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How Well the Ringgit-Yen Rate Fits the Non-linear Smooth Transition Autoregressive and Linear Autoregressive Models

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  • Liew Khim Sen

    (Universiti Putra Malaysia)

  • Ahmad Zubaidi Baharumshah

    (Universiti Putra Malaysia)

Abstract

This study compares the forecasting performance between Smooth Transition Autoregressive (STAR) non-linear model and the conventional linear Autoregressive (AR) time series model using the simple random walk (SRW) model as the standard reference model. To accomplish this objective, quarterly frequency exchange rate data, which is well known for its non-linear adjustment towards purchasing power parity equilibrium path is employed. The empirical results suggest that both the STAR and AR models exceed or match the performance of SRW model based mean absolute forecast error (MAFE) mean absolute percentage forecast error (MAPFE) and mean square forecast error (RMSFE). The results also show that the STAR model outperform the AR model, its linear competitor. This is consistent with the emerging line of research that emphasised the importance of allowing non-linearity in the adjustment of exchange rate toward its long run equilibrium.

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Bibliographic Info

Paper provided by EconWPA in its series GE, Growth, Math methods with number 0307004.

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Date of creation: 23 Jul 2003
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Handle: RePEc:wpa:wuwpge:0307004

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Web page: http://128.118.178.162

Related research

Keywords: Autoregressive; Smooth Transition Autoregressive; non-linear time series; forecasting accuracy;

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References

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  1. Jun Nagayasu, 1998. "Does the Long-Run Ppp Hypothesis Hold for Africa? Evidence From Panel Co-Integration Study," IMF Working Papers 98/123, International Monetary Fund.
  2. Baum, Christopher F. & Barkoulas, John T. & Caglayan, Mustafa, 2001. "Nonlinear adjustment to purchasing power parity in the post-Bretton Woods era," Journal of International Money and Finance, Elsevier, vol. 20(3), pages 379-399, June.
  3. Clements, M.P. & Smith, J., 1998. "Non-Linearities in Exchange Rates," The Warwick Economics Research Paper Series (TWERPS) 504, University of Warwick, Department of Economics.
  4. Jerry Coakley & Ana-Maria Fuertes, 2001. "Nonparametric cointegration analysis of real exchange rates," Applied Financial Economics, Taylor & Francis Journals, vol. 11(1), pages 1-8.
  5. Terasvirta, T & Anderson, H M, 1992. "Characterizing Nonlinearities in Business Cycles Using Smooth Transition Autoregressive Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(S), pages S119-36, Suppl. De.
  6. Eitrheim, Oyvind & Terasvirta, Timo, 1996. "Testing the adequacy of smooth transition autoregressive models," Journal of Econometrics, Elsevier, vol. 74(1), pages 59-75, September.
  7. Taylor, Mark P. & Peel, David A., 2000. "Nonlinear adjustment, long-run equilibrium and exchange rate fundamentals," Journal of International Money and Finance, Elsevier, vol. 19(1), pages 33-53, February.
  8. Francis X. Diebold & James M. Nason, 1989. "Nonparametric exchange rate prediction?," Finance and Economics Discussion Series 81, Board of Governors of the Federal Reserve System (U.S.).
  9. Azali, M. & Habibullah, M. S. & Baharumshah, A. Z., 2001. "Does PPP hold between Asian and Japanese economies? Evidence using panel unit root and panel cointegration," Japan and the World Economy, Elsevier, vol. 13(1), pages 35-50, January.
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Cited by:
  1. Liew Khim Sen & Ahmad Zubaidi Baharumshah & Choo Wei Chong & Habshah Midi, 2003. "A Non-parametric Bootstrap Simulation Study in ESTAR (1) Model," GE, Growth, Math methods 0307005, EconWPA.

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