The joint asymptotic distribution of multistep prediction errors of estimated vector autoregressions

Abstract The joint asymptotic distribution of multistep prediction errors of an estimated stationary vector autoregressive process is given under the assumption that the order of the underlying process is unknown. This result can, for instance, be used to derive the asymptotic distribution of prediction errors of certain non-stationary processes.