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What do we know about real exchange rate nonlinearities?

Author

Listed:
  • R. KRUSE
  • M. FR MMEL

  • L. MENKHOFF
  • P. SIBBERTSEN

Abstract

Nonlinear modeling of adjustments to purchasing power parity has recently gained much attention. However, a huge body of the empirical literature applies ES- TAR models and neglects the existence of other competing nonlinear models. Among these, the Markov Switching AR model has a strong substantiation in international finance. Our contribution to the literature is five-fold: First, we compare ESTAR and MSAR models from a unit root perspective. To this end, we propose a new unit root test against MSAR as the second contribution. Thirdly, we study the case of misspeci- fied alternatives in a Monte Carlo setup with real world parameter constellations. The ESTAR unit root test is not indicative, while the MSAR unit test is robust. Fourthly, we consider the case of correctly specified alternatives and observe low power of the ESTAR but not for the MSAR unit root test. Fifthly, an empirical application to real exchange rates suggests that they may indeed be explained by Markov Switching dy- namics rather than ESTAR.

Suggested Citation

  • R. Kruse & M. Fr Mmel & L. Menkhoff & P. Sibbertsen, 2010. "What do we know about real exchange rate nonlinearities?," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 10/667, Ghent University, Faculty of Economics and Business Administration.
    • Handle: RePEc:rug:rugwps:10/667
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    Cited by:

    1. Niels Haldrup & Robinson Kruse & Timo Teräsvirta & Rasmus T. Varneskov, 2013. "Unit roots, non-linearities and structural breaks," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 4, pages 61-94, Edward Elgar Publishing.
    2. Kaufmann, Hendrik & Kruse, Robinson & Sibbertsen, Philipp, 2012. "On tests for linearity against STAR models with deterministic trends," Economics Letters, Elsevier, vol. 117(1), pages 268-271.
    3. Aloy, Marcel & Boutahar, Mohamed & Gente, Karine & Péguin-Feissolle, Anne, 2011. "Purchasing power parity and the long memory properties of real exchange rates: Does one size fit all?," Economic Modelling, Elsevier, vol. 28(3), pages 1279-1290, May.
    4. Beckmann, Joscha, 2013. "Nonlinear adjustment, purchasing power parity and the role of nominal exchange rates and prices," The North American Journal of Economics and Finance, Elsevier, vol. 24(C), pages 176-190.
    5. Joe Maganga Zonda & Dinarti Tarigan, 2025. "Currency harmonisation in the Southern African Development Community: a pathway to addressing the PPP puzzle," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 12(1), pages 1-18, December.
    6. Brian M. Lucey & Fergal A. O’Connor, 2013. "Do bubbles occur in the gold price? An investigation of gold lease rates and Markov Switching models," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 13(3), pages 53-63, September.
    7. Joscha Beckmann, 2011. "Nonlinear Adjustment, Purchasing Power Parity and the Role of Nominal Exchange Rates and Prices," Ruhr Economic Papers 0272, Rheinisch-Westfälisches Institut für Wirtschaftsforschung, Ruhr-Universität Bochum, Universität Dortmund, Universität Duisburg-Essen.
    8. Dinçer Afat & Michael Frömmel, 2020. "An Alternative Version of Purchasing Power Parity," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 25(4), pages 511-517, October.
    9. Burns, Kelly & Moosa, Imad A., 2015. "Enhancing the forecasting power of exchange rate models by introducing nonlinearity: Does it work?," Economic Modelling, Elsevier, vol. 50(C), pages 27-39.
    10. Aaron D. Smallwood, 2016. "A Monte Carlo Investigation of Unit Root Tests and Long Memory in Detecting Mean Reversion in I(0) Regime Switching, Structural Break, and Nonlinear Data," Econometric Reviews, Taylor & Francis Journals, vol. 35(6), pages 986-1012, June.
    11. Leandro Maciel & Rosangela Ballini, 2021. "Functional Fuzzy Rule-Based Modeling for Interval-Valued Data: An Empirical Application for Exchange Rates Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 57(2), pages 743-771, February.

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    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • F31 - International Economics - - International Finance - - - Foreign Exchange

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