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

18340 10 104362 2 318051 document 104362 1-s2.0-S0169207022001224-main.pdf application/pdf 8022fefee5de88830da8918814326e1d MD5 1871350 2024-01-05 13:42:28 https://pure.iiasa.ac.at/id/eprint/18340/1/1-s2.0-S0169207022001224-main.pdf 18340 1 1 application/pdf text en public cc_by_4

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/104362 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/104362 http://eprints.org/relation/issmallThumbnailVersionOf https://pure.iiasa.ac.at/id/document/104362 archive 353 disk0/00/01/83/40 2022-11-03 08:38:46 2024-01-05 13:42:28 2022-11-03 08:38:46 article show Čapek J. Crespo Cuaresma J. 1838 Hauzenberger N. Reichel V. Macroeconomic forecasting in the euro area using predictive combinations of DSGE models pub POPJUS MIG Forecasting; Model averaging; Prediction pooling; DSGE models; Macroeconomic variables 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. 2022-10-21 published doi:10.1016/j.ijforecast.2022.09.002 58 public International Journal of Forecasting 39 4 1820-1838 TRUE 01692070 no info:eu-repo/semantics/article