Additive Models

Abstract

We give an overview over smooth backfitting type estimators in additive models. Moreover we illustrate their wide applicability in models closely related to additive models such as nonparametric regression with dependent error variables where the errors can be transformed to white noise by a linear transformation, nonparametric regression with repeatedly measured data, nonparametric panels with fixed effects, simultaneous nonparametric equation models, and non- and semiparamet- ric autoregression and GARCH-models. We also discuss extensions to varying coeficient models, additive models with missing observations, and the case of nonstationary covariates.