IDEAS home Printed from
   My bibliography  Save this article

Causality and separability


  • Renault, Eric
  • Triacca, Umberto


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.

Suggested Citation

  • Renault, Eric & Triacca, Umberto, 2015. "Causality and separability," Statistics & Probability Letters, Elsevier, vol. 99(C), pages 1-5.
  • Handle: RePEc:eee:stapro:v:99:y:2015:i:c:p:1-5 DOI: 10.1016/j.spl.2014.12.018

    Download full text from publisher

    File URL:
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    1. Jean-Marie Dufour & Eric Renault, 1998. "Short Run and Long Run Causality in Time Series: Theory," Econometrica, Econometric Society, vol. 66(5), pages 1099-1126, September.
    2. Eichler, Michael, 2007. "Granger causality and path diagrams for multivariate time series," Journal of Econometrics, Elsevier, vol. 137(2), pages 334-353, April.
    3. Florens, J.P. & Mouchart, M. & Rolin, J.M., 1993. "Noncausality and Marginalization of Markov Processes," Econometric Theory, Cambridge University Press, vol. 9(02), pages 241-262, April.
    4. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    5. Sims, Christopher A, 1972. "Money, Income, and Causality," American Economic Review, American Economic Association, vol. 62(4), pages 540-552, September.
    Full references (including those not matched with items on IDEAS)

    More about this item


    Causality; Separability; Time series;


    Access and download statistics


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:stapro:v:99:y:2015:i:c:p:1-5. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.