Tests for Long-Run Granger Non-Causality in Cointegrated Systems
In this paper, we propose a new approach to test the hypothesis of long-run Granger non-causality in cointegrated systems. We circumvent the problem of singularity of the variance-covariance matrix associated with the usual Wald type test by proposing a generalized inverse procedure, and an alternative simple procedure which can be approximated by a suitable chi-square distribution. A test for the ranks of submatrices of the cointegration matrix and its orthogonal matrix plays a vital role in the former. The relevant small sample experiments indicate that the proposed method performs reasonably well in finite samples. As empirical applications, we examine long-run causal relations among long-term interest rates of three and five nations.
|Date of creation:||Jun 2003|
|Note:||February 2001; First Revision, February 2002; Second Revision, February 2003; Third Revision, June 2003|
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- 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.