On the Fit and Forecasting Performance of New Keynesian Models
Marco Del Negro (),
Frank Schorfheide (),
Frank Smets and
Raf Wouters ()
No 4848, CEPR Discussion Papers from C.E.P.R. Discussion Papers
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 delta 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 delta. 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.
Keywords: Bayesian Analysis; DSGE models; model evaluation; vector autoregression (search for similar items in EconPapers)
JEL-codes: C11 C32 C53 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-dge, nep-ecm and nep-ets
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Working Paper: On the fit and forecasting performance of New-Keynesian models (2005)
Working Paper: On the fit and forecasting performance of New Keynesian models (2004)
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