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Detecting And Analyzing The Effects Of Time‐Varying Parameters In Dsge Models

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  • Fabio Canova
  • Filippo Ferroni
  • Christian Matthes

Abstract

We study how structural parameter variations affect the decision rules and economic inference. We provide diagnostics to detect parameter variations and to ascertain whether they are exogenous or endogenous. A constant parameter model poorly approximates a time‐varying data generating process (DGP), except in a handful of relevant cases. Linear approximations do not produce time‐varying decision rules; higher‐order approximations can do this only if parameter disturbances are treated as decision rule coefficients. Structural responses are time invariant regardless of order of approximation. Adding endogenous variations to the parameter controlling leverage in Gertler and Karadi's model substantially improves the fit of the model.

Suggested Citation

  • Fabio Canova & Filippo Ferroni & Christian Matthes, 2020. "Detecting And Analyzing The Effects Of Time‐Varying Parameters In Dsge Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 61(1), pages 105-125, February.
  • Handle: RePEc:wly:iecrev:v:61:y:2020:i:1:p:105-125
    DOI: 10.1111/iere.12418
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    Cited by:

    1. Pablo Cuba‐Borda & Luca Guerrieri & Matteo Iacoviello & Molin Zhong, 2019. "Likelihood evaluation of models with occasionally binding constraints," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(7), pages 1073-1085, November.
    2. Aguirre, Idoia & Vázquez, Jesús, 2020. "Learning, parameter variability, and swings in US macroeconomic dynamics," Journal of Macroeconomics, Elsevier, vol. 66(C).
    3. Julien Albertini & Stéphane Moyen, 2020. "A General and Efficient Method for Solving Regime-Switching DSGE Models," Working Papers 2035, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.

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