A simple investigation of the Granger-causality test in integrated-cointegrated VAR systems

• Published in: Journal of applied statistics Vol. 27; no. 8; pp. 1021 - 1031
• Main Authors: Shukur, Ghazi, Mantalos, Panagiotis
• Format: Journal Article
• Language: English
• Published: Abingdon Taylor & Francis Group 01.11.2000; Taylor and Francis Journals; Taylor & Francis Ltd
• Series: Journal of Applied Statistics
• Subjects: Causality; Hypotheses; Lagrange multiplier; Monte Carlo simulation; Power; Statistics; Statistics/Econometrics; Statistik; Test methods
• ISSN: 0266-4763; 1360-0532; 1360-0532
• DOI: 10.1080/02664760050173346

The size and power of various generalization tests for the Granger-causality in integrated-cointegrated VAR systems are considered. By using Monte Carlo methods, properties of eight versions of the test are studied in two different forms, the standard form and the modified form by Dolado & Lütkepohl (1996) in a study confined to properties of the Wald test only. In their study as well as in ours, both the standard and the modified Wald tests are shown to perform badly especially in small samples. We find, however, that the corrected LR tests exhibit correct size even in small samples. The power of the test is higher when the true VAR(2) model is estimated, and the modified test loses information by estimating the extra coefficients. The same is true when considering the power results in the VAR(3) model, and the power of the tests is somewhat lower than those in the VAR(2).