On multiple regression models with nonstationary correlated errors

We consider the estimation of parameters of a multiple regression model with nonstationary errors. We assume the nonstationary errors satisfy a time-dependent autogressive process and describe a method to estimate the parameters of the regressors and the time-dependent autoregressive parameters. The parameters are rescaled as in nonparametric regression to obtain the asymptotic sampling properties of the estimators. The method is illustrated with an example taken from global temperature anomalies.