Non-Causality Due to Included Variables

Umberto Triacca
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Umberto Triacca: Department of Information Engineering, Computer Science and Mathematics University of L’Aquila, 67100 Coppito, Italy

Econometrics, 2017, vol. 5, issue 4, 1-4

Abstract: The contribution of this paper is to investigate a particular form of lack of invariance of causality statements to changes in the conditioning information sets. Consider a discrete-time three-dimensional stochastic process z = ( x , y 1 , y 2 ) ′ . We want to study causality relationships between the variables in y = ( y 1 , y 2 ) ′ and x . Suppose that in a bivariate framework, we find that y 1 Granger causes x and y 2 Granger causes x , but these relationships vanish when the analysis is conducted in a trivariate framework. Thus, the causal links, established in a bivariate setting, seem to be spurious. Is this conclusion always correct? In this note, we show that the causal links, in the bivariate framework, might well not be ‘genuinely’ spurious: they could be reflecting causality from the vector y to x . Paradoxically, in this case, it is the non-causality in trivariate system that is misleading.

Keywords: Granger causality; Hilbert spaces; time series (search for similar items in EconPapers)
JEL-codes: B23 C C00 C01 C1 C2 C3 C4 C5 C8 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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