Forecasting Performance of an Open Economy Dynamic Stochastic General Equilibrium Model
Malin Adolfson (),
Jesper Lindé and
No 190, Working Paper Series from Sveriges Riksbank (Central Bank of Sweden)
This paper analyzes the forecasting performance of an open economy DSGE model, estimated with Bayesian methods, for the Euro area during 1994Q1-2002Q4. We compare the DSGE model and a few variants of this model to various reduced form forecasting models such as vector autoregressions (VAR) and vector error correction models (VECM), estimated both by maximum likelihood and two different Bayesian approaches, and traditional benchmark models, e.g. the random walk. The accuracy of point forecasts, interval forecasts and the predictive distribution as a whole are assessed in an out-of-sample rolling event evaluation using several univariate and multivariate measures. The results show that the open economy DSGE model compares well with more empirical models and thus that the tension between rigor and fit in older generations of DSGE models is no longer present. We also critically examine the role of Bayesian model probabilities and other frequently used low-dimensional summaries, e.g. the log determinant statistic, as measures of overall forecasting performance.
Keywords: Bayesian inference; Forecasting; Open economy DSGE model; Vector autoregressive models (search for similar items in EconPapers)
JEL-codes: C11 C32 E37 E47 (search for similar items in EconPapers)
Pages: 39 pages
Date: 2005-09-01, Revised 2006-06-01
New Economics Papers: this item is included in nep-dge, nep-ecm, nep-for and nep-mac
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Working Paper: Forecasting Performance of an Open Economy Dynamic Stochastic General Equilibrium Model (2005)
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Persistent link: https://EconPapers.repec.org/RePEc:hhs:rbnkwp:0190
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