Bayesian Prior Elicitation in DSGE Models: Macro- vs Micro-Priors

49 Pages Posted: 20 Jun 2013

See all articles by Marco J. Lombardi

Marco J. Lombardi

Bank for International Settlements (BIS) - Monetary and Economic Department

Giulio Nicoletti

European Central Bank

Date Written: September 21, 2011

Abstract

Bayesian approaches to the estimation of DSGE models are becoming increasingly popular. Prior knowledge is normally formalized either directly on deep parameters' values (‘microprior’) or indirectly, on macroeconomic indicators, e.g. moments of observable variables (‘macroprior’). We introduce a non-parametric macroprior which is elicited from impulse response functions and assess its performance in shaping posterior estimates. We find that using a macroprior can lead to substantially different posterior estimates. We probe into the details of our result, showing that model misspecification is likely to be responsible of that. In addition, we assess to what extent the use of macropriors is impaired by the need of calibrating some hyperparameters.

Keywords: DSGE models, Bayesian estimation, Prior distribution, Impulse response function

JEL Classification: C11, C51, E30

Suggested Citation

Lombardi, Marco Jacopo and Nicoletti, Giulio, Bayesian Prior Elicitation in DSGE Models: Macro- vs Micro-Priors (September 21, 2011). Journal of Economic Dynamics and Control, Vol. 36, No. 2, 2012, Available at SSRN: https://ssrn.com/abstract=2281811

Marco Jacopo Lombardi

Bank for International Settlements (BIS) - Monetary and Economic Department ( email )

Centralbahnplatz 2
CH-4002 Basel
Switzerland
+41612809492 (Phone)

Giulio Nicoletti (Contact Author)

European Central Bank ( email )

Kaiserstrasse 29
Frankfurt am Main, Hessen 60311
Germany

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