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The Relation of Different Concepts of Causality in Econometrics (2006)

Abstract
Granger and Sims non-causality (GSNC) are compared to non-causality based on concepts popular in the microeconometrics and programme evaluation literature (potential outcome non-causality, PONC). GSNC is defined as a set of restrictions on joint distributions of random variables with observable sample counterparts, whereas PONC combines restrictions on partially unobservable variables (potential outcomes) with different identifying assumptions that relate potential to observable outcomes. Based on a dynamic model of potential outcomes, we find that in general neither of the concepts implies each other without further assumptions. However, identifying assumptions of the sequential selection on observable type provide the link between those concepts, such that GSNC implies PONC, and vice versa.

Publication details
Download http://www.alexandria.unisg.ch/EXPORT/DL/34650.pdf
Repository University of St.Gallen - Alexandria Repository (Switzerland)
Keywords Granger causality, Sims causality, Rubin causality, potential outcome model, dynamic treatments
Type Text
Language Englisch

Cited publications (6)
Sequential Matching Estimation of Dynamic Causal Models (2004)
Identification of Effects of Dynamic Treatments by Sequential Conditional Independence Assumptions (2002)
Identification of Dynamic Treatment Effects by Instrumental Variables (2002)
The Logic of Counterfactuals in Causal Inference (Discussion of `Causal Inference without Counterfactuals' by A.P. Dawid) (2000)
Investigating Causal Relations by Econometric Models and Cross-Spectral Methods.
Inference and causality in economic time series models