Looking behind Granger causality

Chen, Pu and Hsiao, Chih-Ying (2010): Looking behind Granger causality. Unpublished.

Abstract

Granger causality as a popular concept in time series analysis is widely applied in empirical research. The interpretation of Granger causality tests in a cause-effect context is, however, often unclear or even controversial, so that the causality label has faded away. Textbooks carefully warn that Granger causality does not imply true causality and preferably refer the Granger causality test to a forecasting technique. Applying theory of inferred causation, we develop in this paper a method to uncover causal structures behind Granger causality. In this way we re-substantialize the causal attribution in Granger causality through providing an causal explanation to the conditional dependence manifested in Granger causality.

• Item Type: MPRA Paper
• Language: English
• Keywords: Granger Causality; Time Series Causal Model; Graphical Model
• Subjects: C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods: General; E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles

References

Chen, P. (2010). A time series causal model. Working paper, mimeo Melbourne University.

Chen, P. and Flaschel, P. (2006). Measuring the interaction of wage and price Phillips curves for the U.S. economy. Studies in Nonlinear Dynamics and Econometrics, 10, No. 4:Article 2.

Chen, P. and Hsiao, C. (2007). Learning causal relations in multivariate time sereis data. Economics: The Open-Access, Open-Accessment E-Journal , 1, 2007-11.

Eichler, M. (2007). Granger causality and path diagrams for multivariate time series. Journal of Econometrics,137:334–353.

Flaschel, P. and Krolzig, H. (2003). Wage and price Phillips curves. An empirical analysis of destabilizing wage-price spirals. Center of Empirical Macroeconomics, Bielefeld University.

Granger, C. W. J. (1980). Testing for causality: A personal viewpoint. Journal of Economic Dynamics and Control , 2:329–352.

Hendry, D. (1995). Dynamic Econometrics. Oxfort University Press, 1st edition.

Hoover, K. (2005). Automatic inference of the contemporaneous causal order of a system of equations. Econometric Theory, 21:69–77. — (2008). Causality in economics and econometrics. The New Palgrave Dictionary of Economics Online, Second Edition. Steven N. Durlauf and Lawrence E. Blume Eds. Palgrave Macmillan. — (2010). Economic theory and causal inference. in HANDBOOK OF THE PHILOSPHY OF ECONOMICS, Uskali M¨aki, ed., Forthcoming.

Kalisch, M. and Buehlmann, P. (2007). Estimating high-dimensional directed acyclic graphs with the pc-algorithm. Journal of Machine Learning Research, 8:613–636.

Pearl, J. (2000). Causality. Cambridge University Press, 1st edition.

Pearl, J. and Verma, T. (1991). A theory of inferred causation. In J.A. Allen,

R. Fikes, and E. Sandewall(Eds.), Principles of Knowledge Representation and Rea- soning: Procedings of the 2nd International Conference, San Mateo, CA:Morgan Kaufmann, pages 441–452.

Reichenbach, H. (1956). The Direction of Time. Berkeley, University of Los Angles Press.

Robins, J., Scheines, R., Sprites, P., and Wasserman, L. (2003). Uniform consistency in causal inference. Biometrika, 90:941–515.

Spirtes, P., Glymour, C., and Scheines, R. (2000). Causation, Prediction and Search. Springer-Verlag, New York / Berlin / London / Heidelberg / Paris, 2nd edition.

Wold, H. (1954). Causality and econometrics. Econometrica, 22:162–177.