On multiple regression models with nonstationary
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