On Structural Time Series Models and the Characterization of Components

This article analyzes certain properties of a class of recently proposed structural time series models in which particular structures are imposed upon the unobserved components of an observed time series. It is shown how the overall model can be expected to fit series, such as those for which the X-11 or Airline models are appropriate. As for the components, identification of the model is achieved by assigning a certain amount of white noise variation to the trend and seasonal components. It is shown that the structural approach can be modified to avoid trend and seasonal components contaminated by noise.