Forecasting with estimated dynamic stochastic general equilibrium models: The role of nonlinearities
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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- Jesús Fernández-Villaverde & Juan F. Rubio-Ramirez, 2006.
"Estimating Macroeconomic Models: A Likelihood Approach,"
122247000000000849, UCLA Department of Economics.
- Jes�s Fern�ndez-Villaverde & Juan F. Rubio-Ram�rez, 2007. "Estimating Macroeconomic Models: A Likelihood Approach," Review of Economic Studies, Oxford University Press, vol. 74(4), pages 1059-1087.
- Jesus Fernandez-Villaverde & Juan F. Rubio-Ramirez, 2006. "Estimating Macroeconomic Models: A Likelihood Approach," NBER Technical Working Papers 0321, National Bureau of Economic Research, Inc.
- Fernández-Villaverde, Jesús & Rubio-Ramírez, Juan Francisco, 2006. "Estimating Macroeconomic Models: A Likelihood Approach," CEPR Discussion Papers 5513, C.E.P.R. Discussion Papers.
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