Tests for Long-Run Granger Non-Causality in Cointegrated Systems
AbstractIn this article, 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 covariance matrix associated with the usual Wald-type test by proposing a generalized inverse procedure. A test for the ranks of submatrices of the cointegration matrix and its orthogonal matrix plays a vital role in our procedure. 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 nations. Copyright 2006 The Authors Journal compilation 2006 Blackwell Publishing Ltd.
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Bibliographic InfoArticle provided by Wiley Blackwell in its journal Journal of Time Series Analysis.
Volume (Year): 27 (2006)
Issue (Month): 5 (09)
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Web page: http://www.blackwellpublishing.com/journal.asp?ref=0143-9782
Other versions of this item:
- Taku Yamamoto & Eiji Kurozumi, 2003. "Tests for Long-Run Granger Non-Causality in Cointegrated Systems," Hi-Stat Discussion Paper Series d03-01, Institute of Economic Research, Hitotsubashi University.
- Yamamoto, Taku & Kurozumi, Eiji, 2003. "Tests for Long-Run Granger Non-Causality in Cointegrated Systems," Discussion Papers 2003-12, Graduate School of Economics, Hitotsubashi University.
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
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