Premium
A Robust Sequential Procedure for Estimating the Number of Structural Changes in Persistence
Author(s) -
Kejriwal Mohitosh
Publication year - 2020
Publication title -
oxford bulletin of economics and statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.131
H-Index - 73
eISSN - 1468-0084
pISSN - 0305-9049
DOI - 10.1111/obes.12348
Subject(s) - unit root , univariate , persistence (discontinuity) , econometrics , extant taxon , monte carlo method , series (stratigraphy) , inflation (cosmology) , mathematics , sequential analysis , computer science , statistical physics , statistics , multivariate statistics , engineering , paleontology , physics , geotechnical engineering , evolutionary biology , theoretical physics , biology
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.