Forecasting with estimated dynamic stochastic general equilibrium models: The role of nonlinearities
Paul Pichler ()
Vienna Economics Papers from University of Vienna, Department of Economics
In this paper we study the e®ects of nonlinearities on the forecast- ing performance of a dynamic stochastic general equilibrium model. We compute ¯rst and second-order approximations to a New Keyne- sian monetary model, and use arti¯cial data to estimate the model's structural parameters based on its linear and quadratic solution. We and that, although our model in not far from being linear, the fore- casting performance improves by capturing the second-order terms in the solution. Our ¯ndings suggest that accounting for nonlinearities will improve the predictive abilities of DSGE models in many appli- cations.
JEL-codes: C68 E47 E52 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-dge, nep-for, nep-ias and nep-mac
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Persistent link: https://EconPapers.repec.org/RePEc:vie:viennp:0702
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