Seasonality in dynamic regression models can be simplified by treating it as a slowly changing unobserved component. By separating seasonal factors from non-seasonal ones, we can better understand the relationship between consumption, income, and prices. Autoregressive models may not effectively capture slowly changing seasonality, leading to confusion between seasonal effects and dynamic responses. The approach presented in the paper can be applied to various cases and shows that efficiency is not significantly compromised even when seasonality is deterministic.