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Forecasting with estimated dynamic stochastic general equilibrium models: The role of nonlinearities

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  • Paul Pichler

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Abstract

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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File URL: http://homepage.univie.ac.at/Papers.Econ/RePEc/vie/viennp/vie0702.pdf
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Bibliographic Info

Paper provided by University of Vienna, Department of Economics in its series Vienna Economics Papers with number 0702.

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Date of creation: Mar 2007
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Handle: RePEc:vie:viennp:0702

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Web page: http://www.univie.ac.at/vwl

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  1. 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.
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Cited by:
  1. Ahmed, Shahzad & Ahmed, Waqas & Khan, Sajawal & Pasha, Farooq & Rehman, Muhammad, 2012. "Pakistan Economy DSGE Model with Informality," MPRA Paper 53135, University Library of Munich, Germany.

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