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Comparison of the Anderson-Rubin test for overidentification and the Johansen test for cointegration

Author

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  • Hoogerheide, L.F.
  • van Dijk, H.K.

Abstract

In this paper we discuss the similarity between the Anderson-Rubin test for overidentification in a Simultaneous Equations Model and the Johansen test for cointegration in a Vector Autoregressive model. The similar structure of the two models is shown to be important in this respect. An alternative procedure for computing the Anderson-Rubin test is given, which appears to be faster than the conventional method. The derivation of the likelihood ratio test for the hypothesis of reduced rank is given for the general case. Both the Anderson-Rubin test and the Johansen test are shown to be monotonically increasing functions of the singular values of a scaled version of the unrestricted least-squares estimator of the matrix upon which the rank restriction is imposed.

Suggested Citation

  • Hoogerheide, L.F. & van Dijk, H.K., 2001. "Comparison of the Anderson-Rubin test for overidentification and the Johansen test for cointegration," Econometric Institute Research Papers EI 2001-04, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    • Handle: RePEc:ems:eureir:1669
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    Citations

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    Cited by:

    1. Andrea Carriero & George Kapetanios & Massimiliano Marcellino, 2011. "Forecasting large datasets with Bayesian reduced rank multivariate models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(5), pages 735-761, August.
    2. van Dijk, H.K., 2002. "On Bayesian structural inference in a simultaneous equation model," Econometric Institute Research Papers EI 2002-10, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    3. Hoogerheide, Lennart F. & Kaashoek, Johan F. & van Dijk, Herman K., 2007. "On the shape of posterior densities and credible sets in instrumental variable regression models with reduced rank: An application of flexible sampling methods using neural networks," Journal of Econometrics, Elsevier, vol. 139(1), pages 154-180, July.
    4. de Pooter, M.D. & Ravazzolo, F. & Segers, R. & van Dijk, H.K., 2008. "Bayesian near-boundary analysis in basic macroeconomic time series models," Econometric Institute Research Papers EI 2008-13, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

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