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Smooth Transitions, Asymmetric Adjustment and Unit Roots

Author

Listed:
  • Juan Carlos Cuestas

    (Department of Economics, The University of Sheffield)

  • Javier Ordóñez

    (University of Bath)

Abstract

The aim of this paper is to develop a unit root test that takes into account two sources of nonlinearites in data, i.e. asymmetric speed of mean reversion and structural changes. The asymmetric speed of mean reversion is modeled by means of a exponential smooth transition autoregression (ESTAR) function for the autoregressive parameter, whereas structural changes are approximated by a smooth transition in the deterministic components. We find that the proposed test performs well in terms of size and power, in particular when the autoregressive parameter is close to one.

Suggested Citation

  • Juan Carlos Cuestas & Javier Ordóñez, 2012. "Smooth Transitions, Asymmetric Adjustment and Unit Roots," Working Papers 2012012, The University of Sheffield, Department of Economics.
  • Handle: RePEc:shf:wpaper:2012012
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    References listed on IDEAS

    as
    1. John Y. Campbell & Pierre Perron, 1991. "Pitfalls and Opportunities: What Macroeconomists Should Know about Unit Roots," NBER Chapters, in: NBER Macroeconomics Annual 1991, Volume 6, pages 141-220, National Bureau of Economic Research, Inc.
    2. Kapetanios, George & Shin, Yongcheol & Snell, Andy, 2003. "Testing for a unit root in the nonlinear STAR framework," Journal of Econometrics, Elsevier, vol. 112(2), pages 359-379, February.
    3. Zivot, Eric & Andrews, Donald W K, 2002. "Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 25-44, January.
    4. Chong, Terence Tai-Leung & Hinich, Melvin J. & Liew, Venus Khim-Sen & Lim, Kian-Ping, 2008. "Time series test of nonlinear convergence and transitional dynamics," Economics Letters, Elsevier, vol. 100(3), pages 337-339, September.
    5. Perron, Pierre & Rodriguez, Gabriel, 2003. "GLS detrending, efficient unit root tests and structural change," Journal of Econometrics, Elsevier, vol. 115(1), pages 1-27, July.
    6. Enders, Walter & Granger, Clive W J, 1998. "Unit-Root Tests and Asymmetric Adjustment with an Example Using the Term Structure of Interest Rates," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(3), pages 304-311, July.
    7. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
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    12. Bierens, Herman J., 1997. "Testing the unit root with drift hypothesis against nonlinear trend stationarity, with an application to the US price level and interest rate," Journal of Econometrics, Elsevier, vol. 81(1), pages 29-64, November.
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    Cited by:

    1. Hepsag, Aycan, 2017. "A unit root test based on smooth transitions and nonlinear adjustment," MPRA Paper 81788, University Library of Munich, Germany.
    2. Chen, Shyh-Wei & Xie, Zixiong, 2015. "Testing for current account sustainability under assumptions of smooth break and nonlinearity," International Review of Economics & Finance, Elsevier, vol. 38(C), pages 142-156.
    3. Hepsag, Aycan, 2017. "New unit root tests with two smooth breaks and nonlinear adjustment," MPRA Paper 83353, University Library of Munich, Germany.
    4. Jiang, Chun & Jian, Na & Liu, Tie-Ying & Su, Chi-Wei, 2016. "Purchasing power parity and real exchange rate in Central Eastern European countries," International Review of Economics & Finance, Elsevier, vol. 44(C), pages 349-358.

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    More about this item

    Keywords

    unit roots; nonlinear trends; exponential smooth transition; autoregressive model; structural change;
    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

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