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Priors from DSGE Models for Dynamic Factor Analysis

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Author Info
Gregor Bäurle

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Abstract

We propose a method to incorporate information from Dynamic Stochastic General Equilibrium (DSGE) models into Dynamic Factor Analysis. The method combines a procedure previously applied for Bayesian Vector Autoregressions and a Gibbs Sampling approach for Dynamic Factor Models. The factors in the model are rotated such that they can be interpreted as variables from a DSGE model. In contrast to standard Dynamic Factor Analysis, a direct economic interpretation of the factors is given. We evaluate the forecast performance of the model with respect to the amount of information from the DSGE model included in the estimation. We conclude that using prior information from a standard New Keynesian DSGE model improves the forecast performance. We also analyze the impact of identified monetary shocks on both the factors and selected series. The interpretation of the factors as variables from the DSGE model allows us to use an identification scheme which is directly linked to the DSGE model. The responses of the factors in our application resemble responses found using VARs. However, there are deviations from standard results when looking at the responses of specific series to common shocks.

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Paper provided by Universitaet Bern, Departement Volkswirtschaft in its series Diskussionsschriften with number dp0803.

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Date of creation: Aug 2008
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Handle: RePEc:ube:dpvwib:dp0803

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Related research
Keywords: Dynamic Factor Model; DSGE Model; Bayesian Analysis; Forecasting; Transmission of Shocks;

Find related papers by JEL classification:
C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Bayesian Analysis
C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions
E0 - Macroeconomics and Monetary Economics - - General

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  3. Uhlig, Harald, 1999. "What are the Effects of Monetary Policy on Output? Results from an Agnostic Identification Procedure," CEPR Discussion Papers 2137, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
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  6. Canova, Fabio, 2002. "Validating Monetary DSGE Models through VARs," CEPR Discussion Papers 3442, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
  7. Marco Del Negro & Frank Schorfheide, 2004. "Priors from General Equilibrium Models for VARS," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 45(2), pages 643-673, 05. [Downloadable!] (restricted)
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  8. Forni, Mario & Lippi, Marco & Reichlin, Lucrezia, 2003. "Opening the Black Box: Structural Factor Models versus Structural VARs," CEPR Discussion Papers 4133, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
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  10. James H. Stock & Mark W. Watson, 2005. "Implications of Dynamic Factor Models for VAR Analysis," NBER Working Papers 11467, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  11. Catherine Doz & Domenico Giannone & Lucrezia Reichlin, 2008. "A Quasi Maximum Likelihood Approach for Large Approximate Dynamic Factor Models," ECARES Working Papers 2008_034, Université Libre de Bruxelles, Ecares. [Downloadable!]
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  12. Jon Faust, 1998. "The robustness of identified VAR conclusions about money," International Finance Discussion Papers 610, Board of Governors of the Federal Reserve System (U.S.). [Downloadable!]
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  14. Giannone, Domenico & Reichlin, Lucrezia & Sala, Luca, 2006. "VARs, common factors and the empirical validation of equilibrium business cycle models," Journal of Econometrics, Elsevier, vol. 132(1), pages 257-279, May. [Downloadable!] (restricted)
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  15. Sargent, Thomas J, 1989. "Two Models of Measurements and the Investment Accelerator," Journal of Political Economy, University of Chicago Press, vol. 97(2), pages 251-87, April. [Downloadable!] (restricted)
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