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.