Application of Bootstrap Methods in Investigation of Size of the Granger Causality Test for Integrated VAR Systems
AbstractThis paper examines the size performance of the Toda-Yamamoto test for Granger causality in the case of trivariate integrated and cointegrated VAR systems. The standard asymptotic distribution theory and the residual-based bootstrap approach are applied. A variety of types of distribution of error term is considered. The impact of misspecification of initial parameters as well as the influence of an increase in sample size and number of bootstrap replications on size performance of Toda-Yamamoto test statistics is also examined. The results of the conducted simulation study confirm that standard asymptotic distribution theory may often cause significant over-rejection. Application of bootstrap methods usually leads to improvement of size performance of the Toda-Yamamoto test. However, in some cases the considered bootstrap method also leads to serious size distortion and performs worse than the traditional approach based on ÷2 distribution.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoArticle provided by University of Primorska, Faculty of Management Koper in its journal Managing Global Transitions.
Volume (Year): 8 (2010)
Issue (Month): 2 ()
Find related papers by JEL classification:
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
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.:
- A. Hatemi-J, 2003. "A new method to choose optimal lag order in stable and unstable VAR models," Applied Economics Letters, Taylor and Francis Journals, vol. 10(3), pages 135-137.
- Granger, C. W. J., 1988. "Some recent development in a concept of causality," Journal of Econometrics, Elsevier, vol. 39(1-2), pages 199-211.
- Gurgul, Henryk & Lach, Lukasz, 2011.
"The electricity consumption versus economic growth of the Polish economy,"
35785, University Library of Munich, Germany.
- Gurgul, Henryk & Lach, Łukasz, 2012. "The electricity consumption versus economic growth of the Polish economy," Energy Economics, Elsevier, vol. 34(2), pages 500-510.
- A. Talha Yalta & Hatice Cakar, 2012.
"Energy Consumption and Economic Growth in China: A Reconciliation,"
1202, TOBB University of Economics and Technology, Department of Economics.
- Talha Yalta, A. & Cakar, Hatice, 2012. "Energy consumption and economic growth in China: A reconciliation," Energy Policy, Elsevier, vol. 41(C), pages 666-675.
- Lukasz Lach & Henryk Gurgul, 2010. "International trade and economic growth in the Polish economy," Operations Research and Decisions, Wroclaw University of Technology, Institute of Organization and Management, vol. 3, pages 5-29.
- Gurgul, Henryk & Lach, lukasz, 2011. "The role of coal consumption in the economic growth of the Polish economy in transition," Energy Policy, Elsevier, vol. 39(4), pages 2088-2099, April.
- Di Iorio, Francesca & Triacca, Umberto, 2011. "Testing for non-causality by using the Autoregressive Metric," MPRA Paper 29637, University Library of Munich, Germany.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Alen Jezovnik).
If references are entirely missing, you can add them using this form.