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Simulation-based finite-sample linearity test against smooth transition models

Author

Listed:
  • González, Andrés

    (Dept. of Economic Statistics, Stockholm School of Economics)

  • Teräsvirta, Timo

    (Dept. of Economic Statistics, Stockholm School of Economics)

Abstract

In this paper we use Monte Carlo testing techniques for testing linearity against the smooth transition models. The Monte Carlo approach allows us to introduce a new test that differs from the tests existing in the literature in two respects. First, the test is exact in the sense that the probability of rejecting the null when it is true is always less that or equal to the nominal size of the test. Second, the test is not based on an auxiliary regression obtained by replacing the model under the alternative by approximations based on a Taylor expansion. We also apply Monte Carlo testing methods for size-correcting the test proposed by Luukkonen Saikkonen and Teräsvirta (1988). Simulated annealing is used in computing values of the test statistics. The results show that the power loss implied by the auxiliary regression based test is nonexistent compared to a supremum-based test but is more substantial when compared to the other three tests under consideration.

Suggested Citation

  • González, Andrés & Teräsvirta, Timo, 2005. "Simulation-based finite-sample linearity test against smooth transition models," SSE/EFI Working Paper Series in Economics and Finance 603, Stockholm School of Economics.
    • Handle: RePEc:hhs:hastef:0603
    Note: This is the working paper version referred to in the published paper (Oxford Bulletin of Economics and Statistics 68, 797-812).
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    References listed on IDEAS

    as
    1. Dufour, Jean-Marie & Kiviet, Jan F., 1996. "Exact tests for structural change in first-order dynamic models," Journal of Econometrics, Elsevier, vol. 70(1), pages 39-68, January.
    2. Hansen, Bruce E, 1996. "Inference When a Nuisance Parameter Is Not Identified under the Null Hypothesis," Econometrica, Econometric Society, vol. 64(2), pages 413-430, March.
    3. 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.
    4. González, Andrés & Teräsvirta, Timo & van Dijk, Dick & Yang, Yukai, 2005. "Panel Smooth Transition Regression Models," SSE/EFI Working Paper Series in Economics and Finance 604, Stockholm School of Economics, revised 11 Oct 2017.
    5. Dufour, Jean-Marie & Khalaf, Lynda & Bernard, Jean-Thomas & Genest, Ian, 2004. "Simulation-based finite-sample tests for heteroskedasticity and ARCH effects," Journal of Econometrics, Elsevier, vol. 122(2), pages 317-347, October.
    6. Andrews, Donald W K & Ploberger, Werner, 1994. "Optimal Tests When a Nuisance Parameter Is Present Only under the Alternative," Econometrica, Econometric Society, vol. 62(6), pages 1383-1414, November.
    7. Dufour, Jean-Marie, 2006. "Monte Carlo tests with nuisance parameters: A general approach to finite-sample inference and nonstandard asymptotics," Journal of Econometrics, Elsevier, vol. 133(2), pages 443-477, August.
    8. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-856, July.
    9. Robert F. Engle & Aaron D. Smith, 1999. "Stochastic Permanent Breaks," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 553-574, November.
    10. Bruce E. Hansen, 2000. "Sample Splitting and Threshold Estimation," Econometrica, Econometric Society, vol. 68(3), pages 575-604, May.
    11. Khalaf, Lynda & Saphores, Jean-Daniel & Bilodeau, Jean-Francois, 2003. "Simulation-based exact jump tests in models with conditional heteroskedasticity," Journal of Economic Dynamics and Control, Elsevier, vol. 28(3), pages 531-553, December.
    12. Goffe, William L. & Ferrier, Gary D. & Rogers, John, 1994. "Global optimization of statistical functions with simulated annealing," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 65-99.
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    Cited by:

    1. Fracasso, Andrea & Vittucci Marzetti, Giuseppe, 2015. "International trade and R&D spillovers," Journal of International Economics, Elsevier, vol. 96(1), pages 138-149.
    2. Andrea Fracasso & Giuseppe Vittucci Marzetti, 2014. "International R&D Spillovers, Absorptive Capacity and Relative Backwardness: A Panel Smooth Transition Regression Model," International Economic Journal, Taylor & Francis Journals, vol. 28(1), pages 137-160, March.
    3. repec:lan:wpaper:2454 is not listed on IDEAS
    4. repec:lan:wpaper:2375 is not listed on IDEAS
    5. Pavlidis Efthymios G & Paya Ivan & Peel David A, 2010. "Specifying Smooth Transition Regression Models in the Presence of Conditional Heteroskedasticity of Unknown Form," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(3), pages 1-40, May.
    6. repec:lan:wpaper:2596 is not listed on IDEAS
    7. repec:lan:wpaper:2373 is not listed on IDEAS
    8. Kadilli, Anjeza & Krishnakumar, Jaya, 2022. "Smooth Transition Simultaneous Equation Models," Journal of Economic Dynamics and Control, Elsevier, vol. 145(C).
    9. Waseem Khadim & Saddam Ilyas & Bilal Mehmood, 2016. "Of Inflation and Growth Nexus in BRIMC Economies," International Journal of Economics and Empirical Research (IJEER), The Economics and Social Development Organization (TESDO), vol. 4(1), pages 32-45, January.
    10. Giulio Cainelli & Andrea Fracasso & Giuseppe Vittucci Marzetti, 2015. "Spatial agglomeration and productivity in Italy: A panel smooth transition regression approach," Papers in Regional Science, Wiley Blackwell, vol. 94, pages 39-67, November.

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    More about this item

    Keywords

    Exact test; Monte Carlo test; Sequential Monte Carlo test; Nonlinear modelling; Panel smooth transition regression;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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