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Merging structural and reduced-form models for forecasting: opening the DSGE-VAR box

Jaime Martinez-Martin (), Richard Morris, Luca Onorante () and Fabio M. Piersanti

No 2335, Working Paper Series from European Central Bank

Abstract: The post-crisis environment has posed important challenges to standard forecasting models. In this paper, we exploit several combinations of a large-scale DSGE structural model with standard reduced-form methods such as (B)VAR (i.e. DSGE-VAR and Augmented-(B)VARDSGE methods) and assess their use for forecasting the Spanish economy. Our empirical findings suggest that: (i) the DSGE model underestimates growth of real variables due to its mean reverting properties in the context of a sample that is difficult to deal with; (ii) in spite of this, reduced-form VARs benefit from the imposition of an economic prior from the structural model; and (iii) pooling information in the form of variables extracted from the structural model with (B)VAR methods does not give rise to any relevant gain in terms of forecasting accuracy. JEL Classification: C54, E37, F3, F41

Keywords: Bayesian VAR; DSGE models; forecast comparison; real time data (search for similar items in EconPapers)
Date: 2019-12
New Economics Papers: this item is included in nep-ets, nep-for and nep-ore
Note: 3767361
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