Abstract

The Kalman filter may be easily understood by the econometricians, and forecasters if it is cast as a problem in Bayesian inference and if along the way some well-known results in multivariate statistics are employed. The aim is to motivate the readers by providing an exposition of the key notions of the predictive tool and by laying its derivation in a few easy steps. The paper does not deal with many other ad hoc techniques used in adaptive Kalman filtering.