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On the Robustness of Cointegration Tests when Series Are Fractionally Integrated

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  • Lee, T.H.
  • Gonzalo, J.

Abstract

This paper shows that when series are fractionally integrated, but unit root tests wrongly indicate that they are I(1), Johansen likelihood ratio (LR) tests tend to find too much spurious cointegration, while the Engle-Granger test presents a more robust performance. This result holds asymptotically as well as infinite samples. The different performance of these two methods is due to the fact that they are based on different principles. The Johansen procedure is based on maximizing correlations (canonical correlation) while Engle-Granger minimizes variances (in the spirit of principal components).
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Suggested Citation

  • Lee, T.H. & Gonzalo, J., 1995. "On the Robustness of Cointegration Tests when Series Are Fractionally Integrated," The A. Gary Anderson Graduate School of Management 95-11, The A. Gary Anderson Graduate School of Management. University of California Riverside.
    • Handle: RePEc:fth:caland:95-11
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    as
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    10. repec:crs:wpaper:8913 is not listed on IDEAS
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    20. Sowell, Fallaw, 1990. "The Fractional Unit Root Distribution," Econometrica, Econometric Society, vol. 58(2), pages 495-505, March.
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    Cited by:

    1. Arielle Beyaert, 2004. "Fractional Output Convergence, with an Application to Nine Developed Countries," Econometric Society 2004 Australasian Meetings 280, Econometric Society.
    2. Nafeesa Yunus, 2016. "Modelling interactions among the housing market and key US sectors," Journal of Property Research, Taylor & Francis Journals, vol. 33(2), pages 121-146, April.
    3. Giorgio Canarella & Stephen M Miller, 2017. "Inflation Persistence Before and After Inflation Targeting: A Fractional Integration Approach," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 43(1), pages 78-103, January.
    4. Boubaker, Heni & Zorgati, Mouna Ben Saad & Bannour, Nawres, 2021. "Interdependence between exchange rates: Evidence from multivariate analysis since the financial crisis to the COVID-19 crisis," Economic Analysis and Policy, Elsevier, vol. 71(C), pages 592-608.
    5. Giorgio Canarella & Stephen M. Miller, 2016. "Inflation Persistence and Structural Breaks: The Experience of Inflation Targeting Countries and the US," Working papers 2016-11, University of Connecticut, Department of Economics.
    6. Sascha Keil, 2023. "The challenging estimation of trade elasticities: Tackling the inconclusive Eurozone evidence," The World Economy, Wiley Blackwell, vol. 46(5), pages 1235-1263, May.
    7. Nafeesa Yunus, 2009. "Increasing Convergence Between U.S. and International Securitized Property Markets: Evidence Based on Cointegration Tests," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 37(3), pages 383-411, September.
    8. Ramya Rajajagadeesan Aroul & Peggy E. Swanson, 2018. "Linkages Between the Foreign Exchange Markets of BRIC Countries—Brazil, Russia, India and China—and the USA," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 17(3), pages 333-353, December.
    9. Nafeesa Yunus & Peggy Swanson, 2007. "Modelling Linkages between US and Asia‐Pacific Securitized Property Markets," Journal of Property Research, Taylor & Francis Journals, vol. 24(2), pages 95-122.
    10. Sascha Keil, 2021. "The Challenging Estimation Of Trade Elasticities:Tackling The Inconclusive Eurozone Evidence," Chemnitz Economic Papers 042, Department of Economics, Chemnitz University of Technology, revised May 2021.
    11. Nikolas Stege & Christoph Wegener & Tobias Basse & Frederik Kunze, 2021. "Mapping swap rate projections on bond yields considering cointegration: an example for the use of neural networks in stress testing exercises," Annals of Operations Research, Springer, vol. 297(1), pages 309-321, February.

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    More about this item

    Keywords

    COINTEGRATION; TESTS; UNIT ROOTS;
    All these keywords.

    JEL classification:

    • 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
    • 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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