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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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  • Lukasz Lach

    (University of Science and Technology, Poland)

Abstract

This 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.

Suggested Citation

  • Lukasz Lach, 2010. "Application of Bootstrap Methods in Investigation of Size of the Granger Causality Test for Integrated VAR Systems," Managing Global Transitions, University of Primorska, Faculty of Management Koper, vol. 8(2), pages 167-186.
  • Handle: RePEc:mgt:youmgt:v:8:y:2010:i:2:p:167-186
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    References listed on IDEAS

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    Cited by:

    1. Gurgul, Henryk & Lach, Łukasz, 2012. "The electricity consumption versus economic growth of the Polish economy," Energy Economics, Elsevier, vol. 34(2), pages 500-510.
    2. Di Iorio, Francesca & Triacca, Umberto, 2011. "Testing for non-causality by using the Autoregressive Metric," MPRA Paper 29637, University Library of Munich, Germany.
    3. 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.
    4. Lukasz Lach, 2011. "Impact of hard coal usage for metal production on economic growth of Poland," Managerial Economics, AGH University of Science and Technology, Faculty of Management, vol. 9, pages 103-120.
    5. Lach, Łukasz, 2010. "Fixed capital and long run economic growth: evidence from Poland," MPRA Paper 52280, University Library of Munich, Germany.
    6. Wesseh, Presley K. & Zoumara, Babette, 2012. "Causal independence between energy consumption and economic growth in Liberia: Evidence from a non-parametric bootstrapped causality test," Energy Policy, Elsevier, vol. 50(C), pages 518-527.
    7. Lin, Boqiang & Wesseh Jr., Presley K., 2014. "Energy consumption and economic growth in South Africa reexamined: A nonparametric testing apporach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 40(C), pages 840-850.
    8. Talha Yalta, A. & Cakar, Hatice, 2012. "Energy consumption and economic growth in China: A reconciliation," Energy Policy, Elsevier, vol. 41(C), pages 666-675.
    9. 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, vol. 9, pages 25-48.
    10. Gbatu, Abimelech Paye & Wang, Zhen & Wesseh, Presley K. & Tutdel, Isaac Yak Repha, 2017. "The impacts of oil price shocks on small oil-importing economies: Time series evidence for Liberia," Energy, Elsevier, vol. 139(C), pages 975-990.
    11. Alessandro Attanasio & Maurizio Maravalle & Giulia Fioravanti, 2012. "Examining Granger causality between atmospheric parameters and radon," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 62(2), pages 723-731, June.
    12. 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.
    13. Yıldırım, Ertugrul & Sukruoglu, Deniz & Aslan, Alper, 2014. "Energy consumption and economic growth in the next 11 countries: The bootstrapped autoregressive metric causality approach," Energy Economics, Elsevier, vol. 44(C), pages 14-21.
    14. Di Iorio, Francesca & Triacca, Umberto, 2013. "Testing for Granger non-causality using the autoregressive metric," Economic Modelling, Elsevier, vol. 33(C), pages 120-125.

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    More about this item

    Keywords

    bootstrap methods; simulation; Granger causality; bootstrap methods; simulation; Granger causality; VAR models models;
    All these keywords.

    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

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