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Finding Cointegration Rank in High Dimensional Systems Using the Johansen Test: An Illustration Using Data Based Monte Carlo Simulations

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  • Ho, Mun S
  • Sorensen, Bent E

Abstract

The authors examine the ability of the Johansen (1991) test to estimate the number of unit roots in high dimensional systems. They use data based Monte Carlo methods as a simple means of evaluating the validity of inference using asymptotic critical values. These simulations for a typical annual post-World War II dataset illustrate how the estimated number of unit roots change in a nonmonotone fashion with the dimension of the system, and with the number of lags in the VAR representation. The authors find that overparametrization in high dimensions is as bad as underparametrization. The Bayes information criteria outperforms the Akaike information criteria in their setup. Copyright 1996 by MIT Press.

Suggested Citation

  • Ho, Mun S & Sorensen, Bent E, 1996. "Finding Cointegration Rank in High Dimensional Systems Using the Johansen Test: An Illustration Using Data Based Monte Carlo Simulations," The Review of Economics and Statistics, MIT Press, vol. 78(4), pages 726-732, November.
    • Handle: RePEc:tpr:restat:v:78:y:1996:i:4:p:726-32
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    References listed on IDEAS

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    11. Shintani, Mototsugu, 2001. "A simple cointegrating rank test without vector autoregression," Journal of Econometrics, Elsevier, vol. 105(2), pages 337-362, December.
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    14. Andrea Carriero & George Kapetanios & Massimiliano Marcellino, 2010. "Forecasting Government Bond Yields with Large Bayesian VARs," Working Papers 662, Queen Mary University of London, School of Economics and Finance.
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    16. Haug, Alfred A., 1999. "Testing linear restrictions on cointegration vectors: Sizes and powers of Wald tests in finite samples," Technical Reports 1999,04, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
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    22. Maite Alguacil & Ana Cuadros & Vicente Orts, 2004. "Does saving really matter for growth? Mexico (1970-2000)," Journal of International Development, John Wiley & Sons, Ltd., vol. 16(2), pages 281-290.
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    25. Mehrotra, Shiv N. & Kant, Shashi, 2009. "Use of composite forest commodity price indices for cointegration analysis," Journal of Forest Economics, Elsevier, vol. 15(4), pages 237-260, December.

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