Bayesian Unobserved Component Models

We present the basics of Bayesian estimation and inference for unobserved component models on the example of a local-level model. The range of topics includes the conjugate prior analysis using normal-inverted-gamma 2 distribution and its extensions focusing on hierarchical modelling, conditional heteroskedasticity, and Student-t error terms. We scrutinise Bayesian forecasting and sampling from the predictive density.