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DSGE models for monetary policy analysis

  • Lawrence J. Christiano
  • Mathias Trabandt
  • Karl Walentin

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.

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Paper provided by Federal Reserve Bank of Atlanta in its series FRB Atlanta CQER Working Paper with number 2010-02.

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Date of creation: 2010
Date of revision:
Handle: RePEc:fip:fedacq:2010-02
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