, we conclude that large-scale factor-augmented models outperform small-scale benchmark models. However, the differences in forecasts among the models are not statistically significant when we apply statistical test.