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A Graphical Investigation of the Size and Power of the Granger-Causality Tests in Integrated-Cointegrated VAR Systems

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Author Info
Panagiotis Mantalos (Lund University)

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Abstract

The size and power of the Wald, Edgeworth expansion corrected likelihood-ratio statistic (LRE), and bootstrap tests for Granger causality in integrated-cointegrated VAR systems are considered. By using Monte Carlo methods and simple graphical techniques, the p-value plots, and power-size plots, properties of the tests in two different forms, the standard and the Dolado and L ¨ utkepohl (1996) modified form, are studied. Regarding the size of the tests, we found that the Wald performs badly in small- and medium-size samples, but the corrected tests, and especially the LRE for large samples, exhibit good performances. The bootstrap test showed the best performance in almost all situations. When considering the power results, using the size-power curves on a correct-size-adjusted basis, we found that the bootstrap tests have adequate power.

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Publisher Info
Article provided by Berkeley Electronic Press in its journal Studies in Nonlinear Dynamics & Econometrics.

Volume (Year): 4 (2000)
Issue (Month): 1 ()
Pages: 17-33
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Handle: RePEc:bep:sndecm:4:2000:1:17-33

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Related research
Keywords: bootstrap test graphical methods Granger causality integrated-cointegrated (VAR) systems

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.:

  1. Mantalos, Panagiotis & Shukur, Ghazi, 1998. "Size and Power of the Error Correction Model Cointegration Test. A Bootstrap Approach," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 60(2), pages 249-55, May.
  2. Davidson, Russell & MacKinnon, James G, 1998. "Graphical Methods for Investigating the Size and Power of Hypothesis Tests," The Manchester School of Economic & Social Studies, Blackwell Publishing, vol. 66(1), pages 1-26, January.
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  3. Russell Davidson & James G. MacKinnon, 1996. "The Size Distortion of Bootstrap Tests," Working Papers 936, Queen's University, Department of Economics. [Downloadable!]
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  4. Russell Davidson & James G. MacKinnon, 1996. "The Size and Power of Bootstrap Tests," Working Papers 932, Queen's University, Department of Economics. [Downloadable!]
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  5. Horowitz, Joel L., 1994. "Bootstrap-based critical values for the information matrix test," Journal of Econometrics, Elsevier, vol. 61(2), pages 395-411, April. [Downloadable!] (restricted)
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(explanations, 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.)

  1. Abdulnasser Hatemi-J & Ghazi Shukur, 2002. "Multivariate-based causality tests of twin deficits in the US," Journal of Applied Statistics, Taylor and Francis Journals, vol. 29(6), pages 817-824, August. [Downloadable!] (restricted)
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