We build a small-scale factor model for Latvia’s GDP to study the exact dynamic versus static factor model performance along a business cycle, with an emphasis placing on nowcasting performance during a pronounced switch of business cycle phases due to the latest recession. We compare the factor models' nowcasting performance to a random walk, autoregressive and the best-performing nowcasting models at our hands, which are vector autoregressive (VAR) models. It is shown that a small-scale static factor-augmented VAR model tends to improve upon the nowcasting performance of the VAR models during the switch business cycle phases while exact dynamic factor models tend to fail to detect the timing and depth of the recession regardless of ARMA specifications. As regards the period of smooth economic growth, static and dynamic factor models appear to show similar performance with potentially slight superiority of dynamic factor models if the factor-forming set of variables and factor dynamics are carefully selected.