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Testing Identifiability of Cointegrating Vectors

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  • Boswijk, H Peter

Abstract

This paper analyzes the identification and normalization of cointegrating vectors. Normalizing a cointegrating relation with respect to one of the relevant variables is with loss of generality; and restrictions which are supposed to identify a vector may fail to do so for particular parameter values. The author proposes to tackle both problems by testing whether particular rank conditions are violated. He shows that S. Johansen and K. Juselius's (1992) class of likelihood ratio statistics for structural hypotheses in a Gaussian vector autoregression may be used for this purpose. The tests are applied to a model of the demand for money in the United Kingdom.

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Bibliographic Info

Article provided by American Statistical Association in its journal Journal of Business and Economic Statistics.

Volume (Year): 14 (1996)
Issue (Month): 2 (April)
Pages: 153-60

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Handle: RePEc:bes:jnlbes:v:14:y:1996:i:2:p:153-60

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Cited by:
  1. Breitung, Jörg, 2002. "A parametric approach to the estimation of cointegration vectors in panel data," SFB 373 Discussion Papers 2002,3, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
  2. Heejoon Kang, 1999. "The Applied Cointegration Analysis for the Open Economy: A Critical Review," Open Economies Review, Springer, vol. 10(3), pages 325-346, July.
  3. Paruolo Paolo, 2004. "The likelihood ratio test for the rank of a cointegration submatrix," Economics and Quantitative Methods qf04024, Department of Economics, University of Insubria.
  4. H. Peter Boswijk & Jurgen A. Doornik, 2004. "Identifying, estimating and testing restricted cointegrated systems: An overview," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 58(4), pages 440-465.
  5. Pitruzzello, Salvatore, 2004. "Trade Globalization, Economic Performance, and Social Protection: Nineteenth-Century British Laissez-Faire and Post World War II U.S.-Embedded Liberalism," International Organization, Cambridge University Press, vol. 58(04), pages 705-744, October.
  6. Strachan, Rodney W. & Inder, Brett, 2004. "Bayesian analysis of the error correction model," Journal of Econometrics, Elsevier, vol. 123(2), pages 307-325, December.
  7. Breitung, Jörg, 1998. "Canonical correlation statistics for testing the cointegration rank in a reversed order," SFB 373 Discussion Papers 1998,105, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
  8. Helmut Luetkepohl, 2005. "Structural Vector Autoregressive Analysis for Cointegrated Variables," Economics Working Papers ECO2005/02, European University Institute.
  9. Kleibergen, F.R. & Paap, R., 1998. "Priors, posteriors and Bayes factors for a Bayesian analysis of cointegration," Econometric Institute Research Papers EI 9821, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

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