  In this article, we study the statistical and asymptotic properties of
break-point estimators in nonstationary autoregressive and predictive
regression models for testing the presence of a single structural break at an
unknown location in the full sample. Moreover, we investigate aspects such as
how the persistence properties of covariates and the location of the
break-point affects the limiting distribution of the proposed break-point
estimators.
