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The Granger Non-Causality Test in Cointegrated Vector Autoregressions

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  • Hiroaki Chigira
  • Taku Yamamoto

Abstract

In general, Wald tests for the Granger non-causality in vector autoregressive (VAR) process are known to have non-standard asymptotic properties for cointegrated systems. However, that may have standard asymptotic properties depending on the rank of the submatrix of cointegration. In this paper, we propose a procedure for conducting Granger non-causality tests that are based on discrimination of these asymptotic properties. This paper also investigate the finite sample performance of our testing procedure, and compare the testing procedure with conventional causality tests in levels VAR’s.

Suggested Citation

  • Hiroaki Chigira & Taku Yamamoto, 2003. "The Granger Non-Causality Test in Cointegrated Vector Autoregressions," Hi-Stat Discussion Paper Series d03-07, Institute of Economic Research, Hitotsubashi University.
    • Handle: RePEc:hst:hstdps:d03-07
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    File URL: http://hi-stat.ier.hit-u.ac.jp/research/discussion/2003/pdf/D03-07.pdf
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    References listed on IDEAS

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    1. Zivot, Eric & Andrews, Donald W K, 2002. "Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 25-44, January.
    2. Osterwald-Lenum, Michael, 1992. "A Note with Quantiles of the Asymptotic Distribution of the Maximum Likelihood Cointegration Rank Test Statistics," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 54(3), pages 461-472, August.
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    Cited by:

    1. Yiannis Kamarianakis & Vagelis Kaslis, 2005. "Geographical competition-complementarity relationships between Greek regional economies," ERSA conference papers ersa05p552, European Regional Science Association.

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    More about this item

    Keywords

    Vector autoregression; Cointegration; Granger causality; Hypothesis testing;
    All these keywords.

    JEL classification:

    • 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
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General

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