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DSGE models for monetary policy analysis

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  • Lawrence J. Christiano
  • Mathias Trabandt
  • Karl Walentin

Abstract

Monetary DSGE models are widely used because they fit the data well and can be used to address important monetary policy questions. We provide a selective review of these developments. Policy analysis with DSGE models requires using data to assign numerical values to model parameters. The paper describes and implements Bayesian moment matching and impulse response matching procedures for this purpose.

Suggested Citation

  • Lawrence J. Christiano & Mathias Trabandt & Karl Walentin, 2010. "DSGE models for monetary policy analysis," FRB Atlanta CQER Working Paper 2010-02, Federal Reserve Bank of Atlanta, revised 2010.
  • Handle: RePEc:fip:fedacq:2010-02
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