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Application of bootstrap methods in investigation of size of the Granger causality test for integrated VAR systems

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  • Lach, Łukasz

Abstract

This paper examines the size performance of Toda-Yamamoto test for Granger causality in case of trivariate integrated-cointegrated VAR systems and relatively small sample size. 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 increase of sample size and number of bootstrap replications on size performance of Toda-Yamamoto test statistics is also examined. The results of 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 Toda-Yamamoto test. However, in some cases considered bootstrap method also leads to serious size distortion and performs worse than the traditional approach based on distribution.

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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 52285.

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Date of creation: 2010
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Handle: RePEc:pra:mprapa:52285

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Keywords: bootstrap methods;

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  1. Hyllerberg, S. & Engle, R.F. & Granger, C.W.J. & Yoo, B.S., 1988. "Seasonal Integration And Cointegration," Papers, Pennsylvania State - Department of Economics 0-88-2, Pennsylvania State - Department of Economics.
  2. Granger, C. W. J. & Newbold, P., 1974. "Spurious regressions in econometrics," Journal of Econometrics, Elsevier, Elsevier, vol. 2(2), pages 111-120, July.
  3. Granger, C. W. J., 1988. "Some recent development in a concept of causality," Journal of Econometrics, Elsevier, Elsevier, vol. 39(1-2), pages 199-211.
  4. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, Econometric Society, vol. 59(6), pages 1551-80, November.
  5. A. Hatemi-J, 2003. "A new method to choose optimal lag order in stable and unstable VAR models," Applied Economics Letters, Taylor & Francis Journals, Taylor & Francis Journals, vol. 10(3), pages 135-137.
  6. Mantalos Panagiotis, 2000. "A Graphical Investigation of the Size and Power of the Granger-Causality Tests in Integrated-Cointegrated VAR Systems," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, De Gruyter, vol. 4(1), pages 1-18, April.
  7. Phillips, P.C.B., 1986. "Understanding spurious regressions in econometrics," Journal of Econometrics, Elsevier, Elsevier, vol. 33(3), pages 311-340, December.
  8. Horowitz, Joel L., 1994. "Bootstrap-based critical values for the information matrix test," Journal of Econometrics, Elsevier, Elsevier, vol. 61(2), pages 395-411, April.
  9. R. Scott Hacker & Abdulnasser Hatemi-J, 2006. "Tests for causality between integrated variables using asymptotic and bootstrap distributions: theory and application," Applied Economics, Taylor & Francis Journals, Taylor & Francis Journals, vol. 38(13), pages 1489-1500.
  10. Engle, Robert F & Granger, Clive W J, 1987. "Co-integration and Error Correction: Representation, Estimation, and Testing," Econometrica, Econometric Society, Econometric Society, vol. 55(2), pages 251-76, March.
  11. MacKinnon, James G, 1992. "Model Specification Tests and Artificial Regressions," Journal of Economic Literature, American Economic Association, American Economic Association, vol. 30(1), pages 102-46, March.
  12. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, Econometric Society, vol. 37(3), pages 424-38, July.
  13. Toda, Hiro Y. & Yamamoto, Taku, 1995. "Statistical inference in vector autoregressions with possibly integrated processes," Journal of Econometrics, Elsevier, Elsevier, vol. 66(1-2), pages 225-250.
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Cited by:
  1. Gurgul, Henryk & Lach, lukasz, 2011. "The role of coal consumption in the economic growth of the Polish economy in transition," Energy Policy, Elsevier, Elsevier, vol. 39(4), pages 2088-2099, April.
  2. 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, Wroclaw University of Technology, Institute of Organization and Management, vol. 3, pages 5-29.
  3. Lach, Łukasz, 2011. "Impact of hard coal usage for metal production on economic growth of Poland," MPRA Paper 52282, University Library of Munich, Germany.
  4. Gurgul, Henryk & Lach, Lukasz, 2011. "The electricity consumption versus economic growth of the Polish economy," MPRA Paper 35785, University Library of Munich, Germany.
  5. Alessandro Attanasio & Maurizio Maravalle & Giulia Fioravanti, 2012. "Examining Granger causality between atmospheric parameters and radon," Natural Hazards, International Society for the Prevention and Mitigation of Natural Hazards, International Society for the Prevention and Mitigation of Natural Hazards, vol. 62(2), pages 723-731, June.
  6. Di Iorio, Francesca & Triacca, Umberto, 2011. "Testing for non-causality by using the Autoregressive Metric," MPRA Paper 29637, University Library of Munich, Germany.
  7. Lach, Łukasz, 2010. "Fixed capital and long run economic growth: evidence from Poland," MPRA Paper 52280, University Library of Munich, Germany.
  8. Henryk Gurgul & Lukasz Lach, 2011. "The interdependence between energy consumption and economic growth in the Polish economy in the last decade," Managerial Economics, AGH University of Science and Technology, Faculty of Management, AGH University of Science and Technology, Faculty of Management, vol. 9, pages 25-48.
  9. Talha Yalta, A. & Cakar, Hatice, 2012. "Energy consumption and economic growth in China: A reconciliation," Energy Policy, Elsevier, Elsevier, vol. 41(C), pages 666-675.
  10. Di Iorio, Francesca & Triacca, Umberto, 2013. "Testing for Granger non-causality using the autoregressive metric," Economic Modelling, Elsevier, Elsevier, vol. 33(C), pages 120-125.

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