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On the fit and forecasting performance of New-Keynesian models

Frank Smets, Raf Wouters (), Marco Del Negro () and Frank Schorfheide ()

No 491, Working Paper Series from European Central Bank

Abstract: The paper provides new tools for the evaluation of DSGE models, and applies it to a large-scale New Keynesian dynamic stochastic general equilibrium (DSGE) model with price and wage stickiness and capital accumulation. Specifically, we approximate the DSGE model by a vector autoregression (VAR), and then systematically relax the implied cross-equation restrictions. Let λ denote the extent to which the restrictions are being relaxed. We document how the in- and out-of sample fit of the resulting specification (DSGE-VAR) changes as a function of λ. Furthermore, we learn about the precise nature of the misspecification by comparing the DSGE model's impulse responses to structural shocks with those of the best-fitting DSGE-VAR. We find that the degree of misspecification in large-scale DSGE models is no longer so large to prevent their use in day-to-day policy analysis, yet it is not small enough that it cannot be ignored. JEL Classification: C11, C32, C53

Keywords: Bayesian analysis; DSGE models; model evaluation; vector autoregressions (search for similar items in EconPapers)
Date: 2005-06
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Related works:
Working Paper: On the Fit and Forecasting Performance of New Keynesian Models (2005) Downloads
Working Paper: On the fit and forecasting performance of New Keynesian models (2004) Downloads
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