  This article discusses the use of dynamic factor models in macroeconomic
forecasting, with a focus on the Factor-Augmented Error Correction Model
(FECM). The FECM combines the advantages of cointegration and dynamic factor
models, providing a flexible and reliable approach to macroeconomic
forecasting, especially for non-stationary variables. We evaluate the
forecasting performance of the FECM model on a large dataset of 117 Moroccan
economic series with quarterly frequency. Our study shows that FECM outperforms
traditional econometric models in terms of forecasting accuracy and robustness.
The inclusion of long-term information and common factors in FECM enhances its
ability to capture economic dynamics and leads to better forecasting
performance than other competing models. Our results suggest that FECM can be a
valuable tool for macroeconomic forecasting in Morocco and other similar
economies.
