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Testing the Null of Stationarity in the Presence of Structural Breaks for Multiple Time Series

Author

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  • Robert Taylor
  • Byung Chul Ahn

Abstract

This paper introduces various consistent tests for the null hypothesis of stationarity with possibly unknown multiple structural break points against the alternative of non-stationarity that can be applied both to univariate and multiple time series, and both to partial or pure structural breaks. The paper shows that tests for stationarity become divergent when structural breaks are ignored. We also demonstrate that one can allow for a variety of structural breaks for which limiting distributions are derived and tabulated. Finite sample properties are studied by simulation. We also consider multivariate testing strategy and univariate tests and find that multivariate tests are often more powerful than univariate tests.

Suggested Citation

  • Robert Taylor & Byung Chul Ahn, 2015. "Testing the Null of Stationarity in the Presence of Structural Breaks for Multiple Time Series," Journal of Economics and Econometrics, Economics and Econometrics Society, vol. 58(2), pages 85-119.
    • Handle: RePEc:eei:journl:v:58:y:2015:i:2:p:85-119
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    More about this item

    Keywords

    Stationarity; structural breaks; LM test; Sargan-Bhargava-Durbin-Hausman test; multiple time series.;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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