Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/48723 
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dc.contributor.authorWolters, Maik H.en
dc.date.accessioned2011-08-12T09:51:32Z-
dc.date.available2011-08-12T09:51:32Z-
dc.date.issued2011-
dc.identifier.urihttp://hdl.handle.net/10419/48723-
dc.description.abstractThis paper investigates the accuracy of point and density forecasts of four dynamic stochastic general equilibrium (DSGE) models for output growth, inflation and the interest rate. The model parameters are estimated and forecasts are derived successively from historical U.S. data vintages synchronized with the Fed’s Greenbook projections. In addition, I compute weighted forecasts using simple combination schemes as well as likelihood based methods. While forecasts from structuralmodels fail to forecast large recessions and booms, they are quite accurate during normal times. Model forecasts compare particularly well to nonstructural forecasts and to Greenbook projections for horizons of three quarters ahead and higher. Weighted forecasts are more precise than forecasts from single models. A simple average of forecasts yields an accuracy comparable to the one obtained with state of the art time series methods that can incorporate large datasets. Comparing density forecasts of DSGE models with the actual distribution of observations shows that the models overestimate uncertainty around point forecasts.en
dc.language.isoengen
dc.publisherZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften, Leibniz-Informationszentrum Wirtschaft |xKiel und Hamburgen
dc.relation.ispartofseries|aBeiträge zur Jahrestagung des Vereins für Socialpolitik 2011: Die Ordnung der Weltwirtschaft: Lektionen aus der Krise - Session: Forecasting Methods |xG17-V2en
dc.subject.jelC53en
dc.subject.jelE32en
dc.subject.jelE37en
dc.subject.ddc330en
dc.subject.keywordDSGEen
dc.subject.keywordforecastingen
dc.subject.keywordmodel uncertaintyen
dc.subject.keyworddensity forecastsen
dc.subject.keywordbusiness cycle modelsen
dc.titleForecasting under Model Uncertainty-
dc.typeConference Paperen
dc.identifier.ppn671755013en
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen
dc.identifier.repecRePEc:zbw:vfsc11:48723en

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