EconStor >
Verein für Socialpolitik >
Jahrestagung des Vereins für Socialpolitik 2010: Ökonomie der Familie >

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10419/37455
  
Title:Forecasting with DSGE Models PDF Logo
Authors:Coenen, Günter
Christoffel, Kai
Warne, Anders
Issue Date:2010
Series/Report no.:Beiträge zur Jahrestagung des Vereins für Socialpolitik 2010: Ökonomie der Familie - Session: Forecasting Methods A11-V1
Abstract:In this paper we review the methodology of forecasting with log-linearised DSGE models using Bayesian methods. We focus on the estimation of their predictive distributions, with special attention being paid to the mean and the covariance matrix of h-steps ahead forecasts. In the empirical analysis, we examine the forecasting performance of the New Area-Wide Model (NAWM) that has been designed for use in the macroeconomic projections at the European Central Bank. The forecast sample covers the period following the introduction of the euro and the out-of-sample performance of the NAWM is compared to nonstructural benchmarks, such as Bayesian vector autoregressions (BVARs). Overall, the empirical evidence indicates that the NAWM compares quite well with the reduced-form models and the results are therefore in line with previous studies. Yet there is scope for improving the NAWM's forecasting performance. For example, the model is not able to explain the moderation in wage growth over the forecast evaluation period and, therefore, it tends to overestimate nominal wages. As a consequence, both the multivariate point and density forecasts using the log determinant and the log predictive score, respectively, suggest that a large BVAR can outperform the NAWM.
Subjects:Bayesian inference
DSGE models
euro area
forecasting
open-economy macroeconomics
vector autoregression
JEL:C11
C32
E32
Document Type:Conference Paper
Appears in Collections:Jahrestagung des Vereins für Socialpolitik 2010: Ökonomie der Familie

Files in This Item:
File Description SizeFormat
VfS_2010_pid_943.pdf498.92 kBAdobe PDF
No. of Downloads: Counter Stats
Download bibliographical data as: BibTeX
Share on:http://hdl.handle.net/10419/37455

Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.