Ratio-based estimators for a change point in persistence

Andreea G. Halunga, Denise R. Osborn

Research output: Contribution to journalArticlepeer-review


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. © 2012 Elsevier B.V. All rights reserved.
Original languageEnglish
Pages (from-to)24-31
Number of pages7
JournalJournal of Econometrics
Issue number1
Publication statusPublished - Nov 2012


  • Order of integration
  • Persistence change
  • Structural breaks


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