Detecting multiple changes in persistence

Stephen Leybourne, Tae-Hwan Kim, A. M.Robert Taylor

Research output: Contribution to journalArticle

37 Citations (Scopus)

Abstract

This paper considers the problem of testing for and dating changes (at unknown points) in the order of integration of a time series between different trend-stationary and difference-stationary regimes. While existing procedures in the literature are designed for processes displaying only a single such change in persistence, our proposed methodology is also valid in the presence of multiple changes in persistence. Our procedure is based on sequences of doubly-recursive implementations of the regression-based unit root statistic of Elliott et al. (1996). The asymptotic validity of our procedure is demonstrated analytically. We use Monte Carlo methods to simulate both finite sample and asymptotic critical values for our proposed testing procedure and to simulate the finite sample behaviour of our procedure against a variety of single and multiple persistence change series. The procedure is shown to work well in practice. The impact of deterministic level and trend breaks on our procedure is also discussed. An empirical application of the procedure to interest rate data is considered.

Original languageEnglish
Article number2
JournalStudies in Nonlinear Dynamics and Econometrics
Volume11
Issue number3
DOIs
Publication statusPublished - 2007 Jan 1

Fingerprint

Persistence
persistence
testing procedure
Testing
trend
interest rate
Unit Root
Interest Rates
time series
Monte Carlo method
Statistic
Critical value
statistics
regime
Time series
Regression
regression
Valid
Unknown
methodology

All Science Journal Classification (ASJC) codes

  • Analysis
  • Social Sciences (miscellaneous)
  • Economics and Econometrics

Cite this

Leybourne, Stephen ; Kim, Tae-Hwan ; Taylor, A. M.Robert. / Detecting multiple changes in persistence. In: Studies in Nonlinear Dynamics and Econometrics. 2007 ; Vol. 11, No. 3.
@article{b9d23759119e44b3a3cb335d616665cf,
title = "Detecting multiple changes in persistence",
abstract = "This paper considers the problem of testing for and dating changes (at unknown points) in the order of integration of a time series between different trend-stationary and difference-stationary regimes. While existing procedures in the literature are designed for processes displaying only a single such change in persistence, our proposed methodology is also valid in the presence of multiple changes in persistence. Our procedure is based on sequences of doubly-recursive implementations of the regression-based unit root statistic of Elliott et al. (1996). The asymptotic validity of our procedure is demonstrated analytically. We use Monte Carlo methods to simulate both finite sample and asymptotic critical values for our proposed testing procedure and to simulate the finite sample behaviour of our procedure against a variety of single and multiple persistence change series. The procedure is shown to work well in practice. The impact of deterministic level and trend breaks on our procedure is also discussed. An empirical application of the procedure to interest rate data is considered.",
author = "Stephen Leybourne and Tae-Hwan Kim and Taylor, {A. M.Robert}",
year = "2007",
month = "1",
day = "1",
doi = "10.2202/1558-3708.1370",
language = "English",
volume = "11",
journal = "Studies in Nonlinear Dynamics and Econometrics",
issn = "1081-1826",
publisher = "Berkeley Electronic Press",
number = "3",

}

Detecting multiple changes in persistence. / Leybourne, Stephen; Kim, Tae-Hwan; Taylor, A. M.Robert.

In: Studies in Nonlinear Dynamics and Econometrics, Vol. 11, No. 3, 2, 01.01.2007.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Detecting multiple changes in persistence

AU - Leybourne, Stephen

AU - Kim, Tae-Hwan

AU - Taylor, A. M.Robert

PY - 2007/1/1

Y1 - 2007/1/1

N2 - This paper considers the problem of testing for and dating changes (at unknown points) in the order of integration of a time series between different trend-stationary and difference-stationary regimes. While existing procedures in the literature are designed for processes displaying only a single such change in persistence, our proposed methodology is also valid in the presence of multiple changes in persistence. Our procedure is based on sequences of doubly-recursive implementations of the regression-based unit root statistic of Elliott et al. (1996). The asymptotic validity of our procedure is demonstrated analytically. We use Monte Carlo methods to simulate both finite sample and asymptotic critical values for our proposed testing procedure and to simulate the finite sample behaviour of our procedure against a variety of single and multiple persistence change series. The procedure is shown to work well in practice. The impact of deterministic level and trend breaks on our procedure is also discussed. An empirical application of the procedure to interest rate data is considered.

AB - This paper considers the problem of testing for and dating changes (at unknown points) in the order of integration of a time series between different trend-stationary and difference-stationary regimes. While existing procedures in the literature are designed for processes displaying only a single such change in persistence, our proposed methodology is also valid in the presence of multiple changes in persistence. Our procedure is based on sequences of doubly-recursive implementations of the regression-based unit root statistic of Elliott et al. (1996). The asymptotic validity of our procedure is demonstrated analytically. We use Monte Carlo methods to simulate both finite sample and asymptotic critical values for our proposed testing procedure and to simulate the finite sample behaviour of our procedure against a variety of single and multiple persistence change series. The procedure is shown to work well in practice. The impact of deterministic level and trend breaks on our procedure is also discussed. An empirical application of the procedure to interest rate data is considered.

UR - http://www.scopus.com/inward/record.url?scp=34948867132&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=34948867132&partnerID=8YFLogxK

U2 - 10.2202/1558-3708.1370

DO - 10.2202/1558-3708.1370

M3 - Article

VL - 11

JO - Studies in Nonlinear Dynamics and Econometrics

JF - Studies in Nonlinear Dynamics and Econometrics

SN - 1081-1826

IS - 3

M1 - 2

ER -