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Taking a DSGE Model to the Data Meaningfully


  • Franchi, Massimo
  • Jusélius, Katarina


All economists say that they want to take their models to the data. But with incomplete and highly imperfect data, doing so is difficult and requires carefully matching the assumptions of the model with the statistical properties of the data. The cointegrated VAR (CVAR) offers a way of doing so. In this paper we outline a method for translating the assumptions underlying a DSGE model into a set of testable assumptions on a cointegrated VAR model and illustrate the ideas with the RBC model in Ireland (2004). Accounting for unit roots (near unit roots) in the model is shown to provide a powerful robustification of the statistical and economic inference about persistent and less persistent movements in the data. We propose that all basic assumptions underlying the theory model should be formulated as a set of testable hypotheses on the long-run structure of a CVAR model, a so called 'theory consistent hypothetical scenario'. The advantage of such a scenario is that it forces us to formulate all testable implications of the basic hypotheses underlying a theory model. We demonstrate that most assumptions underlying the DSGE model and, hence, the RBC model are rejected when properly tested. Leaving the RBC model aside, we then report a structured CVAR analysis that summarizes the main features of the data in terms of long-run relations and common stochastic trends. We argue that structuring the data in this way offers a number of 'sophisticated' stylized facts that a theory model should replicate in order to claim empirical relevance.

Suggested Citation

  • Franchi, Massimo & Jusélius, Katarina, 2007. "Taking a DSGE Model to the Data Meaningfully," Economics - The Open-Access, Open-Assessment E-Journal, Kiel Institute for the World Economy (IfW), vol. 1, pages 1-38.
  • Handle: RePEc:zbw:ifweej:5739

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    References listed on IDEAS

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    Cited by:

    1. David Colander, 2010. "The Keynesian Method, Complexity, and the Training of Economists," Middlebury College Working Paper Series 1035, Middlebury College, Department of Economics.
    2. Juselius, Katarina, 2014. "Testing for near I(2) trends when the signal-to-noise ratio is small," Economics - The Open-Access, Open-Assessment E-Journal, Kiel Institute for the World Economy (IfW), vol. 8, pages 1-30.
    3. Fabio Bacchini & Cristina Brandimarte & Piero Crivelli & Roberta De Santis & Marco Fioramanti & Alessandro Girardi & Roberto Golinelli & Cecilia Jona-Lasinio & Massimo Mancini & Carmine Pappalardo & D, 2013. "Building the core of the Istat system of models for forecasting the Italian economy: MeMo-It," Rivista di statistica ufficiale, ISTAT - Italian National Institute of Statistics - (Rome, ITALY), vol. 15(1), pages 17-45.
    4. Giorgio Fagiolo & Andrea Roventini, 2012. "Macroeconomic Policy in DSGE and Agent-Based Models," Revue de l'OFCE, Presses de Sciences-Po, vol. 0(5), pages 67-116.
    5. J. Barkley Rosser Jr & Richard P.F. Holt & David Colander, 2010. "European Economics at a Crossroads," Books, Edward Elgar Publishing, number 13585.
    6. Juselius, Katarina, 2015. "Haavelmo’S Probability Approach And The Cointegrated Var," Econometric Theory, Cambridge University Press, vol. 31(02), pages 213-232, April.
    7. Paul De Grauwe, 2012. "Lectures on Behavioral Macroeconomics," Economics Books, Princeton University Press, edition 1, number 9891.
    8. Barbara Dluhosch, 2011. "European Economics at a Crossroads, by J. Barkley Rosser, Jr., Richard P. F. Holt, and David Colander," Journal of Regional Science, Wiley Blackwell, vol. 51(3), pages 629-631, August.
    9. Kevin D. Hoover & Soren Johansen & Katarina Juselius, 2008. "Allowing the Data to Speak Freely: The Macroeconometrics of the Cointegrated Vector Autoregression," American Economic Review, American Economic Association, vol. 98(2), pages 251-255, May.
    10. Johansen, Søren & Juselius, Katarina & Frydman, Roman & Goldberg, Michael, 2010. "Testing hypotheses in an I(2) model with piecewise linear trends. An analysis of the persistent long swings in the Dmk/$ rate," Journal of Econometrics, Elsevier, vol. 158(1), pages 117-129, September.
    11. Dilip Nachane, 2017. "Dynamic Stochastic General Equilibrium (DSGE) Modelling :Theory And Practice," Working Papers id:11699, eSocialSciences.

    More about this item


    DSGE; RBC; cointegrated VAR;

    JEL classification:

    • 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
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles


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