A Robust Sequential Procedure for Estimating the Number of Structural Changes in Persistence

This paper proposes a new procedure for estimating the number of structural changes in the persistence of a univariate time series. While the extant literature primarily assumes (regime‐wise) stationarity, our framework also allows the underlying stochastic process to switch between stationary [ I (0)] and unit root regimes [ I (1)]. We develop a sequential testing approach that maintains correct asymptotic size regardless of whether the regimes are I (0) or I (1). We also propose a novel procedure for distinguishing persistence change processes from those with pure level and/or trend shifts. Monte Carlo simulations and an application to OECD inflation rates highlight the practical usefulness of the procedures.