European Business Schools Librarian's Group
Department of Economics Working Papers,
Vienna University of Economics and Business, Department of Economics
Macroeconomic forecasting in the euro area using predictive combinations of DSGE models
Jan Capek (), Jesus Crespo Cuaresma (), Niko Hauzenberger () and Vlastimil Reichel ()
Additional contact information
Jan Capek: Masaryk University
Jesus Crespo Cuaresma: Department of Economics, Vienna University of Economics and Business
Niko Hauzenberger: University of Salzburg
Vlastimil Reichel: Masaryk University
Abstract: We provide a comprehensive assessment of the predictive ability of combinations of Dynamic Stochastic General Equilibrium (DSGE) models for GDP growth, inflation and the interest rate in the euro area. We employ a battery of static and dynamic pooling weights based on Bayesian model averaging principles, prediction pools and dynamic factor representations, and entertain eight different DSGE specifications and four prediction weighting schemes. Our results indicate that exploiting mixtures of DSGE models tends to achieve superior forecasting performance over individual specifications for both point and density forecasts. The largest improvements in the accuracy of GDP growth forecasts are achieved by the prediction pooling technique, while the results for the weighting method based on dynamic factors partly leads to improvements in the quality of inflation and interest rate predictions.
Keywords: Forecasting, model averaging, prediction pooling, DSGE models
JEL-codes: E37; E47; C53 November 2020
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