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.
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Paper provided by University of Vienna, Department of Economics in its series Vienna Economics Papers with number
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Find related papers by JEL classification: C68 - Mathematical and Quantitative Methods - - Mathematical Methods and Programming - - - Computable General Equilibrium Models E47 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Forecasting and Simulation E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
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