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Haavelmo's Probability Approach and the Cointegrated VAR

Author

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  • Katarina Juselius

    (Department of Economics)

Abstract
Some key econometric concepts and problems addressed by Trygve Haavelmo and Ragnar Frisch are discussed within the general framework of a cointegrated VAR. The focus is on problems typical of time series data such as multicollinearity, spurious correlation and regression results, time dependent residuals, normalization, reduced rank, model selection, missing variables, simultaneity, autonomy and identification. Specifically the paper discusses (1) the conditions under which the VAR model represents a full probability formulation of a sample of time-series observations, (2) the plausibility of the multivariate normality assumption underlying the VAR, (3) cointegration as a solution to the problem of spurious correlation and multicollinearity when data contain deterministic and stochastic trends, (4) the existence of a universe, (5) the association between Frisch's confluence analysis and cointegrated VAR analysis, (6) simultaneity and identification when data are nonstationary, (7) conditions under which identified cointegration relations can be considered structural or autonomous, and finally (8) a formulation of a design of experiment for passive observations based on theory consistent CVAR scenarios illustrated with a monetary model for inflation.

Suggested Citation

  • Katarina Juselius, 2012. "Haavelmo's Probability Approach and the Cointegrated VAR," Discussion Papers 12-01, University of Copenhagen. Department of Economics.
    • Handle: RePEc:kud:kuiedp:1201
    as

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    File URL: http://www.econ.ku.dk/english/research/publications/wp/dp_2012/1201.pdf
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    References listed on IDEAS

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    1. Juselius, Katarina, 1993. "VAR Modelling and Haavelmo's Probability Approach to Macroeconomic Modelling," Empirical Economics, Springer, vol. 18(4), pages 595-622.
    2. Henrik Hansen & Søren Johansen, 1999. "Some tests for parameter constancy in cointegrated VAR-models," Econometrics Journal, Royal Economic Society, vol. 2(2), pages 306-333.
    3. HENDRY, David F. & RICHARD, Jean-François, 1983. "The econometric analysis of economic time series," LIDAM Reprints CORE 531, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. Hendry,David F. & Morgan,Mary S., 1997. "The Foundations of Econometric Analysis," Cambridge Books, Cambridge University Press, number 9780521588706, September.
    5. Phillips, P.C.B., 1986. "Understanding spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 33(3), pages 311-340, December.
    6. Johansen, Soren & Juselius, Katarina, 1994. "Identification of the long-run and the short-run structure an application to the ISLM model," Journal of Econometrics, Elsevier, vol. 63(1), pages 7-36, July.
    7. 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.
    8. Davidson, James, 1998. "Structural relations, cointegration and identification: some simple results and their application," Journal of Econometrics, Elsevier, vol. 87(1), pages 87-113, August.
    9. Heino Bohn Nielsen, 2008. "Influential observations in cointegrated VAR models: Danish money demand 1973--2003," Econometrics Journal, Royal Economic Society, vol. 11(1), pages 39-57, March.
    10. Kongsted, Hans Christian, 2005. "Testing the nominal-to-real transformation," Journal of Econometrics, Elsevier, vol. 124(2), pages 205-225, February.
    11. Johansen, Soren, 1995. "Identifying restrictions of linear equations with applications to simultaneous equations and cointegration," Journal of Econometrics, Elsevier, vol. 69(1), pages 111-132, September.
    12. Juselius, Katarina, 2006. "The Cointegrated VAR Model: Methodology and Applications," OUP Catalogue, Oxford University Press, number 9780199285679.
    13. Garrone Giovanna & Marchionatti Roberto & Bellofiore Riccardo, 2004. "Keynes on econometric method. A reassessment of his debate with Tinbergen and econometricians, 1938-1943," CESMEP Working Papers 200401, University of Turin.
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    Cited by:

    1. Katarina Juselius, 2021. "Searching for a Theory That Fits the Data: A Personal Research Odyssey," Econometrics, MDPI, vol. 9(1), pages 1-27, February.
    2. Katarina Juselius, 2017. "Using a Theory-Consistent CVAR Scenario to Test an Exchange Rate Model Based on Imperfect Knowledge," Econometrics, MDPI, vol. 5(3), pages 1-20, July.
    3. Katarina Juselius, 2017. "A CVAR scenario for a standard monetary model using theory-consistent expectations," Discussion Papers 17-08, University of Copenhagen. Department of Economics.
    4. repec:cte:wsrepe:25392 is not listed on IDEAS
    5. Gričar Sergej & Baldigara Tea, 2019. "An explorative study of tourism time series: Evidence from Slovenia and Croatia," Croatian Review of Economic, Business and Social Statistics, Sciendo, vol. 5(2), pages 101-116, December.
    6. Juselius, Katarina & Stillwagon, Josh R., 2018. "Are outcomes driving expectations or the other way around? An I(2) CVAR analysis of interest rate expectations in the dollar/pound market," Journal of International Money and Finance, Elsevier, vol. 83(C), pages 93-105.

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    More about this item

    Keywords

    Haavelmo; CVAR; autonomy; identification; passive observations;
    All these keywords.

    JEL classification:

    • B16 - Schools of Economic Thought and Methodology - - History of Economic Thought through 1925 - - - Quantitative and Mathematical
    • B31 - Schools of Economic Thought and Methodology - - History of Economic Thought: Individuals - - - Individuals
    • 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
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access

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