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Asymptotic Inferences For An Ar(1) Model With A Change Point: Stationary And Nearly Non-Stationary Cases

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  • Tianxiao Pang
  • Danna Zhang
  • Terence Tai-Leung Chong

Abstract

type="main" xml:id="jtsa12055-abs-0001"> This article examines the asymptotic inference for AR(1) models with a possible structural break in the AR parameter β near the unity at an unknown time k 0 . Consider the model y t = β 1 y t − 1 I{t ≤ k 0 } + β 2 y t − 1 I{t > k 0 } + ϵ t , t = 1,2, … ,T, where I{ ⋅ } denotes the indicator function. We examine two cases: case I &7C β 1 &7C > 1,β 2 = β 2T = 1 − c ∕ T; and case II β 1 = β 1T = 1 − c ∕ T, &7C β 2 &7C > 1, where c is a fixed constant, and {ϵ t ,t ≥ 1} is a sequence of i.i.d. random variables, which are in the domain of attraction of the normal law with zero means and possibly infinite variances. We derive the limiting distributions of the least squares estimators of β 1 and β 2 and that of the break-point estimator for shrinking break for the aforementioned cases. Monte Carlo simulations are conducted to demonstrate the finite-sample properties of the estimators. Our theoretical results are supported by Monte Carlo simulations.

Suggested Citation

  • Tianxiao Pang & Danna Zhang & Terence Tai-Leung Chong, 2014. "Asymptotic Inferences For An Ar(1) Model With A Change Point: Stationary And Nearly Non-Stationary Cases," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(2), pages 133-150, March.
    • Handle: RePEc:bla:jtsera:v:35:y:2014:i:2:p:133-150
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    References listed on IDEAS

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    8. Pang, Tianxiao & Zhang, Danna & Chong, Terence Tai-Leung, 2013. "Asymptotic Inferences for an AR(1) Model with a Change Point: Stationary and Nearly Non-stationary Cases," MPRA Paper 55312, University Library of Munich, Germany.
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    Cited by:

    1. Maria Mohr & Leonie Selk, 2020. "Estimating change points in nonparametric time series regression models," Statistical Papers, Springer, vol. 61(4), pages 1437-1463, August.
    2. Tao, Yubo & Phillips, Peter C.B. & Yu, Jun, 2019. "Random coefficient continuous systems: Testing for extreme sample path behavior," Journal of Econometrics, Elsevier, vol. 209(2), pages 208-237.
    3. Tao, Yubo & Phillips, Peter C.B. & Yu, Jun, 2017. "Random Coefficient Continuous Systems: Testing for Extreme Sample Path Behaviour," Economics and Statistics Working Papers 18-2017, Singapore Management University, School of Economics.
    4. Pang, Tianxiao & Tai-Leung Chong, Terence & Zhang, Danna & Liang, Yanling, 2018. "Structural Change In Nonstationary Ar(1) Models," Econometric Theory, Cambridge University Press, vol. 34(5), pages 985-1017, October.

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