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VAR Information and the Empirical Validation of DSGE Models

Author

Listed:
  • Luca Sala

    (Universita' Bocconi)

  • Luca Gambetti

    (Universitat Autonoma de Barcelona)

  • Mario Forni

    (Università di Modena e Reggio Emilia)

Abstract

A shock of interest can be recovered, either exactly or with a good approximation, by means of standard VAR techniques even when the structural MA representation is noninvertible or nonfundamental, possibly because it has more shocks than variables. We propose a measure of how informative a VAR model is for a specific shock, or a subset of shocks, of interest. We show how to use such a measure for the validation of shocks’ transmission mechanism of DSGE models through VARs. In an application, we validate a theory of news shocks. The theory does remarkably well for all variables, except for consumption and output, for which the model over-predicts the effects of news shocks.

Suggested Citation

  • Luca Sala & Luca Gambetti & Mario Forni, 2016. "VAR Information and the Empirical Validation of DSGE Models," 2016 Meeting Papers 260, Society for Economic Dynamics.
  • Handle: RePEc:red:sed016:260
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    References listed on IDEAS

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    1. Jesús Fernández-Villaverde & Juan F. Rubio-Ramírez & Thomas J. Sargent & Mark W. Watson, 2007. "ABCs (and Ds) of Understanding VARs," American Economic Review, American Economic Association, vol. 97(3), pages 1021-1026, June.
    2. Mario Forni & Luca Gambetti & Luca Sala, 2014. "No News in Business Cycles," Economic Journal, Royal Economic Society, vol. 124(581), pages 1168-1191, December.
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    Cited by:

    1. Soccorsi, Stefano, 2016. "Measuring nonfundamentalness for structural VARs," Journal of Economic Dynamics and Control, Elsevier, vol. 71(C), pages 86-101.
    2. Iskrev, Nikolay, 2018. "Are asset price data informative about news shocks? A DSGE perspective," Working Paper Series 2161, European Central Bank.
    3. Mario Forni & Luca Gambetti & Luca Sala, 2017. "News, Uncertainty and Economic Fluctuations (No News is Good News)," Center for Economic Research (RECent) 132, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
    4. Bhattarai, Keshab & Mallick, Sushanta K. & Yang, Bo, 2021. "Are global spillovers complementary or competitive? Need for international policy coordination," Journal of International Money and Finance, Elsevier, vol. 110(C).
    5. Iskrev, Nikolay, 2019. "On the sources of information about latent variables in DSGE models," European Economic Review, Elsevier, vol. 119(C), pages 318-332.
    6. Daniele Siena, 2017. "What's News in International Business Cycles," 2017 Meeting Papers 1206, Society for Economic Dynamics.

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    More about this item

    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
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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