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

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Author Info
L.F. Hoogerheide ()
H.K. Van Dijk () (FEW-Econometrie en besliskunde)

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Abstract

Abstract EI 2001-04: 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. Keywords: Likelihood ratio test, Overidentification, Cointegration, Singular value decomposition.

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Paper provided by Erasmus University Rotterdam, Econometric Institute in its series Econometric Institute Report with number 212.

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Date of creation: 2001
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Handle: RePEc:dgr:eureir:2001212

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Related research
Keywords: likelihood ratio test overidentification cointegration singular value decomposition;

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  1. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-80, November. [Downloadable!] (restricted)
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  1. HOOGERHEIDE, Lennart F. & KAASHOEK, Johan F. & VAN DIJK, Herman K., 2005. "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," CORE Discussion Papers 2005029, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE). [Downloadable!]
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  2. Andrea Carriero & George Kapetanios & Massimiliano Marcellino, 2009. "Forecasting Large Datasets with Bayesian Reduced Rank Multivariate Models," Economics Working Papers ECO2009/31, European University Institute. [Downloadable!]
  3. H.K. Van Dijk, 2002. "On Bayesian structural inference in a simultaneous equation model," Econometric Institute Report 263, Erasmus University Rotterdam, Econometric Institute. [Downloadable!]
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