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Tests for Cointegration with Structural Breaks Based on Subsamples

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  • James Davidson

    (Department of Economics, University of Exeter)

  • Andrea Monticini

    (Department of Economics, University of Exeter)

Abstract

This paper considers tests for cointegration with allowance for structural breaks, using the extrema of residual-based tests over subsamples of the data. One motivation for the approach is to formalize the practice of data snooping by practitioners, who may examine subsamples after failing to find a predicted cointegrating relationship. Valid critical values for such multiple testing situations may be useful. The methods also have the advantage of not imposing a form for the alternative hypothesis, in particular slope vs. intercept shifts and single versus multiple breaks, and being comparatively easy to compute. A range of alternative subsampling procedures, including sample splits, incremental and rolling samples are tabulated and compared experimentally. Shiller's annual stock prices and dividends series provide an illustration.

Suggested Citation

  • James Davidson & Andrea Monticini, 2007. "Tests for Cointegration with Structural Breaks Based on Subsamples," Discussion Papers 0704, University of Exeter, Department of Economics.
    • Handle: RePEc:exe:wpaper:0704
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    File URL: https://exetereconomics.github.io/RePEc/dpapers/DP0704.pdf
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    3. Theologos Dergiades & Panos K. Pouliasis, 2023. "Should stock returns predictability be ‘hooked on’ long‐horizon regressions?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 718-732, January.
    4. Jopp, Tobias A., 2017. "How does the public perceive alliances? The Central and Allied Powers in World War I," IBF Paper Series 12-17, IBF – Institut für Bank- und Finanzgeschichte / Institute for Banking and Financial History, Frankfurt am Main.
    5. Martins, Luis F. & Rodrigues, Paulo M.M., 2014. "Testing for persistence change in fractionally integrated models: An application to world inflation rates," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 502-522.
    6. Atle Oglend, Morten E. Lindbäck, and Petter Osmundsen, 2015. "Shale Gas Boom Affecting the Relationship Between LPG and Oil Prices," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    7. Lindback, Morten & Osmundsen, Petter & Øglend, Atle, 2013. "Shale Gas and the Relationship between U.S. Natural Gas, Liquified Petroleum Gases and Oil Market," UiS Working Papers in Economics and Finance 2013/5, University of Stavanger.
    8. Panopoulou, Ekaterini & Pantelidis, Theologos, 2016. "The Fisher effect in the presence of time-varying coefficients," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 495-511.
    9. Paulo M.M. Rodrigues & Philipp Sibbertsen, 2019. "Testing for breaks in the cointegrating relationship: On the stability of government bond markets’ equilibrium," Working Papers w201912, Banco de Portugal, Economics and Research Department.
    10. Karsten Schweikert, 2020. "Oracle Efficient Estimation of Structural Breaks in Cointegrating Regressions," Papers 2001.07949, arXiv.org, revised Apr 2021.
    11. Karsten Schweikert, 2022. "Oracle Efficient Estimation of Structural Breaks in Cointegrating Regressions," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(1), pages 83-104, January.
    12. Luis F. Martins & Paulo M. M. Rodrigues, 2022. "Tests for segmented cointegration: an application to US governments budgets," Empirical Economics, Springer, vol. 63(2), pages 567-600, August.

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    More about this item

    Keywords

    Level shift; Regime shift; Cointegration; Brownian motion;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

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