Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/153723
Authors: 
Lombardi, Marco J.
Nicoletti, Giulio
Year of Publication: 
2011
Series/Report no.: 
ECB Working Paper 1289
Abstract: 
Bayesian approaches to the estimation of DSGE models are becoming increasingly popular. Prior knowledge is normally formalized either be information concerning deep parameters’ values (‘microprior’) or some macroeconomic indicator, e.g. moments of observable variables (‘macroprior’). In this paper we introduce a non parametric prior which is elicited from impulse response functions. Results show that using either a microprior or a macroprior can lead to different posterior estimates. We probe into the details of our result, showing that model misspecification is to blame for that.
Subjects: 
Bayesian estimation
DSGE Models
impulse response function
Prior Distribution
JEL: 
C11
C51
E30
Document Type: 
Working Paper

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