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Granger Causality and Dynamic Structural Systems

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  • Halbert White
  • Xun Lu

Abstract

Using a generally applicable dynamic structural system of equations, we give natural definitions of direct and total structural causality applicable to both structural vector autoregressions (VARs) and recursive structures representing time-series natural experiments. These concepts enable us to forge a previously missing link between Granger (G-)causality and structural causality by showing that, given a corresponding conditional form of exogeneity, G-causality holds if and only if a corresponding form of structural causality holds. We introduce a variety of structurally informative extensions of G-causality and provide their structural characterizations. Of importance for applications is the structural characterization of finite-order G-causality, which forms the basis for most empirical work. We show that conditional exogeneity is necessary for valid structural inference and prove that, in the absence of structural causality, conditional exogeneity is equivalent to G noncausality. These characterizations hold for both structural VARs and natural experiments. We propose practical new G-causality and conditional exogeneity tests and describe their use in testing for structural causality. We illustrate with studies of oil and gasoline prices, monetary policy and industrial production, and stock returns and macroeconomic announcements. Copyright The Author 2010. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org, Oxford University Press.

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Bibliographic Info

Article provided by Society for Financial Econometrics in its journal Journal of Financial Econometrics.

Volume (Year): 8 (2010)
Issue (Month): 2 (spring)
Pages: 193-243

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Handle: RePEc:oup:jfinec:v:8:y:2010:i:2:p:193-243

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Cited by:
  1. White, Halbert & Chalak, Karim, 2010. "Testing a conditional form of exogeneity," Economics Letters, Elsevier, Elsevier, vol. 109(2), pages 88-90, November.
  2. Lorenzo Frattarolo & Dominique Guegan, 2013. "Empirical Projected Copula Process and Conditional Independence an Extended Version," Documents de travail du Centre d'Economie de la Sorbonne, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne 13068, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
  3. Majid M. Al-Sadoon, 2013. "Geometric and long run aspects of Granger causality," Economics Working Papers, Department of Economics and Business, Universitat Pompeu Fabra 1356, Department of Economics and Business, Universitat Pompeu Fabra.
  4. Lu, Xun & White, Halbert, 2014. "Robustness checks and robustness tests in applied economics," Journal of Econometrics, Elsevier, Elsevier, vol. 178(P1), pages 194-206.
  5. White, Halbert & Pettenuzzo, Davide, 2014. "Granger causality, exogeneity, cointegration, and economic policy analysis," Journal of Econometrics, Elsevier, Elsevier, vol. 178(P2), pages 316-330.
  6. Blake LeBaron, 2013. "Heterogeneous Agents and Long Horizon Features of Asset Prices," Working Papers, Brandeis University, Department of Economics and International Businesss School 63, Brandeis University, Department of Economics and International Businesss School, revised Sep 2013.

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