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Econometric modeling of the relationship among macroeconomic variables of Thailand: Smooth transition autoregressive regression model

Author

Listed:
  • Nachatchapong Kaewsompong

    (Chiang Mai University)

  • Songsak Sriboonchitta

    (Chiang Mai University)

  • Prasert Chaitip

    (Chiang Mai University)

  • Pathairat Pastpipatkul

    (Chiang Mai University)

Abstract

There is evidence of non-linear in macroeconomic variables of Thailand. To understand the behavior of this economic indicators, this paper used the smooth transition autoregressive model (STAR) that was developed by the contribution of Ter?svirta and Anderson (1992). This paper used quarterly data for the period of 1997:3 to 2012:1. The linearity test shows that almost all variables have non-linear behavior with logistic STAR (LSTAR) except in the investment growth rate. The results show that GDP growth rate have suddenly moved from negative to positive on a quarterly period and most of its observation remained in the upper regime. Moreover, inflation rate, unemployment rate, and interest rate are slow in adjustment to reducing their values, and most of them that was based on observation belonged in the lower regime. For investment growth rate, this paper used linear AR(2) model to estimate the parameter and prediction. The results showed that there is tremendous fluctuate movement in the percentile of -30% to 30%.

Suggested Citation

  • Nachatchapong Kaewsompong & Songsak Sriboonchitta & Prasert Chaitip & Pathairat Pastpipatkul, 2012. "Econometric modeling of the relationship among macroeconomic variables of Thailand: Smooth transition autoregressive regression model," The Empirical Econometrics and Quantitative Economics Letters, Faculty of Economics, Chiang Mai University, vol. 1(4), pages 21-38, December.
    • Handle: RePEc:chi:journl:v:1:y:2012:i:4:p:21-38
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    References listed on IDEAS

    as
    1. Dick van Dijk & Timo Terasvirta & Philip Hans Franses, 2002. "Smooth Transition Autoregressive Models — A Survey Of Recent Developments," Econometric Reviews, Taylor & Francis Journals, vol. 21(1), pages 1-47.
    2. K. S. Chan & H. Tong, 1986. "On Estimating Thresholds In Autoregressive Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 7(3), pages 179-190, May.
    3. Anderson, Heather M. & Vahid, Farshid, 1998. "Testing multiple equation systems for common nonlinear components," Journal of Econometrics, Elsevier, vol. 84(1), pages 1-36, May.
    4. 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 119-136, Suppl. De.
    5. Terasvirta, Timo & Tjostheim, Dag & Granger, Clive W. J., 2010. "Modelling Nonlinear Economic Time Series," OUP Catalogue, Oxford University Press, number 9780199587155.
    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. Teräsvirta, Timo, 1996. "Smooth Transition Models," SSE/EFI Working Paper Series in Economics and Finance 132, Stockholm School of Economics.
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    Cited by:

    1. Kyaw Kyaw Lynn, 2015. "An Analysis of the Relationship between Foreign Trade and Economic Growth in Myanmar during 1990-2014," International Journal of Business and Administrative Studies, Professor Dr. Bahaudin G. Mujtaba, vol. 1(4), pages 114-131.

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