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Residual-based tests for cointegration with three-regime TAR adjustment

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  • Daiki Maki

    ()

  • Shin-ichi Kitasaka

    ()

Abstract

This paper proposes residual-based tests for cointegration with three-regime threshold autoregressive (TAR) adjustment. We propose Wald-type and $$t$$ t -type tests that have the null hypothesis of linear no cointegration and the alternative of cointegration with three-regime TAR adjustment and also derive the asymptotic distributions. Monte Carlo simulations show that the proposed tests perform better than the Engle–Granger cointegration test and the cointegration test in a two-regime TAR model introduced by Enders and Siklos (J Bus Econ Stat 19:166–176, 2001 ), under cointegration with three-regime TAR adjustment, particularly when the threshold and sample size increase. When we apply these tests to the money demand of the U.S., the proposed tests reject the null of no cointegration whereas other tests do not. Copyright Springer-Verlag Berlin Heidelberg 2015

Suggested Citation

  • Daiki Maki & Shin-ichi Kitasaka, 2015. "Residual-based tests for cointegration with three-regime TAR adjustment," Empirical Economics, Springer, vol. 48(3), pages 1013-1054, May.
  • Handle: RePEc:spr:empeco:v:48:y:2015:i:3:p:1013-1054
    DOI: 10.1007/s00181-014-0822-x
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    References listed on IDEAS

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    Cited by:

    1. Schweikert, Karsten, 2018. "Testing for cointegration with threshold adjustment in the presence of structural breaks," Hohenheim Discussion Papers in Business, Economics and Social Sciences 07-2018, University of Hohenheim, Faculty of Business, Economics and Social Sciences.

    More about this item

    Keywords

    Cointegration; Three-regime TAR model; Money demand; C12; C22;

    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

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