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Allowing the Data to Speak Freely: The Macroeconometrics of the Cointegrated Vector Autoregression

Author

Listed:
  • Kevin D. Hoover

    (Duke University)

  • Katarina Juselius

    (Department of Economics, University of Copenhagen)

  • Søren Johansen

    (Department of Economics, University of Copenhagen)

Abstract

An explication of the key ideas behind the Cointegrated Vector Autoregression Approach. The CVAR approach is related to Haavelmo’s famous “Probability Approach in Econometrics” (1944). It insists on careful stochastic specification as a necessary groundwork for econometric inference and the testing of economic theories. In time-series data, the probability approach requires careful specification of the integration and cointegration properties of variables in systems of equations. The relationship between the CVAR approach and wider methodological issues and between it and related approaches (e.g., the LSE approach) are explored. The specific-to-general strategy of widening the scope of econometric models to identify stochastic trends and cointegrating relations and to nest theoretical economic models is illustrated with the example of purchasing-power parity

Suggested Citation

  • Kevin D. Hoover & Katarina Juselius & Søren Johansen, 2007. "Allowing the Data to Speak Freely: The Macroeconometrics of the Cointegrated Vector Autoregression," Discussion Papers 07-35, University of Copenhagen. Department of Economics.
    • Handle: RePEc:kud:kuiedp:0735
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    References listed on IDEAS

    as
    1. Søren Johansen & Katarina Juselius & Roman Frydman & Michael Goldberg, 2007. "Testing Hypotheses in an I(2) Model with Applications to the Persistent Long Swings in the Dmk/$ Rate," Discussion Papers 07-34, University of Copenhagen. Department of Economics.
    2. Ireland, Peter N., 2004. "A method for taking models to the data," Journal of Economic Dynamics and Control, Elsevier, vol. 28(6), pages 1205-1226, March.
    3. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    4. Franchi, Massimo & Jusélius, Katarina, 2007. "Taking a DSGE Model to the Data Meaningfully," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 1, pages 1-38.
    5. Hendry, David F., 1995. "Dynamic Econometrics," OUP Catalogue, Oxford University Press, number 9780198283164, Decembrie.
    6. Colander,David (ed.), 2006. "Post Walrasian Macroeconomics," Cambridge Books, Cambridge University Press, number 9780521865487, Enero-Abr.
    7. Juselius, Katarina, 2006. "The Cointegrated VAR Model: Methodology and Applications," OUP Catalogue, Oxford University Press, number 9780199285679, Decembrie.
    8. Colander,David (ed.), 2006. "Post Walrasian Macroeconomics," Cambridge Books, Cambridge University Press, number 9780521684200, Enero-Abr.
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    More about this item

    Keywords

    cointegrated VAR; stochastic trends; Purchasing Power Parity;
    All these keywords.

    JEL classification:

    • B41 - Schools of Economic Thought and Methodology - - Economic Methodology - - - Economic Methodology
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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