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Testing the null of stationarity in the presence of structural breaks for multiple time series

Author

Listed:
  • Ahn

    (The Ohio State University)

  • Byung Chul

    (The Ohio State University)

Abstract

This paper introduces various consistent tests for the null hypothesis of stationarity with possibly unknown multiple structural break points against the alternative of nonstationarity that can be applied to multiple as well as univariate time series. These tests can be applied to either partial or pure structural breaks. It is shown that tests for stationarity become divergent when structural breaks are ignored. We show that we can allow 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

  • Ahn & Byung Chul, 1994. "Testing the null of stationarity in the presence of structural breaks for multiple time series," Econometrics 9411001, EconWPA, revised 08 Nov 1994.
  • Handle: RePEc:wpa:wuwpem:9411001
    Note: 42 pages, Tex file, ASCII-file.
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    References listed on IDEAS

    as
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    Citations

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    Cited by:

    1. D.K. Srivastava & K.R. Shanmugam, 2012. "Stationarity Test for Aggregate Outputs in the Presence of Structural Breaks," Working Papers 2012-072, Madras School of Economics,Chennai,India.
    2. Lee, Junsoo & Huang, Cliff J. & Shin, Yongcheol, 1997. "On stationary tests in the presence of structural breaks," Economics Letters, Elsevier, vol. 55(2), pages 165-172, August.
    3. Devi, P. Indira & Shanmugam, K.R. & Jayasree, M.G., 2012. "Compensating Wages for Occupational Risks of Farm Workers in India," Indian Journal of Agricultural Economics, Indian Society of Agricultural Economics, vol. 67(2).

    More about this item

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs

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