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The Cointegrated VAR Model with Deterministic Structural Breaks

Author

Listed:
  • Emilia Gosińska

    (Chair of Econometric Models and Forecasts, Faculty of Economics and Sociology, University of Łódź)

  • Aleksander Welfe

    (Chair of Econometric Models and Forecasts, Faculty of Economics and Sociology, University of Łódź)

Abstract

The presence of a binary variable in the cointegrated VAR (CVAR) model is most often interpreted as the structural break affecting the data generating process. It is proved in the paper that to enjoy this interpretation the binary variable must appear simultaneously inside and outside the cointegration space. In order to test for the break we advocate to employ the Wald statistic, however, its critical values and the power had to be simulated separately for the possible change of the constant, the trend, and both. The experiments were designed for different sizes of the cointegrating space, number of variables, the span of the break, normally and t-distributed errors. It is shown that the power of the test depends mostly on the magnitude of the break and the sample size while other factors are of secondary importance. In order to test for the break at unknown period the supWald statistic was proposed.

Suggested Citation

  • Emilia Gosińska & Aleksander Welfe, 2022. "The Cointegrated VAR Model with Deterministic Structural Breaks," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 14(3), pages 335-350, September.
    • Handle: RePEc:psc:journl:v:14:y:2022:i:3:p:335-350
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    structural breaks; cointegrated VAR; WALD test; hypothesis testing;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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