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Structural change in non-stationary AR(1) models

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  • Chong, Terence Tai Leung
  • Pang, Tianxiao
  • Zhang, Danna
  • Liang, Yanling

Abstract

This paper revisits the asymptotic inference for non-stationary AR(1) models of Phillips and Magdalinos (2007a) by incorporating a structural change in the AR parameter at an unknown time k0. We derive the limiting distributions of the t-ratios of beta1 and beta2 and the least squares estimator of the change point for the cases above under some mild conditions. Monte Carlo simulations are conducted to examine the finite-sample properties of the estimators. Our theoretical findings are supported by the Monte Carlo simulations.

Suggested Citation

  • Chong, Terence Tai Leung & Pang, Tianxiao & Zhang, Danna & Liang, Yanling, 2017. "Structural change in non-stationary AR(1) models," MPRA Paper 80510, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:80510
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    References listed on IDEAS

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    5. 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:

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    2. Tu, Yundong & Xie, Xinling, 2023. "Penetrating sporadic return predictability," Journal of Econometrics, Elsevier, vol. 237(1).
    3. Westerlund, Joakim & Nordström, Marcus, 2021. "Breaks in persistence in fixed-T panel data," Economics Letters, Elsevier, vol. 205(C).
    4. Eiji Kurozumi & Anton Skrobotov, 2021. "On the asymptotic behavior of bubble date estimators," Papers 2110.04500, arXiv.org, revised Sep 2022.

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    More about this item

    Keywords

    AR(1) model; Least squares estimator; Limiting distribution; Mildly explosive; Mildly integrated; Structural change; Unit root.;
    All these keywords.

    JEL classification:

    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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