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Und dann werfen wir den Computer an – Anmerkungen zur Methodik der DSGE-Modelle

  • Jochen Michaelis

    ()

    (University of Kassel)

Nicht alle Ökonomen teilen die Einschätzung des IWF-Chefökonomen, von den Nicht-Ökonomen ganz zu schweigen. Die Kluft zwischen den professionellen Makroökonomen und der (Fach-)Öffentlichkeit ist nicht zuletzt angesichts der Finanz- und Wirtschaftskrise größer geworden. Vordergründig mag dies in dem Vorwurf münden, die Makroökonomen hätten mit ihren Modellen die Krise nicht vorhergesehen, aber dies ist mehr Reflex der Unkenntnis dar-über, was Modelle leisten oder eben nicht leisten können. Etwas tiefer geht der Vorwurf, die in der Forschung dominierenden DSGE (Dynamic Stochastic General Equilibrium)-Modelle seien „blutleer“, die Makro reduziere sich weitgehend auf das Hantieren mit griechischen Buchstaben, die ökonomische Intuition ginge verloren. Wenn selbst solide ausgebildete Diplom-Volkswirte die Grundmechanismen von Schocks und/oder Politikmaßnahmen nicht mehr nachvollziehen können, dann geht die Akzeptanz und damit die entscheidende Bedingung für eine Umsetzung in die Wirtschaftspolitik verloren. Ziel dieses Beitrags ist es zu verdeutlichen, warum wir auf der einen Seite solche abstrakten Modelle für die Forschungsfront benö-tigen, warum wir aber gleichwohl bspw. im Hörsaal an dem Verwenden kleiner handlicher Modelle festhalten sollten

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Paper provided by Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung) in its series MAGKS Papers on Economics with number 201323.

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Length: 17 pages
Date of creation: 2013
Date of revision:
Publication status: Forthcoming in
Handle: RePEc:mar:magkse:201323
Contact details of provider: Postal: Universitätsstraße 25, 35037 Marburg
Phone: 06421/28-1722
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  9. Fabio Milani, 2012. "The Modeling of Expectations in Empirical DSGE Models: a Survey," Working Papers 121301, University of California-Irvine, Department of Economics.
  10. Edward C. Prescott, 1986. "Theory ahead of business cycle measurement," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Fall, pages 9-22.
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