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Testing Identifiability of Cointegrating Vectors

Author

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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.

Suggested Citation

  • Boswijk, H Peter, 1996. "Testing Identifiability of Cointegrating Vectors," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(2), pages 153-160, April.
    • Handle: RePEc:bes:jnlbes:v:14:y:1996:i:2:p:153-60
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    Citations

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    Cited by:

    1. Helmut Lütkepohl, 2006. "Structural vector autoregressive analysis for cointegrated variables," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 90(1), pages 75-88, March.
    2. 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, November.
    3. Kerry Patterson & Michael A. Thornton, 2013. "A review of econometric concepts and methods for empirical macroeconomics," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 2, pages 4-42, Edward Elgar Publishing.
    4. Hunter, John & Menla Ali, Faek, 2014. "Money demand instability and real exchange rate persistence in the monetary model of USD–JPY exchange rate," Economic Modelling, Elsevier, vol. 40(C), pages 42-51.
    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(4), pages 705-744, October.
    6. Gary Koop & Rodney Strachan & Herman van Dijk & Mattias Villani, 2004. "Bayesian Approaches to Cointegration," Discussion Papers in Economics 04/27, Division of Economics, School of Business, University of Leicester.
    7. Castle, Jennifer L. & Kurita, Takamitsu, 2021. "A dynamic econometric analysis of the dollar-pound exchange rate in an era of structural breaks and policy regime shifts," Journal of Economic Dynamics and Control, Elsevier, vol. 128(C).
    8. 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.
    9. Rodney Strachan & Herman K. van Dijk, "undated". "Bayesian Model Averaging in Vector Autoregressive Processes with an Investigation of Stability of the US Great Ratios and Risk of a Liquidity Trap in the USA, UK and Japan," MRG Discussion Paper Series 1407, School of Economics, University of Queensland, Australia.
    10. Lok Sang Ho & Gary Wong, 2008. "Nexus Between Housing And The Macro Economy: The Hong Kong Case," Pacific Economic Review, Wiley Blackwell, vol. 13(2), pages 223-239, May.
    11. Strachan, Rodney W. & Inder, Brett, 2004. "Bayesian analysis of the error correction model," Journal of Econometrics, Elsevier, vol. 123(2), pages 307-325, December.
    12. Kleibergen, Frank & Paap, Richard, 2002. "Priors, posteriors and bayes factors for a Bayesian analysis of cointegration," Journal of Econometrics, Elsevier, vol. 111(2), pages 223-249, December.
    13. Jorg Breitung, 2005. "A Parametric approach to the Estimation of Cointegration Vectors in Panel Data," Econometric Reviews, Taylor & Francis Journals, vol. 24(2), pages 151-173.
    14. Paolo Paruolo, 2006. "The Likelihood Ratio Test for the Rank of a Cointegration Submatrix," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 68(s1), pages 921-948, December.
    15. 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.
    16. Ziesemer, Thomas, 2019. "The impact of mission-oriented R&D on domestic and foreign private and public R&D, total factor productivity and GDP," MERIT Working Papers 2019-047, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    17. Thomas H.W. Ziesemer, 2021. "Mission-oriented R&D and growth," Journal of Applied Economics, Taylor & Francis Journals, vol. 24(1), pages 460-477, January.
    18. Thomas H. W. Ziesemer, 2024. "Mission-oriented R&D and growth of Japan 1988–2016: a comparison with private and public R&D," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 33(2), pages 218-247, February.
    19. Christophe Rault, 2007. "Une synthèse de l'exogénéité dans les modèles vectoriels à correction d'erreurs," Post-Print halshs-00202651, HAL.
    20. Kurita, Takamitsu, 2020. "Normalising cointegrating relationships subject to long-run exclusion," Economics Letters, Elsevier, vol. 192(C).
    21. Ziesemer, Thomas, 2022. "Mission-oriented R&D and growth of Japan 1988-2016," MERIT Working Papers 2022-034, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    22. Gomez-Biscarri, Javier & Hualde, Javier, 2015. "Regression-based analysis of cointegration systems," Journal of Econometrics, Elsevier, vol. 186(1), pages 32-50.

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