Bayesian Dynamic Factor Analysis of a Simple Monetary DSGE Model /

When estimating DSGE models, the number of observable economic variables is usually kept small, and it is conveniently assumed that DSGE model variables are perfectly measured by a single data series. Building upon Boivin and Giannoni (2006), we relax these two assumptions and estimate a fairly simp...

Ausführliche Beschreibung

Bibliographische Detailangaben
1. Verfasser: Kryshko, Maxym
Format: Zeitschrift
Sprache:English
Veröffentlicht: Washington, D.C. : International Monetary Fund, 2011.
Schriftenreihe:IMF Working Papers; Working Paper ; No. 2011/219
Online Zugang:Full text available on IMF
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520 3 |a When estimating DSGE models, the number of observable economic variables is usually kept small, and it is conveniently assumed that DSGE model variables are perfectly measured by a single data series. Building upon Boivin and Giannoni (2006), we relax these two assumptions and estimate a fairly simple monetary DSGE model on a richer data set. Using post-1983 U.S.data on real output, inflation, nominal interest rates, measures of inverse money velocity, and a large panel of informational series, we compare the data-rich DSGE model with the regular - few observables, perfect measurement - DSGE model in terms of deep parameter estimates, propagation of monetary policy and technology shocks and sources of business cycle fluctuations. We document that the data-rich DSGE model generates a higher implied duration of Calvo price contracts and a lower slope of the New Keynesian Phillips curve. To reduce the computational costs of the likelihood-based estimation, we employed a novel speedup as in Jungbacker and Koopman (2008) and achieved the time savings of 60 percent. 
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