Learning Causal Relations in Multivariate Time Series Data
Applying a probabilistic causal approach, we define a class of time series causal models (TSCM) based on stationary Bayesian networks. A TSCM can be seen as a structural VAR identified by the causal relations among the variables. We classify TSCMs into observationally equivalent classes by providing a necessary and sufficient condition for the observational equivalence. Applying an automated learning algorithm, we are able to consistently identify the data-generating causal structure up to the class of observational equivalence. In this way we can characterize the empirical testable causal orders among variables based on their observed time series data. It is shown that while an unconstrained VAR model does not imply any causal orders in the variables, a TSCM that contains some empirically testable causal orders implies a restricted SVAR model. We also discuss the relation between the probabilistic causal concept presented in TSCMs and the concept of Granger causality. It is demonstrated in an application example that this methodology can be used to construct structural equations with causal interpretations.
Volume (Year): 1 (2007)
Issue (Month): ()
|Contact details of provider:|| Postal: Kiellinie 66, D-24105 Kiel|
Phone: +49 431 8814-1
Fax: +49 431 8814528
Web page: http://www.economics-ejournal.org/
More information through EDIRC
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Ellen R. Rissman, 1995. "Sectoral wage growth and inflation," Economic Perspectives, Federal Reserve Bank of Chicago, issue Jul, pages 15-28.
- Glymour, Clark & Spirtes, Peter, 1988. "Latent variables, causal models and overidentifying constraints," Journal of Econometrics, Elsevier, vol. 39(1-2), pages 175-198.
- Douglas Staiger & James H. Stock & Mark W. Watson, 1997. "The NAIRU, Unemployment and Monetary Policy," Journal of Economic Perspectives, American Economic Association, vol. 11(1), pages 33-49, Winter.
- Vincent Hogan, 1998. "Explaining the Recent Behavior of Inflation and Unemployment in the United States," IMF Working Papers 98/145, International Monetary Fund.
- Daniel Aaronson, 2001. "Price Pass-Through And The Minimum Wage," The Review of Economics and Statistics, MIT Press, vol. 83(1), pages 158-169, February.
- Eichler, Michael, 2007. "Granger causality and path diagrams for multivariate time series," Journal of Econometrics, Elsevier, vol. 137(2), pages 334-353, April.
- Peter Spirtes & Clark Glymour & Richard Scheines, 2001. "Causation, Prediction, and Search, 2nd Edition," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262194406, July.
- Hoover, Kevin D., 2005. "Automatic Inference Of The Contemporaneous Causal Order Of A System Of Equations," Econometric Theory, Cambridge University Press, vol. 21(01), pages 69-77, February.
- Jonsson, Magnus & Palmqvist, Stefan, 2004. "Do Higher Wages Cause Inflation?," Working Paper Series 159, Sveriges Riksbank (Central Bank of Sweden).
- Pu Chen & Carl Chiarella & Peter Flaschel & Willi Semmler, 2006. "Keynesian Macrodynamics and the Phillips Curve. An Estimated Baseline Macromodel for the U.S. Economy," Working Paper Series 147, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
When requesting a correction, please mention this item's handle: RePEc:zbw:ifweej:6175. 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: (ZBW - German National Library of Economics)
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 references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link 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 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.