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Testing of unit roots and other fractionally integrated hypotheses in the presence of structural breaks

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  • Gil-Alaña, Luis A.
Abstract
Tests for unit roots and other nonstationary hypotheses that were proposed by Robinson (1994) are applied in this article to the Nelson and Plosser's (1982) series. The tests can be expressed in a way allowing for structural breaks under both the null and the alternative hypotheses. When applying the tests to the same dataset as in Perron (1989) we observe that our results might be consistent with them when testing the nulls of trendstationarity or a unit-root. However, we also observe that fractionally integrated hypotheses may be plausible alternatives in this context of structural breaks at a known period of time.

Suggested Citation

  • Gil-Alaña, Luis A., 2000. "Testing of unit roots and other fractionally integrated hypotheses in the presence of structural breaks," SFB 373 Discussion Papers 2000,13, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    • Handle: RePEc:zbw:sfb373:200013
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    Cited by:

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    2. Gadea, Maria Dolores & Sabate, Marcela & Serrano, Jose Maria, 2004. "Structural breaks and their trace in the memory: Inflation rate series in the long-run," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 14(2), pages 117-134, April.
    3. Balcilar, Mehmet & Katzke, Nico & Gupta, Rangan, 2018. "Date-stamping US housing market explosivity," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 12, pages 1-33.
    4. Mehmet Balcilar & Zeynel Abidin Ozdemir & Esin Cakan, 2015. "Structural Breaks, Long Memory, or Unit Roots in Stock Prices: Evidence from Emerging Markets," International Econometric Review (IER), Econometric Research Association, vol. 7(1), pages 13-33, April.
    5. Jamal Bouoiyour & Refk Selmi, 2017. "Ether: Bitcoin's competitor or ally?," Working Papers hal-01567277, HAL.
    6. Mehmet Balcilar & Rangan Gupta & Charl Jooste & Omid Ranjbar, 2015. "Characterising the South African Business Cycle: Is GDP Difference-Stationary or Trend-Stationary in a Markov-Switching Setup?," Working Papers 201529, University of Pretoria, Department of Economics.
    7. Mehmet Balcilar & Nico Katzke & Rangan Gupta, 2015. "Identifying Periods of US Housing Market Explosivity," Working Papers 08/2015, Stellenbosch University, Department of Economics.
    8. Mohamed Boutahar & Gilles Dufrénot & Anne Péguin-Feissolle, 2008. "A Simple Fractionally Integrated Model with a Time-varying Long Memory Parameter d t," Computational Economics, Springer;Society for Computational Economics, vol. 31(3), pages 225-241, April.
    9. Luis A. Gil‐Alana, 2008. "Fractional integration and structural breaks at unknown periods of time," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(1), pages 163-185, January.
    10. Barros, Carlos Pestana & Gil-Alana, Luis A. & Payne, James E., 2011. "An analysis of oil production by OPEC countries: Persistence, breaks, and outliers," Energy Policy, Elsevier, vol. 39(1), pages 442-453, January.
    11. Guglielmo Caporale & Luis Gil-Alana, 2003. "Long memory and structural breaks in hyperinflation countries," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 27(2), pages 136-152, June.
    12. Luis Gil-Alana, 2008. "Real GDP growth rates across countries: long memory and mean shifts," Applied Economics Letters, Taylor & Francis Journals, vol. 15(6), pages 449-455.
    13. Zeynel Abidin Ozdemir & Mehmet Balcilar & Aysit Tansel, 2013. "International Labour Force Participation Rates By Gender: Unit Root Or Structural Breaks?," Bulletin of Economic Research, Wiley Blackwell, vol. 65, pages 142-164, May.

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    More about this item

    Keywords

    unit roots; long memory; structural breaks;
    All these keywords.

    JEL classification:

    • 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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