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How good is what you've got? DSGE-VAR as a toolkit for evaluating DSGE models

  • Marco Del Negro
  • Frank Schorfheide

In the constant search for better models to help guide policy decisions, central banks have begun to use and develop dynamic stochastic general equilibrium (DSGE) models. Although such models were until recently considered theoretically sound but overly restrictive, newly developed methods have proved successful in specifying DSGE models that fit the macroeconomic data well. ; Policy institutions that use DSGE models in policymaking need a reliable method for evaluating the models’ effectiveness. This article reviews a procedure recently proposed by the authors and their colleagues. The article first describes how the linear DSGE model can be nested in a vector autoregression (VAR) and then outlines a procedure that can systematically relax the restrictions the DSGE model imposes on the VAR. ; Using the resulting DSGE-VAR specification as a framework, the authors compare the fit and forecasting performance of a DSGE model with several nominal and real rigidities. They use the DSGE-VAR framework to assess the relative importance of different frictions, with particular emphasis on wage and price indexation and habit formation. The DSGE-VAR framework also provides a benchmark that can reveal in what dimensions a DSGE model needs to be improved. ; This DSGE-VAR procedure, the authors believe, shows some promise in delivering robust evaluations of DSGE models.>

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Article provided by Federal Reserve Bank of Atlanta in its journal Economic Review.

Volume (Year): (2006)
Issue (Month): Q 2 ()
Pages: 21-37

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Handle: RePEc:fip:fedaer:y:2006:i:q2:p:21-37:n:v.91no.2
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  1. DeJong, David N. & Ingram, Beth F. & Whiteman, Charles H., 2000. "A Bayesian approach to dynamic macroeconomics," Journal of Econometrics, Elsevier, vol. 98(2), pages 203-223, October.
  2. Lawrence J. Christiano & Martin Eichenbaum & Charles L. Evans, 2005. "Nominal Rigidities and the Dynamic Effects of a Shock to Monetary Policy," Journal of Political Economy, University of Chicago Press, vol. 113(1), pages 1-45, February.
  3. Kydland, Finn E & Prescott, Edward C, 1982. "Time to Build and Aggregate Fluctuations," Econometrica, Econometric Society, vol. 50(6), pages 1345-70, November.
  4. Altig, David E & Christiano, Lawrence J. & Eichenbaum, Martin & Lindé, Jesper, 2005. "Firm-Specific Capital, Nominal Rigidities and the Business Cycle," CEPR Discussion Papers 4858, C.E.P.R. Discussion Papers.
  5. Del Negro, Marco & Schorfheide, Frank & Smets, Frank & Wouters, Rafael, 2005. "On the Fit and Forecasting Performance of New Keynesian Models," CEPR Discussion Papers 4848, C.E.P.R. Discussion Papers.
  6. Marco Del Negro & Frank Schorfheide, 2002. "Priors from general equilibrium models for VARs," Working Paper 2002-14, Federal Reserve Bank of Atlanta.
  7. Fernandez-Villaverde, Jesus & Francisco Rubio-Ramirez, Juan, 2004. "Comparing dynamic equilibrium models to data: a Bayesian approach," Journal of Econometrics, Elsevier, vol. 123(1), pages 153-187, November.
  8. David Altig & Lawrence Christiano & Martin Eichenbaum & Jesper Linde, 2005. "Online Appendix to "Firm-Specific Capital, Nominal Rigidities and the Business Cycle"," Technical Appendices 09-191, Review of Economic Dynamics.
  9. James H. Stock & Mark W. Watson, 2003. "Has the Business Cycle Changed and Why?," NBER Chapters, in: NBER Macroeconomics Annual 2002, Volume 17, pages 159-230 National Bureau of Economic Research, Inc.
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