Granger Causality in the Presence of Structural Changes
AbstractWe focus in these paper on Granger shifts or structural breaks. We show that when the assumption of parameter constancy is violated, due to occurrence of structural breaks, Granger causality tests can provide misleading inference about the underlying relationship of causality. We consider a Bayesian model for the detection of structural breaks which can make Granger causality tests ‘robust’ to the presence of structural instabilities in the sample. An application of the method to the Canadian series of GNP and M1 is presented.
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Bibliographic InfoPaper provided by Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES) in its series Discussion Papers (IRES - Institut de Recherches Economiques et Sociales) with number 1995018.
Date of creation: 01 Jan 1995
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Granger causality; switching regression model; structural breaks;
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- Serena Ng & Timothy Vogelsang, 2002.
"Analysis Of Vector Autoregressions In The Presence Of Shifts In Mean,"
Taylor and Francis Journals, vol. 21(3), pages 353-381.
- Serena Ng & Timothy J. Vogelsang, 1997. "Analysis of Vector Autoregressions in the Presence of Shifts in Mean," Boston College Working Papers in Economics 379, Boston College Department of Economics.
- Thierno Balde & Gabriel Rodriguez, 2005. "Finite sample effects of additive outliers on the Granger-causality test with an application to money growth and inflation in Peru," Applied Economics Letters, Taylor and Francis Journals, vol. 12(13), pages 841-844.
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