This paper discusses how to determine the order of a state-space model. To do so, we start by
revising existing approaches and find in them three basic shortcomings: i) some of them have a
poor performance in short samples, ii) most of them are not robust and iii) none of them can
accommodate seasonality. We tackle the first two issues by proposing new and refined criteria.
The third issue is dealt with by decomposing the system into regular and seasonal sub-systems.
The performance of all the procedures considered is analyzed through Monte Carlo simulations
