| dc.description.abstract | We study estimation of the date of change in persistence, from I(0) to I(1) or vice versa. Contrary
to statements in the original papers, our analytical results establish that the ratio-based break point
estimators of Kim [Kim, J.Y., 2000. Detection of change in persistence of a linear time series. Journal of
Econometrics 95, 97–116], Kim et al. [Kim, J.Y., Belaire-Franch, J., Badillo Amador, R., 2002. Corringendum
to ‘‘Detection of change in persistence of a linear time series’’. Journal of Econometrics 109, 389–392] and
Busetti and Taylor [Busetti, F., Taylor, A.M.R., 2004. Tests of stationarity against a change in persistence.
Journal of Econometrics 123, 33–66] are inconsistent when a mean (or other deterministic component) is
estimated for the process. In such cases, the estimators converge to random variables with upper bound
given by the true break date when persistence changes from I(0) to I(1). A Monte Carlo study confirms
the large sample downward bias and also finds substantial biases in moderate sized samples, partly due
to properties at the end points of the search interval. | en_GB |
