Specification of varying coefficient time series models via generalized flexible least squares

Flexible Least Squares (FLS) is a method for recursively estimating the time paths of the coefficients of a regression model with time-varying coefficients. In its standard form the FLS solution is capable of capturing smooth changes of the coefficients over the sample period. For time series models erratic coefficient changes, for instance, due to seasonal variation, are possible. A generalization of FLS is proposed which can account for such phenomena. The method is applied to artificially generated as well as real economic data. Specifically, West German income and consumption time series are analyzed in some detail.