Macroeconomic forecasting in the euro area using predictive combinations of DSGE models

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Authors

ČAPEK Jan CRESPO CUARESMA Jesús HAUZENBERGER Niko REICHEL Vlastimil

Year of publication 2022
Type Article in Periodical
Magazine / Source INTERNATIONAL JOURNAL OF FORECASTING
MU Faculty or unit

Faculty of Economics and Administration

Citation
Web https://www.sciencedirect.com/science/article/pii/S0169207022001224
Doi http://dx.doi.org/10.1016/j.ijforecast.2022.09.002
Keywords Forecasting; Model averaging; Prediction pooling; DSGE models; Macroeconomic variables
Description We provide a comprehensive assessment of the predictive power 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 six different DSGE specifications and five prediction weighting schemes. Our results indicate that exploiting mixtures of DSGE models produces competitive forecasts compared to individual specifications for both point and density forecasts over the last three decades. Although these combinations do not tend to systematically achieve superior forecast performance, we find improvements for particular periods of time and variables when using prediction pooling, dynamic model averaging, and combinations of forecasts based on Bayesian predictive synthesis.
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