Testing for Granger causality in a system of more than two variables
AbstractThis paper provides useful guidelines to practitioners who investigate Granger causality within a system of more than two variables by means of the two-step procedure proposed by Cheung and Ng (Journal of Econometrics, 1996) and modified by Hong (Journal of Econometrics, 2001). First, a theoretical example highlights cases that can mislead the researcher into reporting false causal relations between the variables under scrutiny. Then, the size of the problem is revealed by means of Monte Carlo simulations. Finally, an empirical application that investigates causality-in-mean among six major European stock markets, illustrates the proper procedure to follow for correct inference.
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Bibliographic InfoPaper provided by Department of Economics, University of Macedonia in its series Discussion Paper Series with number 2012_02.
Date of creation: Jan 2012
Date of revision: Jan 2012
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Web page: http://www.uom.gr/index.php?tmima=3
Causality-in-mean; causality-in-variance; misspecification; simulation.;
Find related papers by JEL classification:
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
This paper has been announced in the following NEP Reports:
- NEP-ALL-2012-01-10 (All new papers)
- NEP-ECM-2012-01-10 (Econometrics)
- NEP-ETS-2012-01-10 (Econometric Time Series)
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- Cheung, Yin-Wong & Ng, Lilian K., 1996. "A causality-in-variance test and its application to financial market prices," Journal of Econometrics, Elsevier, Elsevier, vol. 72(1-2), pages 33-48.
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