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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.

Suggested Citation

  • Halbert White & Xun Lu, 2010. "Granger Causality and Dynamic Structural Systems," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 8(2), pages 193-243, spring.
  • Handle: RePEc:oup:jfinec:v:8:y:2010:i:2:p:193-243
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    File URL: http://hdl.handle.net/10.1093/jjfinec/nbq006
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    Citations

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    Cited by:

    1. Majid M. Al-Sadoon, 2016. "The Linear Systems Approach to Linear Rational Expectations Models," Working Papers 875, Barcelona Graduate School of Economics.
    2. Matthieu Droumaguet & Anders Warne & Tomasz Wozniak, 2015. "Granger Causality and Regime Inference in Bayesian Markov-Switching VARs," Department of Economics - Working Papers Series 1191, The University of Melbourne.
    3. Lu, Xun & White, Halbert, 2014. "Robustness checks and robustness tests in applied economics," Journal of Econometrics, Elsevier, vol. 178(P1), pages 194-206.
    4. Majid M. Al-Sadoon, 2015. "Testing subspace Granger causality," Economics Working Papers 1495, Department of Economics and Business, Universitat Pompeu Fabra.
    5. White, Halbert & Chalak, Karim, 2010. "Testing a conditional form of exogeneity," Economics Letters, Elsevier, vol. 109(2), pages 88-90, November.
    6. Al-Sadoon, Majid M., 2014. "Geometric and long run aspects of Granger causality," Journal of Econometrics, Elsevier, vol. 178(P3), pages 558-568.
    7. Lu, Xun & White, Halbert, 2014. "Testing for separability in structural equations," Journal of Econometrics, Elsevier, vol. 182(1), pages 14-26.
    8. Lorenzo Frattarolo & Dominique Guegan, 2013. "Empirical Projected Copula Process and Conditional Independence An Extended Version," Post-Print halshs-00881185, HAL.
    9. 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 13068, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    10. White, Halbert & Pettenuzzo, Davide, 2014. "Granger causality, exogeneity, cointegration, and economic policy analysis," Journal of Econometrics, Elsevier, vol. 178(P2), pages 316-330.
    11. Blake LeBaron, 2013. "Heterogeneous Agents and Long Horizon Features of Asset Prices," Working Papers 63, Brandeis University, Department of Economics and International Businesss School, revised Sep 2013.

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