Causality and separability

Eric Renault and Umberto Triacca

Statistics & Probability Letters, 2015, vol. 99, issue C, 1-5

Abstract: Following Wold (1954), a causal relationship from a vector y of economic variables towards a vector x should be interpreted through a fictive controlled experiment. At least one factor y(i) component of y should have an impact on x when other factors y(j), j≠i, are kept constant. It is arguably a logical weakness of the causality concept when this interpretation breaks down, due to common factors between the components of y. We provide a general separability condition between causal factors to restore their causal interpretation. This general approach can be applied to most of the commonly used causality concepts in modern econometrics.

Keywords: Causality; Separability; Time series (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (1)

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DOI: 10.1016/j.spl.2014.12.018

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