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Monte Carlo Evidence On Cointegration And Causation

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  • Zapata, Hector O.
  • Rambaldi, Alicia N.

Abstract

The small sample performance of Granger causality tests under different model dimensions, degree of cointegration, direction of causality, and system stability are presented. Two tests based on maximum likelihood estimation of error-correction models (LR and WALD) are compared to a Wald test based on multivariate least squares estimation of a modified VAR (MWALD). In large samples all test statistics perform well in terms of size and power. For smaller samples, the LR and WALD tests perform better than the MWALD test. Overall, the LR test outperforms the other two in terms of size and power in small samples.

Suggested Citation

  • Zapata, Hector O. & Rambaldi, Alicia N., 1996. "Monte Carlo Evidence On Cointegration And Causation," Staff Papers 31690, Louisiana State University, Department of Agricultural Economics and Agribusiness.
    • Handle: RePEc:ags:lsustp:31690
    DOI: 10.22004/ag.econ.31690
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    1. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    2. Johansen, Soren & Juselius, Katarina, 1990. "Maximum Likelihood Estimation and Inference on Cointegration--With Applications to the Demand for Money," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 52(2), pages 169-210, May.
    3. Mosconi, Rocco & Giannini, Carlo, 1992. "Non-causality in Cointegrated Systems: Representation Estimation and Testing," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 54(3), pages 399-417, August.
    4. Lutkepohl, Helmut & Reimers, Hans-Eggert, 1992. "Granger-causality in cointegrated VAR processes The case of the term structure," Economics Letters, Elsevier, vol. 40(3), pages 263-268, November.
    5. Granger, C. W. J., 1988. "Some recent development in a concept of causality," Journal of Econometrics, Elsevier, vol. 39(1-2), pages 199-211.
    6. Gonzalo, Jesus, 1994. "Five alternative methods of estimating long-run equilibrium relationships," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 203-233.
    7. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
    8. Johansen, Søren & Juselius, Katarina, 1992. "Testing structural hypotheses in a multivariate cointegration analysis of the PPP and the UIP for UK," Journal of Econometrics, Elsevier, vol. 53(1-3), pages 211-244.
    9. Toda, Hiro Y. & Yamamoto, Taku, 1995. "Statistical inference in vector autoregressions with possibly integrated processes," Journal of Econometrics, Elsevier, vol. 66(1-2), pages 225-250.
    10. Lutkepohl, Helmut & Reimers, Hans-Eggert, 1992. "Impulse response analysis of cointegrated systems," Journal of Economic Dynamics and Control, Elsevier, vol. 16(1), pages 53-78, January.
    11. Spanos,Aris, 1986. "Statistical Foundations of Econometric Modelling," Cambridge Books, Cambridge University Press, number 9780521269124, December.
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