Factor models are widely used in analyzing time series data, but traditional methods have limitations in forecasting accuracy. This study introduces a new approach that improves estimation by using one-sided estimators for the parameters and common shocks in the Generalized Dynamic Factor Model. The researchers found that these new estimators are consistent and provide better performance compared to traditional methods when applied to US macroeconomic data.