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Simulation Evidence on Granger Causality in Presence of a Confounding Variable

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  • Zahid ASGHAR

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Abstract

This paper provides simulation evidence on Granger causality between two variables when they are jointly caused by a third variable. Four Data Generating Processes (DGPs) are considered for testing causality by Granger method and two DGPs for testing causality by Toda and Yamamoto (1995) procedure. Our simulation involve three variables but causality has been tested only between two variable and the third variable (the real cause) has been ignored to show that its association which matters in these causality tests. Nevertheless, if we know that there are only two variables in economic dynamics and the true model is known then these causality tests work fine and for this we have carried out bootstrap simulation.

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File URL: http://www.usc.es/economet/reviews/ijaeqs526.pdf
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Bibliographic Info

Article provided by Euro-American Association of Economic Development in its journal International Journal of Applied Econometrics and Quantitative Studies .

Volume (Year): 5 (2008)
Issue (Month): 2 ()
Pages:

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Handle: RePEc:eaa:ijaeqs:v:5:y2008:i:2_6

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Related research

Keywords: Granger Causality; Toda and Yamamoto Procedure; Monte Carlo Simulation; Causation and Association; Bootstrap Simulation;

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  1. Granger, C. W. J., 1988. "Some recent development in a concept of causality," Journal of Econometrics, Elsevier, vol. 39(1-2), pages 199-211.
  2. Hiro Y. Toda & Peter C.B. Phillips, 1991. "Vector Autoregression and Causality," Cowles Foundation Discussion Papers 977, Cowles Foundation for Research in Economics, Yale University.
  3. Toda, Hiro Y. & Yamamoto, Taku, 1995. "Statistical inference in vector autoregressions with possibly integrated processes," Journal of Econometrics, Elsevier, vol. 66(1-2), pages 225-250.
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