We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Non-Causality Due to Included Variables.
- Authors
Triacca, Umberto
- 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, y1, y2)'. We want to study causality relationships between the variables in y = (y1, y2)' and x. Suppose that in a bivariate framework, we find that y1 Granger causes x and y2 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.
- Subjects
TIME series analysis; MATHEMATICAL variables; HILBERT space; FALSE precision (Statistics); GRANGER causality test
- Publication
Econometrics (2225-1146), 2017, Vol 5, Issue 4, p46
- ISSN
2225-1146
- Publication type
Article
- DOI
10.3390/econometrics5040046